Atkins Final Report WP3&4 `

Atkins final report WP3&4 `

ATKINS Final Report – Work packages 3 & 4 -

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Contents Pages

WP3.1 – Supply chain elements & 3.2 – Logistics structure ...... 7 Introduction ...... 7 Part Investigation ...... 7 Background to part selection ...... 7 Identification of components ...... 8 Data & supply chain limitations ...... 9 Supply Chain Analysis of Alcon Components ...... 10 Part: Car 22 Brake Calliper ...... 10 Comments and assumptions ...... 10

Supply chain map – Alcon - Car 22 Brake Calliper ...... 11

Supply Chain Analysis of Bentley Components ...... 13 Part: Transmission Mount Bracket ...... 13 Comments and assumptions ...... 13

Supply chain map – Bentley – Transmission Mount Bracket – Scenario 1 ...... 14

Supply chain map – Bentley – Transmission Mount Bracket – Scenario 2 ...... 15

Supply Chain Analysis of Boeing Components ...... 16 Part: Eggcrate Clip – 787 ...... 17 Comments and assumptions ...... 17

Supply chain map – Boeing – Eggcrate Clip ...... 18

Part: Termination Fitting – 787 ...... 19 Comments and assumptions ...... 19

Supply chain map – Boeing – Termination Fitting ...... 20

Part: Sill Fitting ...... 21 Comments and assumptions ...... 21

Supply chain map – Boeing – Sill Fitting ...... 22

Part: Floor Beam End Fitting – 787 ...... 23 Comments and assumptions ...... 23

Supply chain map – Boeing – Floor Beam End Fitting ...... 24

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Part: Pan Casting – 737 ...... 25 Comments and assumptions ...... 25

Supply chain map – Boeing – Pan casting ...... 26

Part: 12’’ Strut Inlet Duct – 777 ...... 27

Comments and assumptions ...... 27

Supply chain map – Boeing – 12’’ Strut Inlet Duct ...... 28

Part: Elevator Link – 777 ...... 29

Comments and assumptions ...... 29

Supply chain map – Boeing - Elevator Link ...... 30

Supply Chain Analysis of Delphi Components ...... 31 Part: Diesel Front Plate 3 (DFP3) ...... 31 Comments and assumptions ...... 33

Supply chain map – Delphi - Diesel Front Plate 3 – Gravity cast – Scenario 1 ...... 34

Supply chain map – Delphi - Diesel Front Plate 3 – Gravity cast– Scenario 2 ...... 35

Part: Diesel Front Plate 3 (DFP3) – Squeeze Cast ...... 36 Comments and assumptions ...... 36

Supply chain map – Delphi - Diesel Front Plate 3 (DFP3) – Squeeze Cast ...... 37

Part: Pump Housing ...... 38 Comments and assumptions ...... 38

Supply chain map – Delphi – Pump Housing ...... 39

Part: Venturi ...... 40 Comments and assumptions ...... 40

Supply chain map – Delphi - Venturi ...... 41

Part: ECU ...... 42 Part: Fuel Connector ...... 43 Comments and assumptions ...... 43

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Supply chain map – Delphi – Fuel Connector ...... 45

Supply Chain Analysis of Virgin Components ...... 46 Part: Upper class monitor arm ...... 46 Part: Economy tray table arm ...... 48 Part: Front row monitor arm ...... 49 Part: Foot rest plate ...... 50 Part: Premier economy tray table arm...... 51 WP2 – Assessment of traditional manufacturing ...... 52 Methodology ...... 52 Life cycle stages assessed ...... 52 Raw material & Process Energy ...... 54 Recycling...... 55

CO2 Calculations ...... 56 Fuel mix ...... 56

Conversion factors ...... 59

Distribution and transport ...... 62

Usage ...... 64

End-of-life ...... 65

References ...... 66

Findings ...... 68 Results tables ...... 68 Findings and discussion ...... 74 Part Mass ...... 75

Location differences...... 76

Recycled content...... 79

Material selection ...... 81

Processing ...... 83

Transport ...... 84

Usage ...... 85

End-of-Life ...... 87

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Reductions ...... 89 Limitations and key assumptions ...... 94 References ...... 97

WP3.3 – Roadmap for Distributed AM & WP4 – Digital Distributed Supply Chain Configuration ...... 99 Introduction ...... 99 Material Selection ...... 99 Processes ...... 100 Material Preparation ...... 101 Metal powder forming ...... 102

Polymer powder forming ...... 103

Extrusion ...... 104

Support Structure ...... 105 Control Parameters ...... 105 Packing Efficiency & Orientation...... 105

Post-Processing ...... 106 Support Removal ...... 107

Logistic Factors ...... 107 Usage ...... 108 End of Life ...... 108 References ...... 109 AM Supply Chain Analysis of Additive Bentley Components ...... 110 Part: Transmission Mount Bracket ...... 110 Additional material requirements: ...... 110

Supply Chain Data ...... 110

Supply Chain Analysis of Additive Boeing Components ...... 111 Part: Eggcrate Clip ...... 111 Additional material requirements: ...... 111

Supply Chain Data ...... 111

Supply Chain Analysis of Additive Delphi Components ...... 112 Part: Pump Housing ...... 112 Additional material requirements: ...... 112

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Supply Chain Data ...... 112

Supply Chain Analysis of Additive Virgin Components ...... 113 Part: Upper Class Monitor Arm ...... 113 Additional material requirements: ...... 113

Supply Chain Data ...... 113

Findings ...... 114 Results tables ...... 114 Findings and discussion ...... 117 Raw Material ...... 117

Processing ...... 117

Transport ...... 117

Usage ...... 118

End-of-Life ...... 118

Totals...... 118

References ...... 119

WP3 & 4 outcome – Low Carbon Supply Chain Software Toolkit ...... 120 enlighten ...... 120 Approach ...... 121 Development of web based software solution for AM carbon footprint analysis ...... 122 CONTACT DETAILS ...... 123

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WP3.1 – Supply chain elements & 3.2 – Logistics structure

Introduction

This report provides a detailed description of the supply chain steps associated with a series of component parts identified by the Atkins partnership. The parts in question have all been identified as suitable candidates for redesign and manufacture using the selective laser melting process, which is at the heart of the Atkins project. Within this report we will look at each of the parts in detail (where information is known) and the different supply chain elements, such as manufacturing processes (M3.1) and logistics pathways (M3.2) involved in the production of these parts. This will provide us with the raw data that we need to establish the Business, Resource, Efficiency and Waste (BREW) metrics for each of these components where produced by traditional manufacturing, and provide benchmark data against which we can compare production using the selective laser melting process later within this report.

Part Investigation

Background to part selection

The parts included in this report were selected during Work Package 1 (WP1) of the Atkins project. A series of selection criteria were initially adopted against which the parts have been selected. These criteria included:

Component manufactured from either Titanium or Aluminium (both materials that can be processed using the SLM process).

o NOTE – A small number of the components chosen for evaluations are currently made from both injection moulded polymer and Zinc dies casting. They have been included as it is intended to replace them with aluminium parts produced using SLM.

Component manufactured by CNC machining with a high ratio of waste materials relative to the final part (alternatively described as a poor buy-to-fly ratio).

Component that could be significantly reduced in material, if manufactured using the SLM process rather than CNC machining from solid billet or casting.

Component that could be significantly reduced in weight, if manufactured using the SLM process.

Component of a suitable size to fit within the build envelop of an SLM machine tool.

Component that could be improved in overall performance efficiency through innovative design that exploits the capabilities of the SLM process.

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Component made in production quantities that make conventional manufacture economically or sustainably difficult to justify.

Identification of components

Table 1 below details each of the component parts identified in WP1 by the Atkins project partners, including the current material type and grade.

Availability of Company Part Material Used traditional supply chain data Alcon Brake Calipers Aluminium AL2618-T6 Partial Bonnet Release System Aluminium 6082 T6 No Bentley Aluminium 6082 T6 Yes Transmission Mount Bracket Zinc-aluminium alloy, Alloy 3 Yes Eggcrate Clip Titanium Ti-6Al-4V Yes Termination Fitting Titanium Ti-6Al-4V Yes Sill Fitting Titanium Ti-6Al-4V Yes Floor Beam End Fitting Titanium Ti-6Al-4V Yes Actuator Fitting Titanium Ti6Al4 No Boeing Duct Support Fitting Titanium Ti6Al4 No Pan Casting Titanium Ti-6Al-4V Yes Fitting Casting – Tire Burst Protector No 12’’ Strut Inlet Duct Titanium Ti-6Al-4V Yes Elevator Link Titanium Ti-6Al-4V Yes Diesel Front Plate 3 AC-AlSi9Cu3 (FE) DF Yes Pump Housing Aluminium AL Si8 Yes Delphi Venturi Nylon 66 (30% GF) Yes ECU Aluminium + Various No Fuel Connector Aluminium Partial Upper Class Monitor Arm Aluminium AL2014 Partial Economy Tray Table Arm Al 2014 No Virgin Front Row Monitor Arm Al 2014 No Foot Rest Plate Al 2014 No Premium Economy Tray Table Arm Al 2014 No

Table 1 - Atkins component geometries and status of supply chain data

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Data & supply chain limitations

One of the most interesting early findings from the Atkins project has been the availability & lack of availability of data relating to the supply chain within different partners. In partners with vertically integrated supply chains such as Delphi and Alcon, it has been relatively simple to map the manufacturing supply chain from raw materials, to at minimum part assembly, and in some cases delivery to the customer. However, in more matrix orientated supply chains, such as Bentley and Boeing, it has been almost impossible to collate the same level of management information. In some cases this is simply a function of organisational structure, cross platform part sharing or simply the lack of data on older legacy parts. Lack of available data has also been a factor when the Atkins partner has been towards the top end of a complex supply chain such as Bentley, where primary manufacturing from raw material is undertaken a number of tiers back down the chain from the Atkins partner. In such cases, although it is possible to identify the immediate top tier suppliers in great detail, it is not always possible to look ‘back past the supplier’ to their subcontractors or material suppliers. Hence, a number of assumptions must be made in establishing the data used to calculate the BREW metrics associated with traditional manufacturing of the chosen component parts.

Within the next sections of this report we will look at each of the component parts listed in Table 1 and identify (where possible) each of the manufacturing steps (deliverable M3.1) and logistics steps (deliverable M3.2), which contribute towards the BREW metrics for each part.

KEY used in report

Manufacturing Logistics step step (M3.1) (M3.2)

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Supply Chain Analysis of Alcon Components

Alcon is one of the world’s foremost manufacturers of performance and motorsport brake and clutch systems; supplying and winning in F1, WRC, NASCAR, Indy Car, Touring Cars and GT racing, as well as engineering extreme solutions for several leading performance road car manufacturers. The brake calliper selected for the Atkins project is a current range product manufactured for the US NASCAR series.

Part: Car 22 Brake Calliper

Materials Aluminium AL2618-T6 Size (bounding box) Within SLM250-400 Primary manufacturing process Milling (245 + 28 mins) Weight of raw material billet 12.5 kg Weight of final part 1.58 kg Resource efficiency 13% Primary reason for selection: Improve material resource efficiency, increase stiffness of design, reduce overall part weight, increase volume sales through innovation.

Comments and assumptions

The energy requirements for raw material manufacture are taken from a combination of virgin and recycled raw material energy, at industry average proportions specific to the selected material.

The energy requirements of pre-op machining and vertical boring process are assumed to equal the requirements of conventional machining and emissions have been aligned as such.

No data is available for any of the following processes;

Deburring, Inspection, NDT, Vibratory micro polishing, Subassembly with lead plugs, Electro less Nickel Plating, Hardening (180C for 4h), Assembly, Laser Marking, Painting of logo (manual operation), Inspected, packed & shipped, Customer.

Mass increases have not been accounted for, as the nature and material of the mass increase is unknown.

Due to a number of data gaps in the supply chain response, there have been some assumptions taken regarding the routes and vehicles used in the supply of this component (assumed locations are marked *).

Alternative supply chains have been mapped, deviating in the method used to transport the component from Tamworth, UK to McHenry, Illinois, USA. In the first scenario, the primary method of transport is via a large containerised sea-vessel. In the second scenario, the primary method of transport is via a long-haul air-craft.

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Supply chain map – Alcon - Car 22 Brake Calliper

Distance Weight Supply chain stage Location Company travelled Mode of transport (kg) (km) Raw Material Manufacture Seoul, S. Korea Alcoa 12.5 Kg ↓ 84.4 Rigid >3.5 <7.5t Material supply chain Daesan, S. Korea* 12.5 Kg ↓ 20,366 Large container vessel Material supply chain Bremen, Germany* 12.5 Kg ↓ 131 Rigid >3.5 <7.5t Material supply chain Hannover, Germany Alcoa 12.5 Kg ↓ 1,081 Rigid 7.5 - 17t Metalfast or Material supply chain Birmingham, UK 12.5 Kg Metalweb ↓ 22 Rigid >3.5 <7.5t Pre-op machining Tamworth, UK Alcon 12 Kg ↓ Machining operation 1 (Hermle 5 axis) Tamworth, UK Alcon 6 Kg ↓ Machining operation 2 (Hermle 5 axis) Tamworth, UK Alcon 2 Kg ↓ Vertical boring (VS 50) Tamworth, UK Alcon 1.58 Kg ↓ Deburring, Inspection, NDT Tamworth, UK Alcon 1.58 Kg ↓ 29 Rigid >3.5 <7.5t Vibratory micro polishing Derby, UK Rhodes 1.58 Kg ↓ 27 Rigid >3.5 <7.5t Subassembly with lead plugs Tamworth, UK Alcon 1.6 Kg ↓ 26 Rigid >3.5 <7.5t Electro less Nickel Plating Coventry, UK Nitec UK 1.6 Kg ↓ Hardening (180C for 4h) Coventry, UK Nitec UK 1.6 Kg ↓ 26 Rigid >3.5 <7.5t Assembly Tamworth, UK Alcon 2 kg ↓ Laser Marking Tamworth, UK Alcon 2 Kg ↓

Painting of logo (manual operation) Tamworth, UK Alcon 2 Kg

↓ Inspected, packed & shipped Tamworth, UK Alcon 2 Kg ↓

278 Rigid >3.5 <7.5t

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Material supply chain (Scenario 1) Swansea, UK* 2 Kg ↓ 6,634 Large container vessel Material supply chain (Scenario 1) Jacksonville, NC, USA* 2 Kg ↓ 1,565 Rigid 7.5 - 17t Material supply chain (Scenario 1) McHenry Il, USA 2 Kg ↓ Brake Parts Component distribution (Scenario 1) McHenry Il, USA 2.5 Kg Inc. ↓ 1306 Rigid 7.5 - 17t Joe Gibbs Customer (Scenario 1) Huntsville NC (USA) 2.5 Kg Racing TOTAL → 31,232

6,248 Long haul Material supply chain (Scenario 2) McHenry Il, USA 2 Kg ↓ Brake Parts Component distribution (Scenario 2) McHenry Il, USA 2.5 Kg Inc. ↓ 1306 Rigid 7.5 - 17t Joe Gibbs Customer (Scenario 2) Huntsville NC (USA) 2.5 Kg Racing TOTAL → 29,024

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Supply Chain Analysis of Bentley Components

Bentley is one of the world’s most prestigious automotive brands, manufacturing a range of luxury cars including the Continental, Continental GT, Azure, Arnage & Mulsanne. Located in Crewe, England since 1946 and owned since 1998 by Volkswagen AG, Bentley Motors is dedicated to making responsive and powerful luxury cars. The component selected for the Atkins project is a pressure die cast transmission mount bracket Part: Transmission Mount Bracket

Materials Aluminium 6082 T6 / Zinc-Aluminium alloy Size (bounding box) 255 x 215 x 70 Primary manufacturing process Milling / Pressure casting Weight of raw material billet Approx: 12.575 kg / 1.148 kg + 5% Weight of final part 1.148 kg Resource efficiency 9% / 95% Primary reason for selection: Reduce overall part weight and optimise design possibilities.

Comments and assumptions

Two scenarios have been investigated for Bentley’s Transmission Mount Bracket, which fundamentally differ on the selection of material and the primary manufacturing process.

An aluminium part is produced with a primary process of milling. Industry standard proportions of virgin and recycled material are deemed to best reflect the makeup of the aluminium used.

A pressure die casting process is used to produce the zinc alternative. According to Bentley, the zinc used is constrained to virgin content only i.e. no recycled zinc is used in the process. Although actual data are not available, the assumption that there is a 5% material loss in the process of casting (i.e. the input of raw material has been increased to 105% of the output) is said to be reasonable.

Industry standard data for a standard petrol passenger car has been used to represent the usage phase of the components lifecycle.

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Supply chain map – Bentley – Transmission Mount Bracket – Scenario 1

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw material manufacture Jamshedpur, India* Unknown 12.575 ↓ 1,632 Rigid 7.5 - 17t Material supply chain Chennai, India* Unknown 12.575 ↓ 13,916 Large container vessel Material supply chain Bremen, Germany* Unknown 12.575 ↓ 629 Rigid 7.5 - 17t Milling Stuttgart, Germany Unknown 1.148 ↓ 629 Rigid >3.5 <7.5t Material supply chain Bremen, Germany* Unknown 1.148 ↓ 685 Small container vessel Material supply chain Felixstowe, UK* Unknown 1.148 ↓ 349 Rigid >3.5 <7.5t - Unknown Ex. Works 1.148 - Unknown Assembly Crewe, UK Bentley 1.148 ↓ - Unknown Customer Unknown Unknown TOTAL → 17,840

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Supply chain map – Bentley – Transmission Mount Bracket – Scenario 2

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw material manufacture Jamshedpur, India* Unknown 1.205 1,632 Rigid 7.5 - 17t Material supply chain Chennai, India* Unknown 1.205 ↓ 13,916 Large container vessel

Material supply chain Bremen, Germany* Unknown 1.205 ↓ 629 Rigid 7.5 - 17t

Casting Stuttgart, Germany Unknown 1.205 ↓ Light machining Stuttgart, Germany Unknown 1.148 ↓ 629 Rigid >3.5 <7.5t Material supply chain Bremen, Germany* Unknown 1.148 ↓ 685 Small container vessel Material supply chain Felixstowe, UK* Unknown 1.148 ↓ 349 Rigid >3.5 <7.5t - Unknown Ex. Works ↓ - - Assembly Crewe, UK Bentley 1.148 ↓ - - Customer Unknown Unknown TOTAL → 17,840

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Supply Chain Analysis of Boeing Components

Boeing is the world's leading aerospace company and the largest manufacturer of commercial jetliners and military aircraft combined. Additionally, Boeing designs and manufactures rotorcraft, electronic and defence systems, missiles, satellites, launch vehicles and advanced information and communication systems. A number of structural component parts have been selected for the Atkins project.

Many of the Boeing components follow similar supply chain paths, with certain locations often being designated to processes that will be performed on an array of their components. Likewise, due to the nature and requirements of the parts, Boeing habitually uses virgin rather recycled material throughout their range.

All of the components in the Boeing range are destined to be employed on Boeing air-craft. Some usage information has been supplied by Boeing, but is not disclosed in this report due to confidentiality agreements.

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Part: Eggcrate Clip – 787

Materials Titanium Ti-6Al-4V Size (bounding box) 127 x 123 x 33 mm Primary manufacturing process Milling Weight of raw material billet 2.33 kg Weight of final part 0.29 kg Resource efficiency 12 % Primary reason for selection: Improve material resource efficiency, reduce overall part weight

Comments and assumptions

The energy requirements of machining are assumed to equal the requirements of conventional machining and emissions have been aligned as such.

No data is available for any of the following processes;

Annealing per AMS 4911, deburring, inspection, packaging and shipping, customer and assembly.

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Supply chain map – Boeing – Eggcrate Clip

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw Material Manufacture Osaka, Japan ↓ 511 Rail

Material supply chain (Scenario 1) Tokyo, Japan* Varies 2.33 ↓ 10,900 Long haul, aircraft Material supply chain (Scenario 1) Morgentown, PA, USA* 2.33 ↓

Material supply chain (Scenario 2) Tokyo, Japan* Varies 2.33 ↓ 8,453 Large container vessel Material supply chain (Scenario 2) San Francisco, CA, USA* 2.33 ↓ 4,555 Rigid >17t Material supply chain (Scenario 2) Morgentown, PA, USA* 2.33 ↓ 743 Rigid >3.5 <7.5t Annealed per AMS 4911 Ohio, USA Varies 2.33 ↓ 639 Rigid >3.5 <7.5t Material supply chain Jacksonville, NC, USA* 2.33 ↓ 9,247 Large container vessel Machining Taranto*, Italy Varies 0.29 ↓ Deburring Taranto*, Italy Varies 0.29 ↓ Inspection, packaging and shipping Taranto*, Italy Varies 0.29 ↓ 9,247 Large container vessel Material supply chain Jacksonville, NC, USA* 0.29 ↓ 4,797 Rigid >17t Customer Everett, WA, USA Boeing 0.29 ↓ Assembly Everett, WA, USA Boeing 0.29

TOTAL → 36,074 Scenario 1

TOTAL → 42,928 Scenario 2

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Part: Termination Fitting – 787

Materials Titanium Ti-6Al-4V Size (bounding box) 66 x 140 x 25 mm Primary manufacturing process Milling Weight of raw material billet 1.052 kg Weight of final part 0.145 kg Resource efficiency 14% Primary reason for selection: Improve material resource efficiency, reduce overall part weight

Comments and assumptions

The energy requirements of machining are assumed to equal the requirements of conventional machining and emissions have been aligned as such.

No data is available for any of the following processes;

Annealing per AMS 4911, deburring, inspection, packaging and shipping, customer and assembly.

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Supply chain map – Boeing – Termination Fitting

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw Material Manufacture Osaka, Japan ↓ 511 Rail

Material supply chain (Scenario 1) Tokyo, Japan* Varies 1.052 ↓ 10,900 Long haul, aircraft Material supply chain (Scenario 1) Morgentown, PA, USA* 1.052 ↓

Material supply chain (Scenario 2) Tokyo, Japan* Varies 1.052 ↓ 8,453 Large container vessel Material supply chain (Scenario 2) San Francisco, CA, USA* 1.052 ↓ 4,555 Rigid >17t Material supply chain (Scenario 2) Morgentown, PA, USA* 1.052 ↓ 743 Rigid >3.5 <7.5t Annealed per AMS 4911 Ohio, USA Varies 1.052 ↓ 639 Rigid >3.5 <7.5t Material supply chain Jacksonville, NC, USA* 1.052 ↓ 9,247 Large container vessel Machining Taranto*, Italy Varies 0.145 ↓ Deburring Taranto*, Italy Varies 0.145 ↓ Inspection, packaging and shipping Taranto*, Italy Varies 0.145 ↓ 9,247 Large container vessel Material supply chain Jacksonville, NC, USA* 0.145 ↓ 4,797 Rigid >17t Customer Everett, WA, USA Boeing 0.145 ↓ Assembly Everett, WA, USA Boeing 0.145

TOTAL → 36,074 Scenario 1

TOTAL → 42,928 Scenario 2

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Part: Sill Fitting

Materials Titanium Ti-6Al-4V Size (bounding box) 137 x 109 x 46 mm Primary manufacturing process Milling Weight of raw material billet 3.003 kg Weight of final part 0.263 kg Resource efficiency 9% Primary reason for selection: Improve material resource efficiency, reduce overall part weight, possible reduction in component size

Comments and assumptions

The energy requirements of machining are assumed to equal the requirements of conventional machining and emissions have been aligned as such.

No data is available for any of the following processes;

Annealing per AMS 4911, deburring, inspection, packaging and shipping, customer and assembly.

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Supply chain map – Boeing – Sill Fitting

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw Material Manufacture Osaka, Japan ↓ 511 Rail

Material supply chain (Scenario 1) Tokyo, Japan* Varies 3.00 ↓ 10,900 Long haul, aircraft Material supply chain (Scenario 1) Morgentown, PA, USA* 3.00 ↓

Material supply chain (Scenario 2) Tokyo, Japan* Varies 3.00 ↓ 8,453 Large container vessel Material supply chain (Scenario 2) San Francisco, CA, USA* 3.00 ↓ 4,555 Rigid >17t Material supply chain (Scenario 2) Morgentown, PA, USA* 3.00 ↓ 743 Rigid >3.5 <7.5t Annealed per AMS 4911 Ohio, USA Varies 3.00 ↓ 639 Rigid >3.5 <7.5t Material supply chain Jacksonville, NC, USA* 3.00 ↓ 9,247 Large container vessel Machining Taranto*, Italy Varies 0.26 ↓ Deburring Taranto*, Italy Varies 0.26 ↓ Inspection, packaging and shipping Taranto*, Italy Varies 0.26 ↓ 9,247 Large container vessel Material supply chain Jacksonville, NC, USA* 0.26 ↓ 4,797 Rigid >17t Customer Everett, WA, USA Boeing 0.26 ↓ Assembly Everett, WA, USA Boeing 0.26

TOTAL → 36,074 Scenario 1

TOTAL → 42,928 Scenario 2

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Part: Floor Beam End Fitting – 787

Materials Titanium Ti-6Al-4V Size (bounding box) 173 x 183 x 54 mm Primary manufacturing process Milling Weight of raw material billet 7.15 kg Weight of final part 0.42 kg Resource efficiency 6 % Primary reason for selection: Improve material resource efficiency, reduce overall part weight, decrease machine set times as this part has multiple variations

Comments and assumptions

The energy requirements of machining are assumed to equal the requirements of conventional machining and emissions have been aligned as such.

No data is available for any of the following processes;

Annealing per AMS 4911, deburring, inspection, packaging and shipping, customer and assembly.

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Supply chain map – Boeing – Floor Beam End Fitting

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw Material Manufacture Osaka, Japan ↓ 511 Rail

Material supply chain (Scenario 1) Tokyo, Japan* Varies 7.15 ↓ 10,900 Long haul, aircraft Material supply chain (Scenario 1) Morgentown, PA, USA* 7.15 ↓

Material supply chain (Scenario 2) Tokyo, Japan* Varies 7.15 ↓ 8,453 Large container vessel Material supply chain (Scenario 2) San Francisco, CA, USA* 7.15 ↓ 4,555 Rigid >17t Material supply chain (Scenario 2) Morgentown, PA, USA* 7.15 ↓ 743 Rigid >3.5 <7.5t Annealed per AMS 4911 Ohio, USA Varies 7.15 ↓ 639 Rigid >3.5 <7.5t Material supply chain Jacksonville, NC, USA* 7.15 ↓ 9,247 Large container vessel Machining Taranto*, Italy Varies 0.42 ↓ Deburring Taranto*, Italy Varies 0.42 ↓ Inspection, packaging and shipping Taranto*, Italy Varies 0.42 ↓ 9,247 Large container vessel Material supply chain Jacksonville, NC, USA* 0.42 ↓ 4,797 Rigid >17t Customer Everett, WA, USA Boeing 0.42 ↓ Assembly Everett, WA, USA Boeing 0.42

TOTAL → 36,074 Scenario 1

TOTAL → 42,928 Scenario 2

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Part: Pan Casting – 737

Materials Titanium Ti-6Al-4V Size (bounding box) Primary manufacturing process Milling Weight of raw material billet 15.32 kg + 5% for casting Weight of final part 15.25 kg Resource efficiency 99% Primary reason for selection:

Comments and assumptions

The energy requirements of machining are assumed to equal the requirements of conventional machining and emissions have been aligned as such.

No data is available for any of the following processes;

Annealed casting, abrasive blasting, heating / part straightening, inspection, customer, assembly.

Although no data are available for casting pour weights, an assumption that 5% additional material is needed to for the process which is removed during the machining process.

Alternative supply chains have been mapped, deviating in the method used to transport the component from Osaka, Japan to Whitehall, Michigan, USA. In the first scenario, the primary method of transport is via a long-haul air-craft. In the second scenario, the primary method of transport is via a large containerised sea-vessel.

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Supply chain map – Boeing – Pan casting

Distance travelled Supply chain stage Location Company (km) Mode of transport Weight (kg)

Raw Material Manufacture Osaka, Japan ↓ 511 Rail

Material supply chain (Scenario 1) Tokyo, Japan* 16.09 ↓ 6,330 Long haul Material supply chain (Scenario 1) Michigan Airport, MI, USA* Varies 16.09 ↓

Material supply chain (Scenario 2) Tokyo, Japan* Varies 16.09 ↓ 17,018 Large container vessel Material supply chain (Scenario 2) Jacksonville, NC, USA* 16.09 ↓ 1,565 Rigid >17t Material supply chain (Scenario 2) Whitehall, MI, USA 16.09 ↓

Annealed casting Whitehall, MI, USA Varies 16.09 ↓ Abrasive blasting Whitehall, MI, USA Varies 16.09 ↓ 3,342 Rigid >17t Material supply chain Auburn, WA, USA Varies 16.09 ↓ Machining Auburn, WA, USA Varies 15.25 ↓

Heating / part straightening Auburn, WA, USA Varies 15.25 ↓ 256 Rigid >3.5 <7.5t

Inspection Camas, WA, USA Varies 15.25 ↓ 23 Rigid >3.5 <7.5t

Customer Renton, WA, USA Boeing 15.25 ↓

Assembly Renton, WA, USA Boeing 15.25

TOTAL → 10,462 Scenario 1

TOTAL → 22,715 Scenario 2

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Part: 12’’ Strut Inlet Duct – 777

Materials Titanium Ti-6Al-4V Size (bounding box) Primary manufacturing process Casting Weight of raw material billet 0.43 kg + 5% for casting trimmings Weight of final part 0.43 kg Resource efficiency 100% Primary reason for selection:

Comments and assumptions

The energy requirements of both the casting and the light machining processes in the supply chain have been aligned to the respective energy requirements used in this study. However, no data is available for any of the following processes;

Penetrant inspection, rivet installation, customer and assembly.

Although no data are available for casting pour weights, an assumption that 5% additional material is needed to for the process which is removed during the machining process.

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Supply chain map – Boeing – 12’’ Strut Inlet Duct

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Osaka, Japan ↓ 511 Rail

Material supply chain (Scenario 1) Tokyo, Japan* 0.45 ↓ 6,330 Long haul Material supply chain (Scenario 1) Michigan Airport, MI, USA* Varies 0.45 ↓

Material supply chain (Scenario 2) Tokyo, Japan* Varies 0.45 ↓ 17,018 Large container vessel Material supply chain (Scenario 2) Jacksonville, NC, USA* 0.45 ↓ 1,565 Rigid >17t Material supply chain (Scenario 2) Whitehall, MI, USA 0.45 ↓

Casting Whitehall, MI, USA Varies 0.43 ↓ Penetrant inspection Whitehall, MI, USA Varies 0.43 ↓ 2,878 Rigid >17t Rivet installation Renton, WA, USA Boeing 0.43 ↓ 25 Rigid >3.5 <7.5t Light machining Auburn, WA, USA Boeing 0.43 ↓ 25 Rigid >3.5 <7.5t Customer Renton, WA, USA Boeing 0.43 ↓ Assembly Renton, WA, USA Boeing 0.43

TOTAL → 9,768 Scenario 1

TOTAL → 22,021 Scenario 2

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Part: Elevator Link – 777

Materials Titanium Ti-6Al-4V Size (bounding box) Primary manufacturing process Forging/ milling Weight of raw material billet 54.89 Kg Weight of final part 46.48 Kg Resource efficiency 85% Primary reason for selection:

Comments and assumptions

The energy requirements of both the forging and the machining processes in the supply chain have been aligned to the respective energy requirements used in this study. All of the mass reduction that occurs in this supply chain is assumed to originate entirely from machining and not from forging.

No data is available for any of the following processes;

Heat treatment, shot peening, edge / break inspection, customer and assembly.

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Supply chain map – Boeing - Elevator Link

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Kazakhstan ↓ 1,931 Rail Material supply chain Salda, Russia VSMPO – AVISMA 54.89 Kg ↓ 1,083 Rail

Material supply chain (Scenario 1) Primorsk, Russia* 54.89 Kg ↓ 124 Rail Material supply chain (Scenario 1) St Petersburg, Russia* 54.89 Kg ↓ 7,350 Long haul, aircraft Material supply chain (Scenario 1) Ohio, USA 54.89 Kg ↓

Material supply chain (Scenario 2) Primorsk, Russia* 54.89 Kg ↓ 8,823 Large container vessel Material supply chain (Scenario 2) Jacksonville, NC, USA* 54.89 Kg ↓ 1,020 Rigid 7.5 - 17t Material supply chain (Scenario 2) Ohio, USA 54.89 Kg ↓

Forged block Ohio, USA Varies 54.89 Kg ↓ Heat treating Ohio, USA Varies 46.48 Kg ↓ 3,842 Rigid >17t Machining Auburn, WA, USA Boeing 46.48 Kg ↓ Shot peen Auburn, WA, USA Boeing 46.48 Kg ↓ 25 Rigid >3.5 <7.5t Edge break / inspection Renton, WA, USA Boeing 46.48 Kg ↓ Customer Renton, WA, USA Boeing 46.48 Kg ↓ Assembly Renton, WA, USA Boeing 46.48 Kg

TOTAL → 14,355 Scenario 1

TOTAL → 16,742 Scenario 2

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Supply Chain Analysis of Delphi Components

Delphi is a leading global supplier for the automotive, computing, communications, energy, and consumer accessories markets. Headquartered in Troy, Mich., Delphi has more than 100,000 employees in 32 countries. Delphi Diesel Systems designs and manufactures diesel Fuel Injection Equipment (FIE) for on and off highway use. Delphi are currently the second largest supplier of diesel FIE in the world with a global manufacturing footprint. From WP1 of the Atkins project, Delphi have selected a range of component parts including pump housing, pump components and electronic control units.

Part: Diesel Front Plate 3 (DFP3)

Materials Aluminium EN1706 AC-AlSi9Cu3 (FE) DF Size (bounding box) Within SLM250-400 Primary manufacturing process Gravity Cast Weight of initial shot 0.852 Kg + 5% Weight of final part 0.652 Kg Resource efficiency 76% Primary reason for selection: Weight reduction, leak point reduction through integration of conformal fluid pathways, assembly count reduction, and reduction in part size to minimise installation envelope.

Post assembly issues for part distribution (front plate)

The supply chain for this component is quite complex, as it comes from three possible sources. However, the real complexities of the pump occur following the assembly of the component parts. The main customer is PSA. However, PSA also licensed the engine manufacturing writes to Ford/Volvo.

Currently most DFP3 pumps are built in Barcelona; however from January 2010 all pumps except for Daimler will be built in Lasi, Romania.

Currently the distribution is from Barcelona to a distribution centre in the Delphi Blois plant in France. From there the pumps for PSA go to Rennes-la-Jannais and Sochaux France.

For Ford the pumps are sent to the Volvo engine plant in Skovde Sweden. The assembled engines are then dispatched to Ford car plants across Europe. The diagram below, shows the scattered distribution of automotive assembly across Europe (NOTE these pumps are used by Ford – Blue, PSA – Green & Daimler – Light Blue).

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In 2010 pumps from Lasi for Volvo will be shipped directly by road to Skovde. Pumps for PSA will also be shipped by road directly to the plants, but as yet it is not clear whether they are sent to an engine assembly plant first. The supply of DTVS front plates from India will cease sometime in 2010. Plates will probably be shipped directly by sea to Romania via Constanta and then by truck to Lasi. Currently as production starts up in Lasi parts are being shipped by road from Barcelona.

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Comments and assumptions

The energy requirements for raw material manufacture are taken from a combination of virgin and recycled raw material energy, at proportions disclosed by Delphi;

“For gravity casting (front plate and housing) the casting gates are recycled in the melt up to a percentage of 30%.”(Email correspondence, Paul Smith, 01/07/2010)

As the location of the raw material manufacture is at this point unknown, it has been assumed to take place 500 km away from the first processing step.

The energy requirements of die-casting and machining processes have been aligned to the respective energy requirements used in this study.

No data is available for any of the following processes;

Washing, air / air leak test, boroscope inspection, dot matrix marking, assembly and customer.

Two alternative supply chains have been mapped independently. These options fundamentally differ in the routes taken.

Each option also contains slighter variations, differing at the point of assembly. In both option one and option two, components may either be transported for assembly at Barcelona, Spain or Constanta, Romania. All options and scenarios conclude at Skovde, Sweden.

Industry standard data for a standard diesel passenger car has been used to represent the usage phase of the components lifecycle.

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Supply chain map – Delphi - Diesel Front Plate 3 – Gravity cast – Scenario 1

Distance travelled Supply chain stage (primary source) Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture India ↓ 500 Rail Gravity Die Casting Padi, India Sundaram-Clayton 0.852 ↓ 26 Rigid >3.5 <7.5t 5-axis CNC Machining Mannur, India Delphi TVS 0.652 ↓ Electrochemical deburring Mannur, India Delphi TVS 0.652 ↓ Washing Mannur, India Delphi TVS 0.652 ↓ Air/Air Leak Test Mannur, India Delphi TVS 0.652 ↓ Boroscope Inspection Mannur, India Delphi TVS 0.652 ↓ Dot Matrix Marking Mannur, India Delphi TVS 0.652 ↓ 39 Rigid >3.5 <7.5t Material supply chain Chennai, India* 0.652

↓ 10,408 Large container vessel Assembly (Option 1) Barcelona, Spain Delphi ES 0.652 ↓ 2,551 Rigid >17t Customer (Option 1) Skovde , Sweden PSA/Ford/Volvo 0.652 TOTAL → 13,525

↓ 9,291 Large container vessel Material supply chain (Option 2) Constanta, Romania Varies 0.652 ↓ 451 Rigid >3.5 <7.5t Assembly (Option 2) Lasi, Romania Delphi Ro 0.652 ↓ 1,548 Rigid 7.5 - 17t Customer (Option 2) Skovde , Sweden PSA/Ford/Volvo 0.652 TOTAL → 11,856

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Supply chain map – Delphi - Diesel Front Plate 3 – Gravity cast– Scenario 2

Distance travelled Supply chain stage (secondary source) Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture France 0.909 ↓ 500* Rigid >3.5 <7.5t Gravity Die Casting Matour, France Groupe SAB 0.866 ↓ 48 Rigid >3.5 <7.5t 5-axis CNC Machining Montmerle, France SAB Montmerle 0.654 ↓ Electrochemical deburring Montmerle, France SAB Montmerle 0.654 ↓ Washing Montmerle, France SAB Montmerle 0.654 ↓ Air/Air Leak Test Montmerle, France SAB Montmerle 0.654 ↓ Boroscope Inspection Montmerle, France SAB Montmerle 0.654 ↓ Dot Matrix Marking Montmerle, France SAB Montmerle 0.654

↓ 679 Rigid >3.5 <7.5t Assembly (Option 1) Barcelona, Spain Delphi ES 0.654 ↓ 2,551 Rigid >17t Customer (Option 1) Skovde (Sweden) PSA/Ford/Volvo 0.654 TOTAL → 3,778

↓ 2,134 Rigid >3.5 <7.5t Assembly (Option 2) Lasi (Romania) Delphi Ro 0.654 ↓ 1,546 Rigid 7.5 - 17t Customer (Option 2) Skovde (Sweden) PSA/Ford/Volvo 0.654 TOTAL → 4,230

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Part: Diesel Front Plate 3 (DFP3) – Squeeze Cast

Materials Aluminium EN1706 AC-AlSi9Cu3 (FE) DF Size (bounding box) Within SLM250-400 Primary manufacturing process Squeeze Cast Weight of initial shot 1.235 Kg Weight of final part 0.603 Kg Resource efficiency 48.8% Primary reason for selection: Weight reduction, leak point reduction through integration of conformal fluid pathways, assembly count reduction, and reduction in part size to minimise installation envelope.

Comments and assumptions

Since this component was first proposed, the material has changed. The new material is A413.2: LM6 - M, cast (Al- 12Si);

“The material for the Pressure Die Casting has changed to EN-AC-47100 (AlSi12 Cu1 (Fe)). This is virgin material straight from smelted ore, so no recycled material.” (Email correspondence, Paul Smith, 01/07/2010)

As the location of the raw material manufacture is at this point unknown, it has been assumed to take place 500 km away from the first processing step.

The energy requirements of the machining process have been aligned to the requirements of conventional machining used in this study. In the absence of data relating to specifically to squeeze-casting, the energy requirements of pressure die-casting energy has been used in its place.

No data is available for any of the following processes;

Washing, air / air leak test, boroscope inspection, dot matrix marking, assembly and customer.

Industry standard data for a standard diesel passenger car has been used to represent the usage phase of the components lifecycle.

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Supply chain map – Delphi - Diesel Front Plate 3 (DFP3) – Squeeze Cast

Distance travelled Supply chain stage (third source) Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Unknown 1.235 ↓ 500 Rigid >3.5 <7.5t Squeeze Casting (Die with pressure) Tuzla, Turkey Adoksan Dokum 1.235 ↓ 5-axis CNC Machining Tuzla, Turkey NCA Ltd 0.603 ↓ Electrochemical deburring / Tuzla, Turkey NCA Ltd 0.603 ↓ Washing Tuzla, Turkey NCA Ltd 0.603 ↓ Air/Air Leak Test Tuzla, Turkey NCA Ltd 0.603 ↓ Boroscope Inspection Tuzla, Turkey NCA Ltd 0.603 ↓ Dot Matrix Marking Tuzla, Turkey NCA Ltd 0.603 ↓ 1,083 Rigid 7.5 - 17t Assembly Lasi, Romania Delphi Ro ↓ 1,548 Rigid 7.5 - 17t Customer Skovde, Sweden PSA/Ford/Volvo Unknown TOTAL → 3,131

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Part: Pump Housing

Materials Aluminium AL Si8 Size (bounding box) Within SLM250-400 Primary manufacturing process Gravity cast with sand core Weight of initial shot 2 Kg Weight of final part 0,826 Kg Resource efficiency 41,3% Primary reason for selection: Weight reduction, material reduction

Comments and assumptions

No data could be located for the exact material proposed by Delphi, the material S380.0: LM24-M, cast (Al-8Si- 3Cu-Fe) has been used as a substitute.

The energy requirements for raw material manufacture are taken from a combination of virgin and recycled raw material energy, at proportions disclosed by Delphi;

“For gravity casting (so front plate and housing) the casting gates are recycled in the melt up to a percentage of 30%.”(Email correspondence, Paul Smith, 01/07/2010)

As the location of the raw material manufacture is at this point unknown, it has been assumed to take place 500 km away from the first processing step.

The energy requirements of die-casting and machining processes have been aligned to the respective energy requirements used in this study.

No data is available for any of the following processes;

Sand removal, heat treatment, electrochemical deburring, washing, air / air leak test, boroscope inspection, dot matrix marking, assembly processes and customer operations.

Industry standard data for a standard diesel passenger car has been used to represent the usage phase of the components lifecycle.

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Supply chain map – Delphi – Pump Housing

Distance travelled Supply chain stage (secondary source) Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Unknown 2.0 ↓ 500 Rigid >3.5 <7.5t Gravity Die Casting Matour, France Groupe SAB 1.031 ↓ Sand removal removed through burnout Matour, France Groupe SAB ↓ Heat treatment Matour, France Groupe SAB ↓ 48 Rigid >3.5 <7.5t 5-axis CNC Machining Montmerle, France SAB Montmerle 0.826 ↓ Electrochemical deburring Montmerle, France SAB Montmerle 0.826 ↓ Washing Montmerle, France SAB Montmerle 0.826 ↓ Air/Air Leak Test Montmerle, France SAB Montmerle 0.826 ↓ Boroscope Inspection Montmerle, France SAB Montmerle 0.826 ↓ Dot Matrix Marking Montmerle, France SAB Montmerle 0.826 ↓ 2,134 Rigid 7.5 - 17t Pump Assembly Lasi, Romania Delphi Ro ↓ 1,880 Rigid 7.5 - 17t Engine Assembly Salzgitter, Germany VW ↓ 1,736 Rigid 7.5 - 17t Car Plant Pamplona, Spain VW TOTAL → 6,298

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Part: Venturi

Materials Nylon 66 (30% GF) Size (bounding box) Suitable for polymer sintering Within EOS, SLS – P390 Primary manufacturing process Injection Moulding Weight of initial shot 0.0027 Kg Weight of final part 0.0022 Kg Resource efficiency 81.5% Primary reason for selection: Part consolidation. Surface finish and performance appraisal. Potential integration into front plate or housing components.

This Venturi is used by Daimler, PSA, Ford & Volvo. In each case the supply chain remains the same up to the pump assembly operation in Barcelona or Lasi, after which each post assembly supply chain differs. The supply chain described below is for Daimler, with final vehicle assembly in Vitoria Spain. It should be noted that this component is used in engines that are the shipped for assembly into vehicles at plants in Sindelfingen; Bremen; Karmann; Dusseldorf and Ludwigsfelde in Germany; Graz in Austria and Vitoria in Spain. This list does not include Chrysler plants in Europe that use the same engines.

Comments and assumptions

Despite the possible variations in the supply chain, only one scenario has been mapped, due to a lack of information on the other possibilities.

The raw material used in the production of this component is assumed to be entirely virgin material.

The energy requirements of injection moulding are assumed to equal the requirements of polymer moulding and emissions have been aligned as such. No data is available for any of the assembly processes.

Industry standard data for a standard diesel passenger car has been used to represent the usage phase of the components lifecycle.

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Supply chain map – Delphi - Venturi

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Richmond, VA, USA Alloy Polymers 0.0027

↓ 380 Rigid >3.5 <7.5t Material supply chain Jacksonville, NC, USA* Varies 0.0027 ↓ 7,560 Large container vessel Material supply chain Bremen, Germany* Varies 0.0027 ↓ 706 Rigid >3.5 <7.5t Material supply chain Freiburg, Germany Rhodia 0.0027 ↓ 570 Rigid >3.5 <7.5t Injection Moulding Lommel, Belgium Helvoet 0.0027 ↓ 1,470 Rigid 7.5 - 17t Pre-assembly Barcelona, Spain Delphi ES 0.0027 ↓ 1,265 Rigid 7.5 - 17t Warehousing Stuttgart, Germany Delphi 0.0027 ↓ 331 Rigid >3.5 <7.5t Pre-assembly Unterkurken, Germany Delphi 0.0027 ↓ 484 Rigid >3.5 <7.5t Engine assembly Kolleda, Germany Daimler 0.0027 ↓ 1,763 Rigid 7.5 - 17t Car assembly Vitoria, Spain Daimler 0.0027 TOTAL → 14,446

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Part: ECU

Materials Aluminium + Various Size (bounding box) Within SLM envelope Primary manufacturing process Cast Aluminium Weight of initial shot ? Kg Weight of final part ? Kg Resource efficiency ?% Primary reason for selection: To improve thermal conductivity of the heat exchanger component, reduce materials and weights and to decrease packaging envelope. Integrate conformal cooling tracts and connectors

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Unknown Unknown ? Kg ↓ Unknown Material supply chain Unknown Unknown ? Kg ↓ Unknown Casting Unknown Unknown ? Kg ↓ Unknown Assembly Liverpool (UK) Delphi (AC Delco) ? Kg ↓ Unknown Customer Unknown Unknown ? Kg TOTAL → Unknown

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Part: Fuel Connector

Materials Aluminium Size (bounding box) Within SLM envelope Primary manufacturing process Machined ; Rolled and Brazed Weight of initial shot ? Kg Weight of final part 0.0413 Kg Resource efficiency ?% Primary reason for selection: Part consolidation. Potential integration directly into front plate or housing components.

Comments and assumptions

The fuel connector is an assembly of four parts, namely the body, plate, pipe and O-ring. The O-ring is excluded from analysis, as it is a non-metallic extension to the primary assembly and will be manufactured regardless of the manufacturing processes discusses in this project.

Various manufacturing processes are assumed to be performed on the three individual pieces that constitute the fuel connector. The mass removed from the body is attributed entirely to conventional machining. The mass removed from the plate is split between stamping (forging, rolling) and conventional machining. Firstly, it is expected to be stamped in to the shape before having the holes machined. The pipe is assumed to have no mass removal process and is only rolled into shape. The assembly is to braze all three components together.

1. the body is machined from bar;

2. the plate is stamped from plate and machined; and

3. the pipe is rolled from tube.

No supply chain detail is known regarding the fuel connector preceding the machining process stage, conducted by S.A.B. Industries in Gasny Paris. For the purposes of this project, the primary material manufacture, for all three of the individual pieces, will be assumed to be sourced by Tata Steel. Tata Steel is one of the world’s largest primary producers of steel for manufacture and is based in Jamshedpur, Jharkhand, India. The pieces are subsequently assumed to travel directly from Jamshedpur, Jharkhand, India to Gasny Paris, by a combination of road freight and sea-craft.

This part is for Daimler the same as the Venturi, so all stages after the shipment from the assembly plant in Barcelona shown for the Venturi apply to the fuel connector also.

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The exact material used for this part is unknown. The material is assumed to match that of the pump-housing for each of the body, plate and pipe (S380.0: LM24-M, cast (Al/8Si/3Cu/Fe)).

The mass of the raw material needed to produce each piece has been calculated by using the dimensions of the final piece and calculating the minimum amount of material needed to manufacture their shape and form using the processes described by Delphi.

The energy requirements of the machining process have been aligned to the requirements of conventional machining used in this study. In the absence of data relating to specifically to rolling, the energy requirements of forging, rolling have been used in its place.

No data is available for any of the assembly processes or the warehousing operations.

Industry standard data for a standard diesel passenger car has been used to represent the usage phase of the components lifecycle.

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Supply chain map – Delphi – Fuel Connector

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Jamshedpur, India* Unknown 0.10 ↓ 1,632 Rigid >17t Material supply chain Chennai, India* Unknown 0.10 ↓ 10,227 Large container vessel Material supply chain Fos, France* Unknown 0.10 ↓ 832 Rigid >3.5 <7.5t Machining Gasny, Paris, France S.A.B. Industries 0.06 ↓ Rolling France SAB 0.04 ↓ 1,079 Rigid 7.5 - 17t Pre-assembly Barcelona, Spain Delphi ES 0.04 ↓ 1,265 Rigid 7.5 - 17t Warehousing Stuttgart, Germany Delphi 0.04 ↓ 331 Rigid >3.5 <7.5t Pre-assembly Untertürken, Germany Delphi 0.04 ↓ 484 Rigid >3.5 <7.5t Engine assembly Kolleda, Germany Daimler 0.04 ↓ 1,079 Rigid 7.5 - 17t Car assembly Vitoria, Spain Daimler 0.04 ↓ 1,439 Rigid 7.5 - 17t Customer Stuttgart, Germany Daimler 0.04 TOTAL → 19,120

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Supply Chain Analysis of Virgin Components

Virgin Atlantic is a transcontinental airline operating out of the UK. Virgin Atlantic is committed to reducing its environmental impacts by becoming a more efficient business through both practical and technical solutions. Virgin Atlantic is continuing to evaluate more efficient ways of operating its existing fleet of aircraft, until manufacturers can develop technological solutions to reducing carbon emissions such as innovative aircraft design or viable alternative fuels. From WP1 of the Atkins project, Virgin have selected a number of metallic component parts for design optimisation and additive manufacture, which are all orientated around the passenger seats in upper, premier and economy classes.

Part: Upper class monitor arm

Materials Aluminium AL2014 Size (bounding box) ? Primary manufacturing process ? Weight of initial shot ? Kg Weight of final part ? Kg Resource efficiency ?% Primary reason for selection: Part consolidation, material utilization, weight saving

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Unknown Unknown ? Kg ↓ Unknown Material supply chain Unknown Unknown ? Kg ↓ Unknown Manufacturing (n) Unknown Unknown ? Kg Unknown Manufacturing (n+1) Unknown Unknown ↓ Unknown Unknown Unknown Assembly ? Kg ↓ Unknown Customer Unknown Unknown ? Kg TOTAL → Unknown

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Part: Economy tray table arm

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

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Part: Front row monitor arm

Materials Aluminium AL2014 Size (bounding box) ? Primary manufacturing process Machining Weight of initial shot ? Kg Weight of final part ? Kg Resource efficiency ?% Primary reason for selection: Material utilization, weight saving

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

Raw Material Manufacture Unknown Unknown ? Kg ↓ Unknown Material supply chain Unknown Unknown ? Kg ↓ Unknown Machining Unknown Unknown ? Kg Unknown Manufacturing (n+1) Unknown Unknown ↓ Unknown Unknown Unknown Assembly ? Kg ↓ Unknown Customer Unknown Unknown ? Kg TOTAL → Unknown

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Part: Foot rest plate

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

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Part: Premier economy tray table arm

Distance travelled Supply chain stage Location Company (Km) Mode of transport Weight (kg)

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WP2 – Assessment of traditional manufacturing

Methodology

Before reporting on the figures calculated for each component considered in this study, this section will first explain the methodology used for the calculations.

Life cycle stages assessed

Figure 1.1 outlines the life cycle stages and process steps that were included in calculating the parts’ carbon footprints. All of the components pass through a series of common steps across their life, but these can occur in different locations and often in a different sequence.

Inputs considered

Outputs considered

Inputs / outputs not considered

Key for Figure 1 - Life cycle stages included in footprint calculations for components

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Energy and fuels CO2 emission to air

Raw material Water Waste to landfill manufacture

Chemicals Waste to recycling

Energy and fuels CO2 emission to air Distribution Transport

Waste product Packaging material

Energy and fuels CO2 emission to air

Processing Water Waste to landfill

Chemicals Waste to recycling

CO2 emission to air

Customer and Energy and fuels Waste to landfill assembly

Waste to recycling

Energy and fuels

Usage Transport CO2 emission to air

Maintenance and repair

Remanufacture

End-of-life Energy and fuels CO2 emission to air

Transport

Figure 1 - Life cycle stages included in footprint calculations for components

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Raw material & Process Energy

The embedded energy values attributed to the manufacturing processes for the various material compositions have been sourced primarily from the GRANTA database using the CES Selector 2009 software. Data has been extracted for the following categories. Also displayed is the means in which the energy (MJ / kg) has been credited to the mass of the component;

Category Attribution All materials

Virgin raw material Mass produced Recycled production Mass produced Average recycling rate Mass produced Metals Casting Total mass

Forging, rolling Total mass Vaporisation Total mass Metal powder forming Total mass Conventional machining Mass removed Non-conventional machining Mass removed

Polymers Polymer moulding Total mass Polymer extrusions Total mass Polymer machining Mass removed Technical ceramics

Ceramic powder forming Total mass

Table 2 - GRANTA data

Where no exact match has been found, the material that most closely matches has been used as a substitute. All substitutes compare well with the actual materials used in production and the figures are thought to provide a good representation of actual energy use.

The embodied energy (MJ / kg) is attributed to the components depending upon the type of process that is undertaken within the supply chain. The energy needed to perform mass adding (material production) or non- mass removing (casting, forging, rolling) processes is applied to the total mass of the component. For instance, in the case of the production of material, whether it is primary or recycled production, the energy required will be applied to the amount of material produced. With casting, forging and rolling the energy required will instead be applied to the mass at the start of the process, as this is the amount of mass on which the process is performed.

Mass reducing activities are treated in a different manner. The energy required for each process is only applied to the mass removed from the piece. For instance, the energy implications of machining a 1 kg billet into a 0.75 kg of piece, will apply the energy required to machine 0.25 kg of material. Likewise, the energy required to reduce a 10 kg billet to 9.75 kg will only be applied to the 0.25 kg of material removed.

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Some data extracted from ecoinvent have been used to supplement the GRANTA figures. The figures allow data to be more specific to the processes investigated, as they are able to report on different types of processes.

For instance, CNC machining energy data are reported with respect to roughing, dressing or average machining. Dressing energy figures have therefore been used as more representative of finishing processes for the relevant test cases.

Recycling

Unlike other products and consumables, when recovered the properties of metals are theoretically identical to those in the raw material. Therefore, the metals can be reused in another product life cycle, provided that its concentration makes a recovery economic (Steiner and Frischknecht, 2007). This reused or ‘secondary’ metal is assigned a different ecological burden to the metal that is extracted directly from the ore, or ‘primary metal’, due to the different implications of producing it.

Average recycling rates used globally have also been extracted from the GRANTA database. The figures have been combined with the embedded energy required for primary production from both virgin material and recycled material. These figures have been applied to material production where the actual recycled content is unknown in the supply chain.

There are numerous arguments surrounding the debate on how recycling is credited as performing better environmentally than primary production. In discussing the price elasticity of aluminium, Frees (2008) believes that it is of no use to measure the recycled content in a product. His main issue with this is that in order to satisfy the demand for aluminium a large part of the aluminium production must be made from primary aluminium that is recycled after use. Another reason is that, for many specifications of aluminium there this no comparison on whether is originates from virgin or recycled aluminium. Frees (2008) does however also mention that, the transport sector is a typical example where, when recycled the aluminium contained in products will replace primary aluminium and therefore should be given credit for the avoided production of the primary aluminium.

Hammond and Jones (2008) present the two main methodologies, namely the ‘recycled content approach’, which credits recycling, and the ‘substitution method’, which credits recyclability.

Recycled content calculations draw from the proportions of incoming materials that originates from recycled and primary material sources. This occurs at the start of the lifecycle and credits are apportioned upstream of the use or application. Conversely, the substitution method is an end-of-life methodology, where the ability of the materials to be recycled at the end-of-life stage is considered.

The distinction between the methodologies discussed is especially pertinent to the metal production, where recycled aluminium can produce savings of 85 – 90% in its embodied impacts when compared to primary aluminium (Hammond and Jones, 2008).

Frees (2008) suggests that, available aluminium scrap approximately covers just 30 – 40% of the demand for aluminium and its supply price elasticity is rather inelastic. Thus, he concludes that it is the production of primary aluminium that is avoided by recycling.

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The authors of this study consider that the recycled content approach better reflects the requirements of this study, as it is not uncommon for producers to require extraordinarily high virgin material content. It is also believed that this approach better reflects the current impacts on production. This method also is aligned with the guidelines of the Carbon Trust and British Standards. According to PAS 2050 (2008), the methodology used for calculating emission from recycling depends upon the material in question. The PAS 2050 (2008), an independent standard for assessing product lifecycle emissions, elucidates that a distinction between open and closed loop systems should be made.

Closed loop systems imply that when a material is recycled, the material does not change and the material is used again for the same purpose. In this circumstance, the proportion of input from virgin and recycled sources should be analysed and the emissions should then be calculated based upon these proportions. Unless the inputs are known to be different, industry average recycling rates should be used. This varies from recycled materials that are not part of a closed-loop system, which factors in the recycling rate of the entire material system. According to the PAS 2050 (2008), this affords some flexibility in sectors that have little control over the recycled content of the inputs but also acknowledges sectors where there are high recycling rates (e.g. the aluminium industry).

It should be noted, that the PAS 2050 (2008) also advocates that recycling considered at the disposal stage of the life-cycle is allocated an emission factor of zero.

CO2 Calculations

Once the material grade and process performed have been aligned to a respective energy value, a subsequent CO2 figure is calculated from the product of the respective energy / fuel mix and a series of emission factors.

Fuel mix

In order to apportion process energy to a fuel mix, a percentage split has been calculated from US industry totals detailed in the 2002 Manufacturing Energy Consumption Survey (MECS). This report estimates total energy consumption by source types, industry type and Census region, categorising the findings into energy consumed as a fuel, energy consumed as a non-fuel, energy consumed for all purposes, offsite-produced fuel consumption and so forth (U.S. EIA, 2007).

The U.S. EIA (table 5.2, 2007) explain that their estimates include the total consumption of energy for the production of heat, power, and electricity generation, regardless of where the energy was produced. They expand that specifically, the estimates include the quantities of energy that were originally produced offsite and purchased by or transferred to the establishment, plus those that were produced onsite from other energy or input materials not classified as energy, or were extracted from captive (onsite) mines or wells.

Figures referring only to direct process energy consumed as a fuel by end use have been used for the purposes of this study.

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This report divides energy into seven categories, namely;

1. net electricity;

a. obtained by summing purchases, transfers in, and generation from non-combustible renewable resources, minus quantities sold and transferred out. It does not include electricity inputs from onsite cogeneration or generation from combustible fuels because that energy has already been included as generating fuel (for example, coal).

2. residual fuel oil;

3. distillate fuel oil and diesel fuel;

a. includes Nos. 1, 2, and 4 fuel oils and Nos. 1, 2, and 4 diesel fuels.

4. natural gas;

a. includes natural gas obtained from utilities, local distribution companies, and any other supplier(s), such as independent gas producers, gas brokers, marketers, and any marketing subsidiaries of utilities.

5. liquid purified gas (LPG) and natural gas liquids (NGL);

a. Examples of Liquefied Petroleum Gases '(LPG)' are ethane, ethylene, propane, propylene, normal butane, butylene, ethane-propane mixtures, propane-butane mixtures, and isobutene produced at refineries or natural gas processing plants, including plants that fractionate raw Natural Gas Liquids '(NGL).'

6. coal (excluding coke and breeze); and

7. other;

a. includes net steam (the sum of purchases, generation from renewables, and net transfers), and other energy that respondents indicated was used to produce heat and power.

As the figures are sourced from a U.S. based research agency, it must be noted that they are representative of developed manufacturing and energy systems located in the United States. In the absence of figures available for other countries, this data is deemed appropriate for the purposes of this study.

Despite the lack of locality in the figures, the application of industry fuel mix data is a significant part of the methodology which, it is believed, allow us to more accurately apply CO2 conversion factors to the energy values extracted from GRANTA. Applying variable fuel mixes to the same processing energy values has also allowed us to differentiate between similar processes and their CO2 burden. For instance, applying the fuel mix which refers to

‘Aluminium Die-Casting Foundries’ can be used to distinguish aluminium die casting CO2 emissions from aluminium investment casting emissions, which is assigned a fuel mix referring to ‘Aluminium Foundries, except Die-Casting’.

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Material category Description All aluminium based materials, including commercially pure, cast and Aluminium wrought aluminium. All steels, including alloy steel, carbon steel, stainless steel and tool Steel steel. All plastic based materials, including thermoplastics (such as PA and Plastic PP) and thermosets (such as EP and PUR). Metals that do not fall into the category of either ‘aluminium’ or Other metal ‘steel’.

Table 3 – Material categories for processing fuel mixes

Unfortunately, due to a lack of data it is has not been possible to precisely align an industry mix to the entire range of different materials and processes, and therefore assumptions have been made as to where the process will most likely be performed. In order to do this, materials have been categorised into different classes depending on the primary material in the composition. For instance, commercially pure Aluminium, Al 7050, Al/9Si/3Cu/Mg grades all fall into the aluminium class of materials. Titanium Ti-6Al-4V would however fall into the ‘titanium class’ of materials, as although it contains aluminium, the primary material is titanium.

In a number of cases, the energy consumed is assumed to be entirely electrical. This has been assumed where the process is almost entirely reliant on machinery, for example the source of energy for CNC machining will most likely be solely derived from electrical sources. Another example is revealed by Choate and Green (2003) who state that, “electricity is required for smelting and accounts for over 98% of the energy used in the process”. The pair go on to suggest that, smelting requires 49% of the total energy consumed in U.S. manufacturing of aluminium (Choate and Green, 2003).

Another level of intricacy is applied to the calculation of the emissions resulting from the primary manufacture of the materials. In this case, the relevant energy mix is applied to the different constituents that make up the composition of the material. Again the materials have been aligned to categories, but in the presence of more detailed information on, and the relative importance of, the primary production of raw material more categories have been added.

Material category Description

Aluminium Aluminium content.

Steel Iron content.

All steels, including alloy steel, carbon steel, stainless steel and tool Iron steel. All plastic based content, including thermoplastics (such as PA and Plastic PP) and thermosets (such as EP and PUR).

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Glass Glass content.

Non-ferrous metals (except The content of metals that are naturally found as ore with an aluminium) abundant supply in the earth’s crust. Electrometallurgial ferro- Materials that add critical elements to compositions. Including alloys chromium, manganese, silicon, titanium and vanadium.

Table 4 - Material categories for raw material manufacturing fuel mixes

In the case of steel, the entire composition is aligned to the category of steel, as opposed to the constituent parts with the other material classes.

In some cases, some of the elements that make up the composition of a material do not fall into any of the aforementioned categories. For example, occasionally some alloys contain forms of gas (oxygen, nitrogen) trapped as a result of the production method. What is more, some of the elements in a composition may be defined as a range within GRANTA and in this case averages of the upper and lower limits have been taken to estimate the mean value. Consequently, many of the aggregated compositions do not result in a sum of 100%, but fall slightly above or below the expected total. Therefore, all the materials that fall into the measures categories (see Table 4) have been scaled to bring the composition to 100%. The discrepancies are always relatively minor and are not expected to affect the result in any significant manner.

Conversion factors

The energy mix allows us to allocate the energy figure to the sources of primary energy, which can subsequently all be assigned different ‘greenhouse gas conversion factors’, depending upon their impact to the environment. Defra’s guidelines explain;

“conversion factors allow organisations and individuals to calculate greenhouse gas emissions from a range of activities, including energy use, water consumption, waste disposal, recycling and transport activities.” (Defra Guidelines, 2010, pp.2)

Most emission factors are relatively static and in general they are unlikely to vary significantly between different years. However, as new research becomes available, particularly with specific transport vehicles and possibly also in natural gas and bio-energy due to changing sources, certain emission factors do change on an annual basis and it is important to use figures from the most recent / relevant year of reporting (Defra Guidelines, 2010). It is not recommended however, that recent factors should be worked back to re-calculate previous emissions using the newer factors and updated factors should only be applied for reporting on years up to 2 years prior to the most recent dataset.

Electricity stands as the most important exception to this rule, and in its case emissions should be recalculated for previous years using the latest time-series dataset. This is due to improvements in calculation methodologies or the UK GHG inventory datasets they are based upon (Defra Guidelines, 2010). Electricity also differs in that the CO2 emanating from the use of a single unit will vary drastically depending upon the source of the energy, for example whether energy is produced from fossil fuel plants, nuclear power stations, renewable sources and so on. Except for some larger processing facilities which hold the capacity to produce energy in-house, the vast majority of

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manufacturers will source their energy from their respective national or regional grid, which in turn will supply electricity from a diversified mix of sources. Therefore, the emission factor applied to electricity usage is dependent upon the location of the process and in some cases the specified energy provider.

Such emission factors are provided by a variety of sources. The Greenhouse Gas Protocol Initiative (2009) disclose emission factors for individual countries, and regions within countries, covering the at least the emission factors for carbon dioxide (the principal GHG emitted by power facilities) emissions (kg CO2 / kWh). Results are displayed by year (2000 – 2006) and by the fuel base (coal / peat, oil, gas, total). Total mix for the base year 2006, has been selected for the purposes of this study.

U.S. State emission factors have been extracted from the U.S. Environmental Protection Agency (2007) datasheets, which refer to 'State annual CO2 output emission rate (lb / mWh)’ for the base year 2005. This has been converted to a unit comparable with the other data sources.

By combining emission factors from the aforementioned sources, it was possible to calculate an emission factor for the electricity produced in all of the world’s major countries. In the case of the USA, it was also possible to calculate emission factors on a state basis. Due to the size of the area and the variation in state energy provision this is considered to improve the accuracy of the calculated CO2 emissions.

Where the data sources have ‘overlapped’ and multiple values are available for a single location, the mean value of the figures available has been used.

Some smaller nations were not listed in any of the data sources and were instead allocated the emission factor of a ‘best fit’. This was either the emission factor of another country thought to closely match that of the allocated country, a combination of multiple ‘supplier’ countries, or the emission factor of a sub-region or continent. This is considered sufficiently accurate for the purposes of the Atkins research project.

Where possible, the most specific emission factors should be used and using geographically specific emission factors for the use of energy again allows this report to paint a more accurate representation of the environmental burdens of manufacturing across different locations.

It would also be possible to differentiate emission factors based upon the source of energy within nations, for instance discerning between electricity generated through national coal / peat, oil or gas systems.

Yet another possibility would analyse the specific energy providers of electricity of the actors in the supply chain. This is increasingly utilised due to a mounting obligation on energy suppliers to disclose the sources of their energy. Ever since March 2005, it has become a mandatory requirement of ‘The Electricity (Fuel Mix Disclosure)’ that, all UK electricity suppliers publish information on the mix of fuels used to generate the electricity they supply and the environmental impact of its generation (Fuel mix, 2010). The percentage of coal, natural gas, nuclear and renewable energy used to produce the electricity provided must be provided by each supplier as a bare minimum, along with other environmental information related to the CO2 emissions and levels of radioactive waste generated.

However, sourcing accurate information regarding the partners supply chains on this matter may be extremely difficult and is not expected to substantially benefit the findings.

Koch and Harnisch (2002) discuss the implications of using different boundaries, in the table below;

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System Boundary Arguments for Arguments against

Appropriate for a closed system of smelter Only a minority of European smelters with Single power plant self-generated electricity power plant would and power plant with self-generated supply not necessarily shut down, if smelter closes; electricity existing. always back-up supply. Network connection of electricity generating Operational conditions of the utility are companies; increasing proportion of Contract mix determined by the economic relationship. electricity supply outside the electricity company Before liberalisation of the electricity National boundaries only of limited markets, the national markets were strongly National mix relevance for the European electricity determining the conditions and effects of market. electricity generation. Overall system boundaries set by the Very broad and generalised approach: does electricity network; organisations; European grid mix not take local and regional conditions into interconnection of national electricity account; limited transfer capacity. networks.

Table 5 - Advantages and disadvantages of the four different choices of system boundaries (Koch and Harnisch, 2002)

National and regional mixes have been chosen as the boundaries for electricity emission factors in this project.

Despite relative agreement in the methodology of calculating emission factors, some differences do exist between different agencies and should be understood. Defra’s guidelines (2010) recommend the use of different factors depending upon the requirement of the report;

For reporting emissions under the EU Emissions Trading Scheme, refer to http://www.environment- agency.gov.uk/business/topics/pollution/32232.aspx

For reporting emissions under the Climate Change Agreements, refer to http://www.decc.gov.uk/en/content/cms/what_we_do/change_energy/tackling_clima/ccas/ccas.aspx

For reporting emissions under the new CRC Energy Efficiency Scheme (CRC), refer to http://www.environment-agency.gov.uk/business/topics/pollution/116626.aspx

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Distribution and transport

The environmental burden emanating from the transportation of components have been calculated based upon the supply chain information provided by the partners and distances researched from various web-based tools, including Google Maps (http://maps.google.co.uk/) and Port World (http://www.portworld.com/). Unless otherwise stated, all transport journeys are assumed to go direct from origin to destination. No stop-offs or route deviations have been accounted for. Distances are approximate but are thought to provide a reasonable reflection of reality.

The method used applies vehicle specific emission factors to the distance travelled and the mass transported in the journey.

As one may expect, the environmental burden of travelling a set distance can vary substantially depending upon which mode of transport is taken. For instance, flying a 1 kg component 1,000 km in a domestic aircraft will be radically more damaging than shipping the same component over the same distance in a large container vessel. What is more, similar vehicles can also have markedly different emission factors and even the same vehicle may produce different burdens depending on non-trivial factors such as the use of air-conditioning, tire pressure or driving style.

However, many of these factors are unknowable in supply chains that can stretch over many countries and continents. The emission factors used are extracted from Defra’s (2011) methodology paper for transport emission factors.

Only the actual mass of the component transported is accounted for at this stage. This is simply the mass of the component at the end of most recent mass reducing activity. It does not account for any primary, secondary or transit packaging or any other additional mass that may be transported along with the component. For this reason, the calculated emissions of transportation are expected to underestimate the actual burden.

Where possible, this report has sought to use only the locations and vehicle types provided by the partners, however due to numerous difficulties in tracing components back to their beginnings, some assumptions have had to be made. For instance, the origin and destination of shipping journeys must be located at a recognised port and cannot be located inland. Where only the processing locations are provided, additional steps have been added, which not only account for the shipping distance but also for the transportation to and from a local port. An appropriate port has in all cases been assigned to shipping journeys.

Likewise, it can only be assumed what mode of transport has been used for particular journeys. Generally greater distances are travelled by larger vehicles and this logic has been applied to the transport stages in a consistent and comparable manner.

It is expected that it is highly unlikely that air freight will play a significant role in the supply chains of the components considered in this study. Although, many supply chains depend on air travel to reduce lead time and transport goods quickly, none of the components considered here are perishable or thought to be time critical. Therefore, where the primary data suggests either short or long haul air travel may have been used, an alternative scenario has also been mapped which replaces the journey with a combination of road and sea travel, with assumptions made on the ports and routes used.

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In order to report on energy use, vehicles have been linked to specific fuel types. Energy figures are then calculated backwards by comparing the emissions in a step with the emission factor (kg CO2-eq. / MJ) of the relevant fuel.

Aviation

This study draws on data that refers to all air freight, rather than extracting figures that differentiate between passenger and cargo services. This is due to fact that, supply chain information is not available as to what type of service has been undertaken for specific journeys or what type of aircraft the component will be used on. As passenger services often carry large amounts of cargo, it has not been assumed supply chain flights will be dedicated to cargo.

The methodology used to calculate the figures is discussed by Defra in their methodology papers.

Passenger Surface Transport

The figures released in Defra (2008) can in most cases be extracted per ‘tonne km’, allowing figures to be calculated in terms of the CO2 burden of transporting a particular mass over distance in a set vehicle. This is useful when investigating the emissions of freight and cargo bearing transport. As neither petrol nor diesel car are regularly used for freight or cargo, figures are not displayed in this manner but are instead given per km travelled on a car market class basis. In order to determine a comparable CO2 per t.km, the masses of the example cars (of each class) have been aligned with the relative emissions.

Masses have been extracted from the technical specifications of car makers and from other comparison sites found via web-based searches.

The mass and emissions have been plotted on a graph, to which has been applied a ‘line of best fit’. The gradient of this line has therefore been used as the CO2 per t.km, for a typical car. This assumes that the market is constituted by an equal number of cars from each class.

Freight surface transport

Emission factors for cargo transported by freight surface transport vehicle have been taken directly from Defra (2011). As no loading information has been provided by the partner average loading data have been used which is also reported by Defra. It is also notable that return journeys have not been considered for these types of transport. Depending on the structure of a supply chain and planning efficiencies, return journeys can amount to non-trivial total contributions.

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Usage

The use phase is treated much like the distribution and transport phase in that emissions are based upon the burden of transporting a mass over distance.

According to the Defra Guidelines (2010), the use phase describes the activities and energy consumed when the product is used by the end consumer. This includes the energy required during storage, preparation, application and maintenance / repair (for long use phases). As all the components considered in this study are ‘vehicle parts’ (i.e. they have been produced to be used on a vehicle), the burden induced by their transportation during use has been considered. This will undoubtedly and appreciably outweigh any of the other burdens in usage.

Unlike the transportation stage, each and every journey is not accounted for individually; instead estimates have been made as to how far the component is expected to travel over its useful life. It has been useful in dividing this calculation into it constituent parts, allowing easy estimates regarding;

the annual distance travelled by the vehicle (km);

the expected service life of the vehicle (years); and

the number of times the component is expected to be replaced.

Clearly, these figures will vary significantly depending on how the vehicle is used and quite radically different figures could relate to the same vehicle. Where no information has been sourced regarding a components usage distance, assumptions have been made based upon industry research and similarities to other partners’ components.

This allows emissions to be reported upon in various ways, for example it allows one to analyse emissions per component piece or per functional area. This may be preferable when comparing components that fulfil the same function but where design alterations or manufacturing changes influence its useful life.

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End-of-life

Mounting obligations on producer responsibilities are making end-of-life scenarios an important consideration for designers, manufacturers and recyclers alike. Many parts are not simply sent to landfill and discarded at the end- of-their useful life but instead undergo additional processing to restore their utility and value.

For example, remanufacturing, the process of returning used parts to an ‘as new’ condition, is a strategy for the profitable and environmental sensitive treatment of end-of-life products. Remanufacture results in the extension of a product’s life and promotes the reuse of components and materials, effectively preventing waste and conserving natural resources. In most cases the additional energy requirement of the remanufacture process is outweighed by the energy saving of not having to manufacture a new product.

There are many perceived environmental advantages of remanufacturing and even larger positive impacts on sustainability are slowly emerging. However, the process is not yet fully understood or measured and it appears that remanufacturing is not a process that is used for any of the components considered in this study. As such the implications of remanufacture have not been investigated.

As discussed previously in the report, the methodology of dealing with recycling is a hotly debated subject, but where possible, this study has attempted to base its findings upon the guidelines presented in the PAS 2050 which proposes that to calculate a full and complete footprint, all the steps in disposal should be considered including transport implications, storage requirements and the energy required in and the direct emissions (carbon decay, methane release, incineration) from the disposal processes (PAS 2050, 2008).

Metals are highly recyclable and a large percentage of the metallic material used in the metals industry is recycled (Anderson, 2006). Collected metal scrap is converted to new material of equal or similar quality through metallurgical processes, such as remelting and refining. The level of processing will very much depend on the metal grades considered and the requirements of the product.

Nevertheless, in terms of boundaries, it is generally considered appropriate that the “system boundaries for recycled waste stop upon the point where the material is recycled or the product is sold. In some cases this will include transport (e.g. municipal recycling), in others it will not (e.g. where companies sell waste for recycling)” (Carbon Trust, personal communications, 2010). In this respect, all waste that is recycled is treated the same irrespective of the recycling method taken and given an emission factor of 0 kg CO2/kg and only the emissions of transport from point of disposal to waste treatment facilities are considered.

Considering only the primary materials used in the supply chain, there will only be a minor amount of material that is not recycled. In relation to the landfill emission of material that is not recycled, although, metals and glass contain do some carbon of fossil origin, the combustion of significant amounts of metal and glass in not common. Likewise natural rubbers and plastics contain content that would not likely degrade under anaerobic conditions at solid waste disposal sites (IPCC Guidelines, 2006). The IPCC guidelines state that, the DOC (degradable organic carbon or the portion of organic carbon present in solid waste that is susceptible to biochemical decomposition) for metals and plastic is 0 %. Therefore, it has been assumed that the emission factor for sending inert materials to landfill will be given an emission factor of 0 kg CO2/kg. This is thought reasonable as any GHG emissions contributed are expected to be negligible.

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Data on transport vehicles and distances have been taken from studies conducted by ecoinvent (Doka, 2009), which relate to similar materials. The burdens of the other processes involved in disposal are not included in the figures presented in the results section of this report.

References

Atherton, J. (2006), Declaration by the Metals Industry on Recycling Principles, Life Cycle Management, International Journal of Life Cycle Assessment, found at http://www.world-aluminium.org/cache/fl0000130.pdf, last accessed 23rd September 2010

Carbon Trust (2010), personal communications with Thomas Caldicott, [email protected], 14th September 2010

Classen, M., Althaus, H. J. and Blaser, S. (2009), Life cycle inventories of metals, ecoinvent v2.1 report No. 10

Choate, W. T. And Green, J. A. S. (2003), U.S. Energy requirements for Aluminium production: Historical perspectives, theoretical limits and new opportunities, Energy Efficiency and Renewable Energy, U.S. Department of Energy, http://www.secat.net/docs/resources/US_Energy_Requirements_for_Aluminum_Production.pdf

DEFRA (2008), 2008 Guidelines to Defra's GHG Conversion Factors: Methodology Paper for Transport Emission Factors, Department for Environment, Food and Rural Affairs

Defra Guidelines (2010), 2010 Guidelines to Defra / DECC’s GHG Conversion Factors for Company Reporting, Department of Energy and Climate Change

Defra Guidelines (2011), 2011 Guidelines to Defra / DECC’s GHG Conversion Factors for Company Reporting, Department of Energy and Climate Change

Dhingra, R., Overly, J. G. and Davis, G. A. (1999), Life-cycle environmental evaluation of aluminium and composite intensive vehicles, Centre for clean products and clean technologies, University of Tennessee

Doka, G. (2009), Life Cycle Inventories of Waste Treatment Services, ecoinvent report No. 13, Swiss Centre for Life Cycle Inventories

Frees, N. (2008), Crediting Aluminium Recycling in LCA by Demand or by Disposal, International Journal of Life Cycle Assessments, Issue 13, Number 3, pp. 212 – 218

Fuel mix (2010), How green is your energy?, http://www.fuelmix.co.uk/index.htm, last accessed 2nd September 2010.

Greenhouse Gas Protocol Initiative (2009), Emission Factors from Cross-Sector Tools, found at http://www.ghgprotocol.org/calculation-tools/all-tools, last accessed 6th September 2010.

IPCC Guidelines (2006b), Waste generation, composition and management data, IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 5, Chapter 2

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Koch, M. and Harnisch, J. (2002), CO2 Emissions Related to the Electricity Consumption in the European Primary Aluminium Production, International Journal of Life Cycle Assessments, Issue 7, Number 5, pp. 283 – 289

Hammond, G. And Jones, C. (2008), Inventory of Carbon & Energy (ICE), Version 1.6 a, Sustainable Energy Research Team (SERT), University of Bath

PAS 2050 (2008), Guide to PAS 2050: How to assess the carbon footprint of goods and services, BSI British Standards Crown and Carbon Trust

Steiner, R. and Frischknecht, R. (2007), Metals processing and compressed air supply, ecoinvent report No. 23

U.S. EIA (2007), Energy Consumption by Manufacturers -- Data Tables, U.S. Energy Information Administration, U.S. Department of Energy, http://www.eia.doe.gov/emeu/mecs/mecs2002/data02/shelltables.html

U.S. Environmental Protection Agency (2007), eGRID2007 Version 1.1, available from http://www.epa.gov/cleanenergy/energy-resources/egrid/index.html, last accessed 6th September 2010.

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Findings

This section will endeavour to provide an estimate of the CO2 footprint of the components considered within Atkins. In the absence of additional data, the footprinting process predominantly considers the primary processing activities conducted in the supply chain and excludes the majority of the supportive and auxiliary processes, which may or may not add significant CO2 contributions to the supply chain. The reported footprints are therefore expected to underestimate the real life cycle emissions of the components discussed.

This section reports in CO2-eq. units which relate to global warming over a timescale of 100 years. Although the importance of other impact categories should be acknowledged they are not discussed in this section. This reflects the availability of data on this issue and the level of consumer and corporate understanding. Moreover, it is loosely predicated on the belief that the key issues responsible for reducing GHG emissions and will help to improving the performance on the product in other areas and will enhance the level of awareness regarding sustainability.

Energy values are also reported in this section.

Results tables

Breakdowns of the carbon footprints calculated for each component are shown in the tables contained in this section. For the purposes of environmental modelling, results have been displayed in a variety of methods. This allows one to compare emissions, not only on a per component basis but also, per kg of material product. The relative importance of each life cycle stage can also be analysed, with regard to each individual components, the aggregate total for each of the partners and the aggregate total for each of the materials considered.

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Raw material Raw material Final part Material Company Part Scenario location mass mass efficiency kg kg % Scenario 1 Korea, Republic of 12.5 1.6 13% Alcon Brake Calipers Scenario 2 Korea, Republic of 12.5 1.6 13% Scenario 1 India* 12.6 1.1 9% Bentley Transmission Mount Bracket Scenario 2 India* 1.2 1.1 95% Scenario 1 Japan 2.3 0.29 12% Eggcrate Clip Scenario 2 Japan 2.3 0.29 12% Scenario 1 Japan 1.1 0.15 14% Termination Fitting Scenario 2 Japan 1.1 0.15 14% Scenario 1 Japan 3.0 0.26 9% Sill Fitting Scenario 2 Japan 3.0 0.26 9% Scenario 1 Japan 7.2 0.42 6% Floor Beam End Fitting Scenario 2 Japan 7.2 0.42 6% Boeing Actuator Fitting Duct Support Fitting Scenario 1 Japan 16.1 15.3 95% Pan Casting Scenario 2 Japan 16.1 15.3 95% Fitting Casting – Tire Burst Protector Scenario 1 Japan 0.45 0.43 95% 12’’ Strut Inlet Duct Scenario 2 Japan 0.45 0.43 95% Scenario 1 Middle-East 54.9 46.5 85% Elevator Link Scenario 2 Middle-East 54.9 46.5 85% Scenario 1 - Option 1 India 0.89 0.65 73% Scenario 1 - Option 2 India 0.89 0.65 73% Diesel Front Plate 3 (gravity cast) Scenario 2 - Option 1 France 0.91 0.65 72% Scenario 2 - Option 2 France 0.91 0.65 72% Diesel Front Plate 3 (squeeze cast) Turkey 1.3 0.65 50% Delphi Pump Housing France 2.0 0.83 41% Venturi United States 0.0027 0.0022 81% ECU Body India* 0.038 0.017 45% Fuel Connector Plate India* 0.048 0.010 21% Pipe India* 0.013 0.013 100% Upper Class Monitor Arm India* 2.9 0.86 29% Economy Tray Table Arm Virgin Front Row Monitor Arm Foot Rest Plate Premium Economy Tray Table Arm

*Location assumed Table 6 – Components assessed

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Company Part Scenario Raw Material Process Transport Usage Disposal Total

(kg CO2-eq.) Scenario 1 199 11 21 247 0 479 Alcon Brake Calipers Scenario 2 199 11 16 247 0 473 Scenario 1 549 9 18 180 0 755 Bentley Transmission Mount Bracket Scenario 2 15 0 2 180 0 198 Scenario 1 157 2 22 18,983 0 19,164 Eggcrate Clip Scenario 2 157 2 5 18,983 0 19,147 Scenario 1 71 1 9 9,491 0 9,573 Termination Fitting Scenario 2 71 1 2 9,491 0 9,565 Scenario 1 202 3 26 17,019 0 17,251 Sill Fitting Scenario 2 202 3 5 17,019 0 17,229 Scenario 1 482 7 64 27,492 0 28,045 Floor Beam End Fitting Scenario 2 482 7 12 27,492 0 27,993 Boeing Actuator Fitting Duct Support Fitting Scenario 1 1,084 9 90 821,663 0 822,846 Pan Casting Scenario 2 1,084 9 40 821,663 0 822,796 Fitting Casting – Tire Burst Protector Scenario 1 30 0 2 28,147 0 28,180 12’’ Strut Inlet Duct Scenario 2 30 0 1 28,147 0 28,178 Scenario 1 5,954 44 350 3,042,483 0 3,048,832 Elevator Link Scenario 2 5,954 44 92 3,042,483 0 3,048,574 Scenario 1 - Option 1 48 1 1 125 0 174 Scenario 1 - Option 2 48 1 1 125 0 174 Diesel Front Plate 3 (gravity cast) Scenario 2 - Option 1 6 0 1 125 0 132 Scenario 2 - Option 2 6 0 2 125 0 133 Diesel Front Plate 3 (squeeze cast) 31 1 1 125 0 158 Delphi Pump Housing 13 1 3 158 0 175 Venturi 0 0 0 0 0 0 ECU Body 3 0 0 3 0 6 Fuel Connector Plate 4 0 0 2 0 6 Pipe 1 0 0 3 0 4 Upper Class Monitor Arm 217 1 8 56,101 0 56,327 Economy Tray Table Arm Virgin Front Row Monitor Arm Foot Rest Plate Premium Economy Tray Table Arm

Table 7 - Footprints per component

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Final part Raw Company Part Scenario Process Transport Usage Disposal Total mass Material

kg (kg CO2-eq. / kg) Scenario 1 1.6 126 7 13 156 0 303 Alcon Brake Calipers Scenario 2 1.6 126 7 10 156 0 300 Scenario 1 1.1 478 8 15 156 0 658 Bentley Transmission Mount Bracket Scenario 2 1.1 13 0 2 156 0 172 Scenario 1 0.29 541 7 75 65,458 0 66,081 Eggcrate Clip Scenario 2 0.29 541 7 16 65,458 0 66,023 Scenario 1 0.15 489 7 64 65,458 0 66,017 Termination Fitting Scenario 2 0.15 489 7 11 65,458 0 65,965 Scenario 1 0.26 778 11 102 65,458 0 66,349 Sill Fitting Scenario 2 0.26 778 11 18 65,458 0 66,265 Scenario 1 0.42 1,147 17 152 65,458 0 66,774 Floor Beam End Fitting Scenario 2 0.42 1,147 17 28 65,458 0 66,650 Boeing Actuator Fitting Duct Support Fitting Scenario 1 15.3 71 1 6 53,880 0 53,957 Pan Casting Scenario 2 15.3 71 1 3 53,880 0 53,954 Fitting Casting – Tire Burst Protector Scenario 1 0.43 71 1 6 65,458 0 65,535 12’’ Strut Inlet Duct Scenario 2 0.43 71 1 1 65,458 0 65,531 Scenario 1 46.5 128 1 8 65,458 0 65,594 Elevator Link Scenario 2 46.5 128 1 2 65,458 0 65,589 Scenario 1 - Option 1 0.65 74 1 1 191 0 267 Scenario 1 - Option 2 0.65 74 1 1 191 0 267 Diesel Front Plate 3 (gravity cast) Scenario 2 - Option 1 0.65 9 0 2 191 0 202 Scenario 2 - Option 2 0.65 9 0 3 191 0 203 Diesel Front Plate 3 (squeeze cast) 0.65 48 1 2 191 0 242 Delphi Pump Housing 0.83 16 1 4 191 0 211 Venturi 0.0022 13 0 4 191 0 209 ECU Body 0.017 165 0 6 191 0 362 Fuel Connector Plate 0.010 358 1 9 191 0 558 Pipe 0.013 75 0 4 191 0 270 Upper Class Monitor Arm 0.86 253 2 9 65,458 0 65,722 Economy Tray Table Arm Virgin Front Row Monitor Arm Foot Rest Plate Premium Economy Tray Table Arm

Table 8 - Footprint per kg

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Raw Company Part Scenario Process Transport Usage Disposal Material

% Scenario 1 42% 2% 4% 52% 0% Alcon Brake Calipers Scenario 2 42% 2% 3% 52% 0% Scenario 1 73% 1% 2% 24% 0% Bentley Transmission Mount Bracket Scenario 2 8% 0% 1% 91% 0% Scenario 1 1% 0% 0% 99% 0% Eggcrate Clip Scenario 2 1% 0% 0% 99% 0% Scenario 1 1% 0% 0% 99% 0% Termination Fitting Scenario 2 1% 0% 0% 99% 0% Scenario 1 1% 0% 0% 99% 0% Sill Fitting Scenario 2 1% 0% 0% 99% 0% Scenario 1 2% 0% 0% 98% 0% Floor Beam End Fitting Scenario 2 2% 0% 0% 98% 0% Boeing Actuator Fitting Duct Support Fitting Scenario 1 0% 0% 0% 100% 0% Pan Casting Scenario 2 0% 0% 0% 100% 0% Fitting Casting – Tire Burst Protector Scenario 1 0% 0% 0% 100% 0% 12’’ Strut Inlet Duct Scenario 2 0% 0% 0% 100% 0% Scenario 1 0% 0% 0% 100% 0% Elevator Link Scenario 2 0% 0% 0% 100% 0% Scenario 1 - Option 1 28% 0% 0% 71% 0% Scenario 1 - Option 2 28% 0% 1% 71% 0% Diesel Front Plate 3 (gravity cast) Scenario 2 - Option 1 4% 0% 1% 95% 0% Scenario 2 - Option 2 4% 0% 1% 94% 0% Diesel Front Plate 3 (squeeze cast) 20% 0% 1% 79% 0% Delphi Pump Housing 7% 0% 2% 90% 0% Venturi 6% 0% 2% 91% 0% ECU Body 46% 0% 2% 53% 0% Fuel Connector Plate 64% 0% 2% 34% 0% Pipe 28% 0% 2% 71% 0% Upper Class Monitor Arm 0% 0% 0% 100% 0% Economy Tray Table Arm Virgin Front Row Monitor Arm Foot Rest Plate Premium Economy Tray Table Arm

Table 9 - % by life cycle stage

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Total Raw Total Final Material Raw Company Process Transport Usage Disposal material mass part mass efficiency Material

kg kg % % Alcon 25.0 3.2 13% 42% 2% 4% 52% 0% Bentley 13.8 2.3 17% 59% 1% 2% 38% 0% Boeing 169.9 126.6 74% 0% 0% 0% 100% 0% Delphi 7.0 4.1 59% 17% 0% 1% 82% 0% Virgin 2.9 0.9 29% 0% 0% 0% 100% 0% Total 218.6 137.0 63% 0% 0% 0% 100% 0%

Table 10 - % by life cycle stage and by partner Total Total Raw Final Material Raw Material Process Transport Usage Disposal material part efficiency Material mass mass kg kg % % Aluminium: 2618, wrought, T6 25.0 3.2 13% 42% 2% 4% 52% 0% Aluminium: 6082, wrought, T6 12.6 1.1 9% 73% 1% 2% 24% 0% Aluminium: A413.2: LM6 - M, cast (Al-12Si) 1.3 0.7 50% 20% 0% 1% 79% 0% Aluminium: S332.1: LM26-TE, cast (Al/9Si/3Cu/Mg) 3.6 2.6 72% 18% 0% 1% 81% 0% Aluminium: S380.0: LM24-M, cast (Al/8Si/3Cu/Fe) 5.0 1.7 34% 0% 0% 0% 100% 0% Titanium: Alpha-beta alloy, Ti-6Al-4V, cast 169.9 126.6 74% 0% 0% 0% 100% 0% Zinc: Zinc-aluminium alloy, Alloy 3, pressure die casting 1.2 1.1 95% 8% 0% 1% 91% 0% Polyamide / Nylon (PA): PA, Type 66, 30 - 33% glass fibre 0.0 0.0 81% 6% 0% 2% 91% 0%

Table 11 - % by life cycle stage and by material

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Findings and discussion

Life-cycle considerations

After analysing the results displayed in the ‘Results tables’, it quickly becomes apparent that the raw material manufacture and usage phases of the life-cycle stand as the worst performing areas of the components considered in this study. In particular the usage phase seems to dominate the lifecycle emissions of most of the parts, often contributing over 90% of the total emissions. The level of domination

As discussed earlier in this report, the burden of transporting a set mass over a set distance differs greatly depending on the mode of transport used. As such, the vehicles on which the Atkins parts will be used radically affects the emissions in usage. As one may anticipate, the emissions of aircraft considerably outweigh those of other vehicles ‘per tonne kilometre’, and accordingly the usage emissions of components designed as aircraft parts considerably outweigh those destined for other vehicles. The level of difference between the aircraft and surface transport parts during usage is approximately two orders of magnitude, rising from figures in the hundreds for passenger vehicles to the tens of thousands for aircraft.

This is in most evidence when viewing Error! Reference source not found.. The CO2 burden resulting from the manufacture of the raw material needed for Boeing’s parts, pales into insignificance when compared to the burden of their usage. This cannot be attributed to a declination of raw material emissions; indeed the use of titanium means that on average Boeing’s raw material phase is itself the worst offending of all the partners per kilogram used. Instead, it is simply down to the fact that they are destined to be used on either long or short-haul air-craft which not only have worse contributions per mile travelled, but also travel much further distances over their lifetime.

Also notable with Boeing’s components is an obvious deviation between the CO2 burdens of raw material manufacture per kg of part. In all but one case (Elevator link - Kazakhstan), the raw material manufacture stage occurs at the same location (Japan) and therefore, this is not due to a geographical differences in the emission factors of local fuel mixes. In fact, it is the resource efficiency of the processes that are responsible for variations in the CO2 burdens of raw material manufacture per kg of part. In the case of the ‘Floor beam end fitting’ there is a ‘buy-to-fly’ (how much material is needed in order to manufacture to the final flying part) ratio as small as 6%. The ‘Sill fitting’, ‘Eggcrate clip’ and the ‘Termination fitting’ do not perform much better, with ratios of 9%, 12% and 14% respectively. This contrasts greatly with Boeing’s other components, the ‘Pan Casting’, the ‘12” Strut inlet duct’ and the ‘Elevator link’, which have much improved buy-to-fly ratios of around 95%, 95% and 85% respectively.

It seems obvious, but a key piece of advice proposed by Koelsch (2008) for reducing energy consumption is to machine less. One example given is the waste generated in machining the wall sections for airplanes, a classic antithesis of near net shape production. He reports, that a high-speed machine may whittle a 227 kg slab of aluminium down to a 27 kg shell, a tremendous amount of waste regarding time, metal and power. If the machining of that part could somehow be started at close to the right shape, a lot less time and power may be used removing material.

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The components that fair better in terms of efficiency in this study all undergo some sort of casting process, allowing geometries to be manufactured without the huge reductions in mass from conventional machining. What is more, the casting processes themselves only contribute an extremely small quantity of CO2 relative to the production of raw material, and it appears the benefit of a reduction of material far outweighs the added burden of the process. The detriment of this inefficiency is magnified due to Boeing’s obligation to only use virgin raw material.

Norgate et al. (2007) assert that, one way of achieving greater efficient in resource use is through a reduction in the amount of energy and materials required to service economic functions or ‘dematerialisation’. They suggest smaller and lighter products with longer service lives can reduce the amount of materials required by society, whilst at the same time, re-use and recycling can also minimise fresh inputs and waste outputs.

Part Mass

Generally speaking, it is as to be expected, that lighter components result in less CO2 emissions than with heavier components. Indeed, Boeing’s ‘Elevator Link’ appears as the worst offending part considered, and by some distance. However, given its colossal size, this is understandable and on a per kg basis its total emissions fall much more in line with the rest of Boeings components.

This implies that mass reduction really can make a significant difference over the life-cycle of the components considered, and remains a major factor in the CO2 burdens calculated.

This is most evident with Bentley’s ‘Transmission Mount Bracket’ which can be manufactured from either aluminium (aluminium – 6082, wrought, T6) or zinc (zinc-aluminium, alloy 3, pressure die casting). For this component, 12.58 kg of aluminium is required to produce an aluminium part (9% resource efficiency), while just 1.20 kg of zinc is required to manufacture a zinc part (95% resource efficiency). The effect of this permeates down the whole supply chain.

First of all, the energy implications of raw material manufacture are much worse with the aluminium part, although it should be noted that aluminium manufacture (208 MJ / kg) is also a more energy intensive process than zinc production (70 MJ / kg). The combination of these two factors results in a raw material burden of 15 kg

CO2 for the zinc component and almost 550 kg CO2 for the aluminium component.

Process energy follows in demonstrating the importance of mass reduction. At this point, the additional energy requirements of removing the large amount of aluminium results in a much greater CO2 output during processing.

Indeed, the processes performed on the aluminium part contribute 9 kg CO2, whilst approximately 0.4 kg CO2 is emitted from the processes performed on the zinc part. This is in spite of the fact that the zinc also has to be cast in order to manufacture the final component.

Finally, the clearest representation of the effect of the mass change is shown in the figures representing the transport phase of the life-cycle. Although following exactly the same routes, the impact of transporting the aluminium part stands at 18 kg CO2, compared to an impact of just 2 kg CO2 for the zinc part. This can be wholly ascribed to the difference in mass of between the components as the journeys taken during the supply chain have been assumed as equal.

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Location differences

It seems there is a preference for the partners to conduct similar processes at a specific location, for instance a production facility, a central foundry or a processing plant. Because of this commonality within the partners’ components, it is difficult to observe the significance of geographic locations in the supply chain from the results displayed above.

Nevertheless, one example which shows the importance of location when analysing CO2 emissions, is Delphi’s ‘Diesel Front Plate 3’, for which the raw material is produced at three different locations, namely India, France and Turkey.

Energy of raw material CO impact Raw material CO impact 2 Material production 2 (kg CO per kg of material manufacture location (kg CO per kWh) 2 (MJ / kg) 2 produced) Aluminium (Al/9Si/3Cu/Mg) 220 France 0.08 11.1 Aluminium (Al/9Si/3Cu/Mg) 220 Turkey 0.44 44.3 Aluminium (Al-12Si) 220 India 0.94 54.8

Table 12 – CO2 implications of changing location

As is evident in Table 12, CO2 emissions do depend upon the energy emission factor of the location concerned and the final burdens correlate closely with the relative emission factors used. As aluminium production is especially reliant upon electricity; the differences are more pronounced than they may be elsewhere.

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The emission factors of a selection of locations are shown in Table 13 - Electricity emission factors, along with the emission factors of a selection of other locations.

CO impact Energy location 2 (kg CO2 per kWh)

USA - Vermont 0.00 Paraguay 0.00

Norway 0.01 France 0.08 USA - Washington 0.15 Spain 0.35 Germany 0.40 Italy 0.40 Japan 0.42 Turkey 0.44 South Korea 0.46 United Kingdom 0.50 USA - Virginia 0.54 USA 0.60 USA - Michigan 0.61 USA - Ohio 0.80 India 0.94 USA – District of Columbia 1.10 Botswana 2.12

Table 13 - Electricity emission factors (GHG Protocol Initiative, 2009)

There is a clear difference between the emission factors of the best and worst performing nations and regions.

Table 13 shows for example that, 1 kWh of electricity used in the District of Columbia, USA (1.1033 kg CO2 per kWh) will result in 7 times the amount of CO2 that would be emitted from using the same amount of electricity in

Washington, USA (0.1502 kg CO2 per kWh) and 525 times that of Vermont, USA (0.0021 kg CO2 per kWh). Plainly, the implications of this will be greater for more electricity intensive processes, where a higher proportion of the energy is susceptible to the variation in emission factors.

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Displayed in Table 14 - CO2 impact of processing based upon location, is the CO2 burden of processing the same 1 kg titanium (Alpha-beta alloy, Ti-6Al-4V, cast) raw material billet in France, the UK and India.

CO impact Process Energy location 2 (kg CO2 per kg) France 0.18 CNC Machining United Kingdom 1.09

India 2.04 France 0.23

Gravity die casting United Kingdom 0.40 India 0.58 France 0.19 Drop forging United Kingdom 0.45 India 0.72

Table 14 - CO2 impact of processing based upon location

Again this clearly shows the importance of the source of electricity used when considering the CO2 burden of supply chain processes.

It must be acknowledged that, this table is only intended to display the impact of different emission factors upon

CO2 emissions; it assumes that there will be an equal energy requirement for processes independent of location. Locating processing plants in France may well increase total emissions if actual energy requirements should increase, as they may if other factors were to be introduced as a result of processing in France.

Similar conclusions can be made from Table 15 - CO2 impact of producing titanium and aluminium based upon location, which shows the impact of differential emission factors upon the CO2 emitted by producing 1 kg of titanium (Alpha-beta alloy, Ti-6Al-4V, cast) or aluminium (A413.2: LM6 - M, cast (Al-12Si)). Shown is the impact of primary (virgin) production, recycled production and a combination of virgin and recycled production at industry standard levels for titanium and aluminium.

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CO impact Material Material source Energy location 2 (kg CO2 per kg) France 165.86 Virgin raw material United Kingdom 208.61 India 253.35 France 37.54 Titanium Recycled United Kingdom 92.10 India 149.19 France 137.63 Industry production United Kingdom 182.98 India 230.44 France 12.67 Virgin raw material United Kingdom 34.89 India 58.13 France 5.46 Aluminium Recycled United Kingdom 27.97 India 51.53 France 9.60 Industry production United Kingdom 31.94 India 55.32

Table 15 - CO2 impact of producing titanium and aluminium based upon location

Thus, location does appear to play a vital role in the production and processing of resource. Indeed Das et al. (2004) claim that, driven primarily by energy considerations, there has been a major change in the geographical distribution of primary aluminium production over the past few decades, even as the energy efficiency of the process improves.

Recycled content

What also becomes apparent from Table 15 - CO2 impact of producing titanium and aluminium based upon location, are the strong CO2 reductions that can occur from the production of recycled material rather than virgin material. In India, using 1 kg of primary titanium (Alpha-beta alloy, Ti-6Al-4V, cast) results in CO2 emissions 104 kg (41%) higher than when using secondary material. The increases are even more marked in the UK where the emissions increase by 116 kg CO2 (56%) and France 128 kg CO2 (77%).

Smaller savings still occur with aluminium where the energy required to produce secondary aluminium is closer than that required to produce primary aluminium. Nevertheless, these are important saving considering the volume of aluminium produced each year.

Figure 2 presents the energy savings (MJ) of using recycled raw material in place of virgin content.

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380 400 372 350 300 250 200 200 189 189 189 200

MJ / kg MJ 150

Energy saving Energy 100 57 50 0

Material Grade

Figure 2 - Energy savings of recycled production

What is more, of all the materials currently used by society, metals have arguably the greatest potential for recycling. Norgate et al. (2007) suggest that, metals are not biodegradable and their elemental nature means that they can have an unlimited lifespan.

Theoretically at least, Das et al. (2004) profess that there can be an energy saving from recycling;

Smelting Re-melting (BTU / lb) (BTU / lb)

Theoretical minimum 10,200 510 Current average 26,000 2,200 Practically achievable 20,000 925 Energy efficiency savings opportunity 6,000 1,275

Table 16 – Energy requirements of smelting vs. re-melting

The savings suggested in this section and various quarters has given rise to the almost universal acceptance that the recovery, re-use and recycling of discarded materials is vital in achieving greater sustainability in resource use. One must be careful however, in considering recycling based on the entire life-cycle. Norgate (2004, pp. ii) lists some general considerations;

secondary metal production is more “sustainable” in life cycle energy terms than primary metal production up to a certain recycling rate, beyond which the additional energy required to recover and recycle the more widely dissipated metal exceeds the energy required to produce the equivalent amount of primary metal;

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this maximum recycling rate is very dependent on the recycling scenario (e.g. metal, product nature, geographical location, etc.) being considered;

there is an optimum recycling rate at which the life-cycle energy consumption per application is at a minimum relative to primary metal production, and this optimum recycling rate is also very recycling scenario-dependent; and

it can be expected that maximum recycling rates will be greater for those metals having the highest GER (Gross Energy Requirement) values for primary metal production, such as aluminium, nickel and titanium, and lower for those metals having the lowest GER values for primary metal production such as copper, steel and lead.

Despite these reservations, as an environmental hotspot for many of the components, raw material production is an area that would appear to need attention, recycled content (/ production method) sitting beside material selection and the location of the supplier all playing vital roles in the CO2 and energy footprints. In trying to consider the lifecycle emissions it should be acknowledged that, the location of virgin raw material production would in all probability be completely different to that of the recycled production, and the early stages of the supply chain would take on an entirely different dynamic.

Table 15 shows that the savings resulting from the use of 100% recycled material over virgin material diminish as poorer energy mixes are used, and the difference between virgin raw material produced in France and recycled raw material produced in India is just 10%. Then again, a combination of a superior energy mix and a high recycling rate can result in immense reductions. Furthermore, if you consider that primary production often occurs at distant locations, whereas metal recycling is a £5 billion UK industry (BMRA, 2010) which will probably occur much closer to home, then the emissions of transportation and storage will also be reduced.

Stand alone changes in the supply chain can be of great consequence, for instance in choosing where to source your material (China (0.79 kg CO2 / kWh), Russia (0.33 kg CO2 / kWh), Kazakhstan (0.52 kg CO2 / kWh) and Brazil

(0.08 kg CO2 / kWh)), but decision makers will need to take into account a combination of all these factors if they wish to have the most significant impact on the carbon footprints of their operations.

Material selection

The choice between one material and the next can result in important consequences for the CO2 implications and energy requirements of raw material production and processing activities along the supply chain. Simplistically speaking, less energy is needed to produce and process certain materials over others and consequently they hold a smaller propensity for damage to the environment. For example, Figure 3 illustrates the CO2 implications of producing 1 kg of a selection the various materials discussed in this project (the process is assumed to take place in the UK and use a national average energy mix). If CO2 reduction at the primary production phase was the sole concern of the supply chain, there would be a clear decision as to which material should be selected.

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CO2 implications of primary production 250 208.61 201.41 200 150

/ kg) / 106.50 2 burden

2 100 (CO CO 33.17 32.68 27.71 26.98 28.07 50 6.74 0

Atkins Materials

Figure 3 – CO2 implications of primary production

There are clearly other attributes that need to be considered and, as stressed upon in numerous occasions in this report, it is the whole life-cycle that should be considered along with other eco-indicators such as other GHG emissions, water user, chemical requirements and toxic waste, landfill use and so on. Dhingra et al. (1999) explain that the use of certain materials that seem benevolent to the environment in one particular life-cycle stage might require huge amounts of energy to produce in one of the upstream stages, rendering their selection unjustifiable. Likewise, a seemingly large reduction in emissions during one stage might be rendered inconsequential by a hefty increase in another stage.

Differences in factors such as ore grade, process technology, fuel source for electricity generation and transportation issues however, make it difficult to generate comparable figures for different supply chains. For example, when comparing the energy intensity of different materials, Norgate et al. (2004) propose that stainless steel is comparable with copper and zinc, lower than aluminium and nickel, but higher than steel and lead. Widening their boundaries to consider other impact categories toxicity and lifespan factors, they promote stainless steel above the other materials, as copper and lead are often associated with toxicity concerns and the steels have generally shorter life-spans when compared to stainless steel. This does not take into account the usage, or downstream processes associated with the metals though and as we have seen inclusion of such stages can have a significant effect on the comparative CO2 impacts of components. For instance, density and mass considerations will have enormous effects on aerospace components which travel vast distances over their lifetime.

Dhingra et al. (1999) do warn that the use of lighter-weight materials including primary aluminium, titanium and magnesium does have a trade-off. The CO2 reductions stemming from the use stages are offset by the increased burdens of the extraction and materials processing life-cycle stage. They go on to suggest that, any consequential fuel efficiency gains resulting from lighter-weight materials is offset by a much greater energy demand per mass of product produced and a substantially greater quantity of air emissions and solid wastes generated.

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Their findings, which refer to road based vehicles, compare well to the findings for similar vehicles discussed in this report that have often found raw material production to be an important life-cycle phase of components destined for use on petrol and diesel engine cars. On the other hand, the findings of this study imply that for air-craft components in particular a high strength to weight-ratio is a most favourable characteristic and relatively small reductions in mass merit the additional energy intensity of initial primary production.

Another finding by Norgate et al. (2004) is that it is not just the choice of material that is important but also the way in which it is produced. In their investigation into sources of stainless steel, Norgate et al. (2004) used a life cycle approach to show how changes to production processes and material selection can affect energy consumption. They demonstrate that, when ferronickel is used the nickel source for stainless steel, the total energy consumption (75 MJ / kg) is 50% higher that when nickel metal is used as the nickel source (49 MJ / kg). Their results also show that, when used as the feedstock for stainless steel the production of ferronickel made by far the largest contribution (59%) to the total energy consumption, as opposed to a much more evenly distribution of the various stages when nickel metal was used as the source.

Processing

As with the transportation and disposal phases, processing emissions could easily be overlooked in the context of entire lifecycles, rarely contributing more than 1% of the total emissions. What is more, they are very much a function of the mass processed and the material considered. In the cases where process energy is high, there are significant quantities of material removed through CNC machining.

Casting emerges as a solution which appears to alleviate this, as generally speaking the process requires less energy per kg processed and results in much less wastage. Frees (2008) exclaims that in the processing of aluminium it is possible to apply so-called near-net shaping in aluminium castings and forged products where no material is wasted and only little finishing is needed.

Furthermore, the fact that casting is more reliant on natural gas, which boasts an emission factor much lower than that of the average electricity supply, endears it as a favourable alternative to CNC machining with regards to the

CO2 produced.

CNC machining does though, hold immense potential for improvement. As a process entirely reliant upon electricity as a source of energy, it is particularly susceptible to the emission factor of the electricity used. As Table 14 - CO2 impact of processing based upon location illustrates, sourcing electricity from more sustainable sources will have important implications upon the CO2 produced. Considering only the factors within the boundaries of this study, it appears that there may be benefit in actually transporting the component to a location with a favourable energy mix.

Table 17 shows in Option 1 the CO2 burden of machining 15 kg from a piece of titanium (Ti-6Al-4V) in the UK, with no transport steps. Option 2 on the other hand shows the burden of machining 15 kg from a 20 kg billet, which is transported from the UK to France and back again in a 7.5 – 17 tonne rigid lorry.

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Mass processed Impact Phase Location / Journey (kg) (kg CO2) Option 1 Process 15 UK 16.36 Option 2 Transport 20 Birmingham, UK – Matour France 7.43 Process 15 France 2.75 Transport 5 Matour, France – Birmingham, UK 1.86 12.40

Table 17 - Processing emissions by location

It appears that, although travelling 2,210 km, option 2 is environmentally more beneficial, due to the favourable energy mix found in France. In this scenario there is a resource efficiency of 25%, not unreasonable in the context of the values seen with the Boeing components. But it should be noted that improving the resource efficiency and removing smaller amounts of mass relative to the mass transported negates the savings and makes the transportation less favourable. What is more, even though this may reduce processing emissions it does not impact upon the level of waste material and the consequential requirement for additional raw material manufacture.

It should also be noted that this is a simple comparison that does not take into account packing operations or packaging materials for instance. These items will add to the burden of transportation, though these may again be countered by potential savings that could arise from other processing operations which rely on electrical energy. If these too sourced energy from more sustainable sources then other issues surrounding transport may be outweighed.

Transport

Due to the enormous emissions caused by the usage phases and to a lesser extent the raw material phase, transport implications can appear quite low. In the context of a components lifecycle they account for very little of the total CO2 released. Nevertheless, this does not mean they should be excluded from analysis and nor does it mean they are impervious to potential reductions.

For the purposes of this study, air transport is seen as a dispensable, non-essential means of transport. The components are not perishable and the time taken to transport them will in no way affect their characteristics. However, they are in many cases exceptionally valuable items and short travel times alleviate some of the issues with having capital tied up in their existence. Thus, where the partners have suggested that air travel is used, alternative scenarios have been mapped in order to understand the consequences of this in the supply chains. In such cases, one scenario considers the supply chain with air travel whilst the other uses a combination of road, rail and sea transport in its place.

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Emissions from Emissions from Distance by air Total distance Total emissions Supplier Component Scenario air-travel air-travel (km) (km) (kg CO2) (kg CO2) (%)

Scenario 1 6,248 29,024 7 21 34% Alcon Brake Callipers Scenario 2 - 31,232 - 16 -

Scenario 1 10,900 36,074 18 21 85% Eggcrate Clip Scenario 2 - 42,928 - 5 -

Scenario 1 10,900 36,074 8 9 90% Termination Fitting Scenario 2 - 42,928 - 2 -

Scenario 1 10,900 36,074 24 26 90% Sill Fitting Scenario 2 - 42,928 - 5 -

Scenario 1 10,900 36,074 57 64 89% Boeing Floor Beam End Fitting Scenario 2 - 42,928 - 12 -

Scenario 1 6,330 10,462 74 90 82% Pan Casting Scenario 2 - 22,715 - 40 -

Scenario 1 6,330 9,768 2 2 86% 12’’ Strut Inlet Duct Scenario 2 - 22,021 - 1 -

Scenario 1 7,350 14,355 293 350 84% Elevator Link Scenario 2 - 16,724 - 92 -

Table 18 – Relative emissions of air travel vs. non air travel

Looking at the transport phase in isolation, it is evident throughout the study that the choice between using air travel or not has a pronounced affect upon CO2 emissions. Indeed, in many of the supply chains that contain air- travel, this one step can be of greater consequence that the rest of transport steps contained in the supply chain added together.

Usage

Over the full range of component parts considered in this study, usage appears as the most damaging phase of a components lifecycle.

Table 19 shows the CO2 emissions for every kilogram of part produced for each of the phases in the lifecycle, averaged over all of the components considered. Each of the partners’ components share many characteristics, for instance all of Boeing’s components are made from titanium and are aircraft parts, whereas Delphi’s parts are predominantly made from aluminium for use on road vehicle cars. This makes it useful to categorise the parts based upon their company. The percentage breakdown as a proportion of total emissions has also been shown.

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Distribution Raw material Company Processing and Usage Disposal Unit manufacture transport

126 1 6 58,310 0 kg CO2-eq. / kg All 0% 0% 0% 100% 0% %

126 7 12 156 0 kg CO2-eq. / kg Alcon 42% 2% 4% 52% 0% %

168 4 9 156 0 kg CO2-eq. / kg Bentley 59% 1% 2% 38% 0% %

2,768 1 6 62,667 0 kg CO2-eq. / kg Boeing 0% 0% 0% 100% 0% %

77 1 2 191 0 kg CO2-eq. / kg Delphi 17% 0% 1% 82% 0% %

253 2 9 65,458 0 kg CO2-eq. / kg Virgin 0% 0% 0% 100% 0% %

Table 19 – Average implications of lifecycle phases

Analysing the results by the company ownership quickly reveals that the domination of usage is skewed by the massive usage demands of the Boeing components, whose emissions dwarf those of all the other lifecycle stages.

Again, this illustrates the sheer scale of the CO2 emissions of transporting mass via long-haul and short-haul aircraft.

The reason as to why the usage emissions of aircraft components are so high is due to a combination of firstly, their higher emission factor (CO2 per tonne kilometre) and secondly and more significantly, the distances they travel over their lifetime.

A component that is to be placed on an aircraft is assumed to travel up to 2.25 million kilometres per annum, over a 40 year period. What is more, the parts are not expected to be replaced in this period and therefore a single component placed on a long haul aircraft is assumed to travel 90 million kilometres in its lifetime. A standard, petrol engine, passenger surface vehicle on the other hand is estimated to travel 12,500 km per annum over a 15 year period. Again the parts are assumed not to be replaced, leaving the part travelling approximately 187,500 kilometres over its lifetime.

This leaves long haul components travelling approximately 480 times farther than a component designed for a petrol engine automobile. Clearly, this will have a huge impact on the usage emissions which are based on how far the component is expected to travel and the consequential fuel consumed.

As a result it is perhaps unfair to compare the aircraft and road vehicle components directly. Hypothetically at least, if the components were to travel the same distances over their lifecycle then the picture would look very different. Table 20 draws from data modified to suppose that each component would travel 100,000 km over their usage lifetime.

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Raw material Distribution Company Processing Usage Disposal Unit manufacture and transport

126 7 12 83 0 kg CO2-eq. / kg Alcon 55% 3% 56% 37% 0% %

246 4 9 83 0 kg CO2-eq. / kg Bentley 72% 1% 3% 24% 0% %

126 1 6 94 0 kg CO2-eq. / kg Boeing 56% 0% 3% 41% 0% %

39 1 2 64 0 kg CO2-eq. / kg Delphi 37% 1% 2% 60% 0% %

253 2 9 73 0 kg CO2-eq. / kg Virgin 75% 1% 3% 22% 0% %

Table 20 – Average implications of lifecycle phases (modified usage phase)

Boeing’s usage emissions remain significantly higher than those of the other partners but now appear much more comparable as the only variable that remains is the emission factor of the vehicle used.

Thus it may be concluded that both the distance travelled and the emission factor of the vehicle are both highly influential in the calculated emissions of usage. The usage phase of components destined for use on aircraft is expected to radically outweigh the emissions stemming from any other phase, while the usage of parts on any other vehicles is expected to be more in line with raw material extraction emissions.

Ugaya and Walter (2004), state that their lifecycle assessment for the steel used in automobiles showed that the ‘automobile use is mainly responsible for most environmental concerns considered’. Their study, which was geared towards Brazilian conditions, found that the use of the automobile was characterised by the high amount of fuel consumed, the combustion of which is responsible for the emission of several air pollutants. They also associated automobile use with high levels of water consumption, used for cleaning and cooling, and solid residues, dues to parts exchange.

End-of-Life

Throughout this study, the burden of disposal and end-of-life processes have not emerged as a significant contributor to lifecycle CO2 emissions. The negligible emissions calculated are not however intended to imply that there are unimportant contributions at this phase but reflect the methodology behind allocating emissions; only the transport of the waste material has been accounted for.

In fact when considering the fate of large parts or systems such as vehicles, the recycling procedure can be a long and drawn out process, requiring the involvement of many actors. Dhingra et al. (1999) provide a good account of the end of life processes involved with an automobile. They elucidate that at the end of their useful lives; useable parts contained in automobiles are removed for reuse or remanufactured, whilst the hazardous materials are disposed of in appropriate manner. Remaining hulks are commonly flattened and sent to automobile shredders, who use hammer mills to break them down. Magnetic separation is used to recover most of the ferrous metals which is sent for recycling and the lightweight waste material or ‘fluff’ is removed by air cyclone separation before being land-filled. What remains is a mixture of high-density, non-magnetic material that is rich in non-ferrous

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metal. This is usually dispatched to non-ferrous metal separators, where processes such as water elutriation, eddy current separation and heavy media separation, are used to recover aluminium, zinc, copper, brass and other valuable metals. Finally, the waste material that remains, consisting of mainly dirt and fines, is land-filled.

The aerospace industry seems less developed in this field. The Aircraft Fleet Recycling Association or, AFRA (2010a) estimate that 12,000 aircraft will reach the end of their service life in the next 20 years. Even so Burchell (2006) states that up until recently most have been sent to scrap yards, some have been used for ground training and the rest have ‘been left to rot next to the runways’. But the value of recycling aircraft does appear to be increasingly understood and in order to clean up the industry major manufacturers have begun to take recycling more seriously. Boeing and Airbus have both ramped up their efforts to promote recyclability, and they have even started collaborating on efforts aimed at developing recycling methods and materials.

As discussed earlier in WP3 the majority of the emissions for this process are attributed to the production of recycled materials and in order to avoid issues with double counting are excluded from the figures calculated for end-of-life and disposal.

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Reductions

In analysing energy use and CO2 emissions, this document has reported on the environmental implications of the five lifecycle phases of a series of component parts destined for use on various aircraft and land based vehicles. In doing so it has identified some key areas which hold potential to reduce their energy intensity and carbon footprint.

Most significant is the usage burden of aerospace components. The vast distances travelled immediately shame the components in terms of the huge amounts of fuel used. Initiatives geared towards a reduction in the structural mass of transportation equipment can serve as a means of directly reducing the CO2 impacts. Manufacturers do already seek to identify new ways of reducing the mass of an aircraft, which consequently reduces fuel consumption and improves performance. For instance, large investments are made in increasing the use of materials that combine relatively low mass with the requisite strength and flexibility. The savings found in this study suggest that the substitution for lighter materials would be a successful environmental choice in aerospace and appear to justify the extra burden of manufacturing and processing materials with high embodied energy figures. Mass reductions can also arrive through redesigning the parts geometry, while retaining its properties and functionality, an improvement that may be achieved with the additively produced parts.

The distribution of the lifecycle emissions for non-air based components on the other hand, highlights primary production as the key area to tackle. Whereas it appears that weight savings can justify an increased burden of material production in aerospace, this is not necessarily the case for components destined for use on petrol or diesel engine automobiles and the choice between one material and another is an important one. It is understandable that some non-environmental characteristics make certain materials more favourable; most obviously economics is a big factor and mechanical properties also play a big role, but as is evident from Bentley’s transmission bracket, more sustainable materials can be effectively integrated into production. In the case of the transmission bracket, a zinc-aluminium alloy was used as an alternative to aluminium and radically reduced the impact of raw material production due to its lower embodied energy values. As raw material represents a significant proportion of the CO2 emissions arising from the lifecycle of a component destined for a petrol engine vehicle, it may be recommended as a particularly apt material to use. On the other hand, the zinc alloy is a denser material than the aluminium alternative and in different circumstances (aerospace) it may not have fared better.

Despite holding a smaller proportion of the overall emissions, the burden of material production remains high for aerospace components and raw material manufacture consistently emerges as a damaging source of CO2. Thus, there is potential benefit in focussing on production burdens but it is important that they do not come at the expense of mass increases with components destined for a life aboard aircraft.

Substantial reductions in production can be realised through the use of a higher proportion of recycled material. Although recycling systems can be energy intensive, recycled content often has as little as 10% of the embodied energy of virgin production. The embodied energy of recycled aluminium (S332.1: LM26-TE, cast (Al/9Si/3Cu/Mg)) is for instance just 20 MJ / kg, whilst the embodied energy of primary production is approximately 220 MJ / kg. Although the figures are more analogous with other materials, it remains clear that remarkable savings could be attained through the use of more recycled material. Insisting that a component must be primarily or exclusively made of virgin raw material can have severe repercussions on the environmental burden of raw material production.

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The British Metals Recycling Association (BMRA, 2010) assert that, of the 13 million tonnes of metal that was recycled in the UK in 2005, only 40% was used domestically and the rest was exported worldwide. They go on to suggest that, the UK produced considerably more scrap than is required in domestic markets.

However, this truth is not necessarily universal and the choice between recycled and virgin material is not always clear; it is noteworthy that the demand for aluminium is considerably higher than the volume of recycled aluminium. Kirchner (2003) remarks that, this is not attributable to the level of recycling effort and theoretically the amount of available scrap volume today remains too low to cover actual aluminium demand. The challenge therefore is through optimising the separation of different scrap types, and developing the technology available for the separation of scrap to be applied on an industrial scale.

According to Abraham (2008) there is not necessarily a shortage of dismantling points in the automotive industry either, with around 6,000 spread across Europe handling vehicles of all origins, makes and models. But given the diversity of models, techniques and technologies, it can be difficult for recyclers to standardise their practice and recycling can become drawn out and complicated. Consequently it becomes important that manufactures take this concern into account upstream of production.

Again many manufacturers already do recognise the importance of product ‘take-back’ and increasingly implement recycling considerations into their design. BMW have for some time had an objective to build their automobiles from 100% reusable or recyclable parts, and recycling was an important factor when redesigning the new MINI Cooper (Callan and Thomas, 2007). Also, Honda (2007) have developed technologies which claim to improve the ease of dismantling and dissembling, and reuse and recycling. Their approach has allowed them to reduce the quantity of parts used, increase labelling for easy recognition and phase out PVC from several components. They have also replaced virgin material with recycled plastics and use mono-materials in order to aid recycling. Renault too, claim to have ‘integrated recycling into the genes of their new models through a design for recycling approach’ (Abraham, 2008). They have created educational and design guidance tools to be used by all design engineers, making it easier for the recyclers, who may even cut along visible markings to recover and recycled material.

Driven by the ‘End-of-Life Vehicle Directive’, enacted by the European Union in 2000, most car manufacturers boast a range of techniques and initiatives from simple, common sense ideas to more ambitious solutions.

The aerospace industry can perhaps be seen as lagging behind in this area and although manufacturers are ramping up their efforts on recycling there is still work to be done. Companies such as Boeing and Airbus are beginning to work more closely in developing more sustainable end-of-life processes and this is important as, collaboration is thought to be particularly critical in meeting targets set by The Aircraft Fleet Recycling Association (AFRA), of raising the proportion of aircraft material that can be recycled from its current level of 70% to 95% by 2016 (O’Keeffe, 2009).

Specialist companies do currently dismantle and recycled some aircraft at the end of their working life but many remain ‘parked in the desert’ (Chen, 2008). Obsolete aircraft are a valuable material resource, particularly aluminium and this fact has drawn attention to the potential of sophisticated sorting methods to maximise the economic gain of using aerospace scrap in secondary production.

The potential recyclability of aircraft goes beyond just aluminium and metal as other materials can be recycled in large proportions. Using recycled or recovered carbon fibre instead of virgin fibre for instance can help reduce

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manufacturing CO2 emissions by 90-95% (AFRA, 2010b). What is more, naturally the spare parts business is already an important part to this market, especially engines, landing gear and various other pieces, such as in-flight entertainment systems and seats which sell pretty well amongst private collectors. Collecting all these elements is the first part of the recycling job. But innovation is arriving in that more uses are being found for more and more parts that can be removed (Institute of Mechanical Engineers, 2010).

It is notable that a significant driver in developing initiatives that increase proportions of recovered, reused or recycled materials has been the increasing cost of raw materials. Optimising the use of raw materials can reduce costs and secure future supplies of increasingly expensive materials (Institution of Mechanical Engineers, 2010). What is more, if goods are not ultimately recycled, its effective price is the market purchase price, whereas if goods can be recycled the effective price is purchase price less the scrap value of the goods (Palmer et al., 1996).

Another method of reducing the carbon footprint of production is by increasing the material efficiency of the processes involved. Processes that allow ‘near net shaping’ alleviate some of the dependence on raw material production and appear to benefit the environmental performance of a component over the whole lifecycle. Improving process efficiency can ease raw material production, alleviate transport costs and eliminate a large proportion of waste.

Casting emerges as a means of radically improving the material efficiency and furthermore appears to only add relatively minor CO2 burdens to the lifecycle total. In fact, the casting process generally consumes less energy to process material than machining and forging and because much of the energy is based upon the use of natural gas the consequential CO2 burden is also lower.

Despite its low emission factor, when used in large quantities, natural gas can be a significant source of CO2. Carbon capture and storage is gaining weight as a means of further negating the process emissions of coal and gas fired power generators, LNG plants and gas processing facilities. This procedure effectively captures the CO2 from the major emissions sources, before transporting them to a location where they can be injected into formations deep underground (depleted gas fields, rock formations etc.). Should CCS technology be installed at a metals production or processing facility, the CO2 captured from either the combustion or the process can be deducted from emissions calculations (IPCC Guidelines, 2006a). Although developing rapidly, much of the focus has been placed on the capture element of this process and it would benefit from further research into the development of suitable storage reservoirs.

CCS technology is best focussed on concentrated CO2 sources, as the energy required and the size of the equipment, increase rapidly against the inverse of concentration. The ‘best’ sources for capture are those where the concentration, the flow-rate and the industrial environment justify large investments and the additional energy requirements of the CCS process. The largest commercial facilities of CCS, associated with natural gas processing, are presently of the order of 1 Mt CO2 / annum, comparable to that of a gas fired power plant with a 300 MW electric power rating (Tondeur, 2009). Consequently, centralised manufacturing systems may be recommended if high capacity can be achieved, although the additional transport and distribution emissions must be considered.

Other processes, such as machining, are more reliant on electricity and would heavily benefit from favourable electricity sources. Where large amounts of material are machined it may even be beneficial to transport the components to factories located at sites with a better energy mix. Clearly, the difference between the locations’ electricity emission factor, the distance between the sites and the transport used will also influence this decision.

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Unfortunately, it is expected that the process emissions have however been significantly underestimated in this study and without further investigation it is difficult to truly understand whether material savings warrant the addition of casting to the process.

If as suspected process emissions are actually higher than has been stated in this report, then remanufacturing may be introduced as an important consideration, which can result in significant reductions in CO2 emissions and potential energy savings of 85% (Steinhilper, 2006).

As with recycling though, in order to realise its full societal benefits, remanufacturing needs to become an integral part of the product development process. But due to a lack of OEM engagement in remanufacture and awareness of ‘eco-design’, there is currently little or no design for remanufacturer being practiced (Gray, 2006). Indeed, remanufacturing is not a technique applied in the supply chain of any of the components considering in this study,

When used effectively remanufacturing can result in great savings, but it is not a new innovation. Caterpillar Inc. started remanufacturing diesel engines in 1972, because it made ‘good business sense’ (Stahel, 1995). Remanufacturing allows the extension of a components life, through a process that restores used parts to an ‘as good as new’ condition in which they can be used again. Effectively remanufacturing is part of an ‘economy in loops’, which includes an extended producer responsibility from ‘cradle-back-to-cradle’ (Stahel, 1995), obviating the need to produce another part and all the processes it encompasses. Legislation is again arriving, making manufacturers more responsible for the waste resulting from their products in such forms as extended producer responsibly and the take-back obligation.

Design for remanufacture is not an easy process, as parts may effectively have to work with many generations and models of products and production is often quite labour intensive (Koetz, 2004). What is more, design and durability improvements must avoid adding mass, which this report suggests would increase overall emissions more than potential process savings.

Despite being outweighed by the enormous contributions of the raw material manufacture and usage phases of the lifecycle, transportation and distribution emissions remain significant in the context of the an ordinary product, as most of the components considered here travel thousands of miles before even being processed in the final assembly.

The issue is not simply put down to the ‘product miles’ travelled and in some cases a distributed supply chain can benefit the lifecycle emissions. Instead, the first port of call in reducing the carbon footprint of this phase is in choosing between the available transportation vehicles. The emission factors of aircraft are so high that this form of transport should be avoided if at all possible. While it is understandable that companies want to shorten delivery times and improve cash flow et cetera, if an economic cost could be put on the amount of CO2 emitted then it would likely outweigh any cash flow benefit.

The contribution of the freight sector to global warming has so far received less attention than that of car traffic and aviation. But efforts are being made in this area and sustainable fleet management is increasingly utilised as an efficient and economic initiative. McKinnon (2007) believes the freight sector holds great potential for environmental improvements, after investigating the benefits of numerous proposals.

In his study, McKinnon (2007) prophesises about a potential reduction in CO2, stemming from various changes to the freight system in a hypothetical scenario that he suggests could be achieved by 2015. Using a base year of

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2004, the scenario allows for a 7% increase in tonne.km but no further growth in heavy lorry traffic. Instead, the number of van delivery operations would increase and there would be greater reliance on rail freight, which would rise by 30% (in line with the recent forecasts by Network Rail). The scenario also sees significant improvements being made to vehicle utilisation and fuel efficiency, with a switch being made to the use of bio-fuels in HGVs and vans, which is proposed to cut CO2 emission factors by 10% and 20% respectively. It is suggested that, achieving such aspirations could potentially reduce the CO2 burden of freight transport by 72% (McKinnon, 2007).

Many of the measures can effectively be categorised at four different levels of efficiency; logistics, vehicle, driver, route (Léonardi and Baumgartner, 2004). Logistic efficiencies aim at increasing load factors, optimising vehicle selection, and developing entire transport chains. Vehicle efficiencies are more concerned with vehicle design and technology and fuel consumption rates. Driver efficiency targets improving fuel use by improving driving behaviour through training and assistance. Finally, routing efficiency seeks to optimise routing through developing information systems on itinerary, road conditions and traffic.

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Limitations and key assumptions

This study set out with the intention of investigating the primary processes of a series of components and identifying CO2 hotspots within the supply chains. In doing so it has endeavoured to explore the five phases of a product lifecycle; namely raw material production, processing, distribution and transportation, use and end-of-life.

A methodology was put in place to logically investigate each of the components across their lifecycle and produce results which could be contrasted and compared against each other across the same set of conditions. As a result, recommendations have been presented with the intention of reducing the carbon footprint of the whole process.

The focus of the study is on individual components, and is geared around the premise of replacing one component with another. Alternative component scenarios are intended to fulfil an equal usage function, and therefore are not considered to have influence on any other parts. This allows for the boundaries to enclose only the individual component, making comparisons easier and more valuable.

Some system considerations have been mentioned and it is likely that more radical changes to system design would have greater implications on the lifecycle emissions. This may even influence vehicles’ ‘emission factors’, which are not intended to remain as static constants. Developing new sources of fuel for instance can have great implications for the sustainability of transport.

It should be noted that the findings of the study are only intended to give a high level overview of the components as a whole and are not intended to present a full lifecycle assessment for each of the potential scenarios. As such many secondary and auxiliary processes have not been investigated in this study; it is unknown whether these would make substantial contributions to the total emissions.

CO2-eq. and energy use are the primary units investigated and reported upon. This is believed to reflect the level of corporate and consumer understanding and is influenced by the availability of data on this issue. Implications on raw material requirements are also discussed. The importance of other factors should be noted, other BREW matrices such as business issues, water consumption and hazardous waste are not discussed in this section.

CO2 figures have been derived from a variety of sources, and in some cases many assumptions have been imposed upon the calculation methodology. All assumptions are intended to provide a best estimate of what happens in reality or what may happen hypothetically, and have been discussed throughout this report. Due to the data limitations of the supply chain, which can be spread over many countries and stakeholders, the assumptions are considered sufficient for the purposes of the study.

The process CO2 emissions are derived from the embodied energy figures of a process. Depending upon the process evaluated, these values are based on the energy required to heat up the base material to its processing temperature, the energy required to heat up and maintain the equipment at its operating temperature and the energy required to deform the material at the processing temperature.

The quoted values are intended to represent the energy consumed by the local material processing operation, including the energy required to operate processing equipment and of the facility, such as lighting, heating, cooling, ventilation, compressors, water pumps and so forth. The figures do not include ‘tacit energy’ associated with the generation and supply of energy to the processing plant.

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Processing energy requirements are sourced on a mass basis (MJ / kg), and consequently small mass reductions result in small energy requirements. While this is likely to be true in the most part, it does not reflect the start-up, idling or non-mass related activities. In all cases the energy associated with operations represent high volume production and utilisation. It is hoped that energy monitoring studies conducted by Loughborough University, Alcon and Boeing will determine whether or not mass is the primary indicator for energy intensity or whether other factors need to be considered.

All emission factors have been sourced from reputable sources and are referenced throughout this report. Electricity is the only energy source that is given a location specific emission factor, as considerable differences in the energy mix of the electricity generation can result in vastly different rates of CO2 production. Although the actors may source their electricity from a range of providers and may in some case generate electricity in-house, no data has been sourced on this area and it has not been reported upon. All other energy sources have been given an emission factor that represents all areas of the world. As location plays a minor role in their generation and use, this is considered appropriate for the purposes of this study.

Going forward, for non-CO2 emissions in particular, there can often be a high degree of uncertainty associated with generalised emission factors being applied to individual countries. Generally speaking, country specific emission factors can provide more accurate estimates and it is often recommended that if an activity is a ‘major source of emissions in a country’ then it is good practice to use a country specific emission factor. Although it is preferable to use emission factors that reflect national circumstances, emission factor development is expensive and time consuming and goes beyond the requirements of this overview.

In considering distribution emissions, this study has not considered production rates, production programmes or stock holding implications. It has allocated a kilogram of material (raw material, processed component) a kilogram of transport burden for the routed journeys at average rates. In reality, where supply chain efficiency is not maximised and vehicles run at less than full capacity, material should be assigned a larger portion of the vehicle mass and vice versa for highly efficient supply chains. The distribution specific vehicle emission factors are expected to negate some of the issues with this issue, as they take into account an assumed vehicle utilisation capacity. However, fuel consumption rates are very sensitive and depend on vehicle load factors, particularly in the case of road transport (McKinnon, 2007).

Moreover, the study investigates only the journey from the origin location to the destination location. Although this may take into account indirect routes, through ports / airports et cetera, it does not consider the return journey of the vehicle. In circumstances where throughput and utilisation rates are relatively small, return journey loading can be low. Therefore a portion of the burden of this journey should be attributed to the initial component. It has not been possible to source information on this area but as all of the suppliers are expected to be reasonably large, the return journeys are also assumed to be run at maximum capacity.

In future, it may be suggested that the efficiency of vehicle usage could also be reported on, by acknowledging the burden of the vehicle empty weight and the distance travelled whilst empty. Léonardi and Baumgartner (2004) propose combining a mass kilometre variable to the existing tonne kilometre. They measure vehicle efficiency (Evu) as equal to t.km / m.km where m = freight mass (payload) + the weight of the empty vehicle. The value of Evu is intended to indicate how much more physical transport capacity was actually carried out in addition to the t.km value.

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The components have been considered as following an established and agreed course of action, alleviating any need for lengthy storage requirements or retail periods. As such, no warehousing or stock holding factors have been investigated. Again it is unknown whether or not these factors would contribute significantly to the overall total.

As discussed in the methodology, waste material has only been attributed the CO2 burdens of the transport needed to move the mass to a local waste disposal site. As such the calculations are expected to underestimate the true emissions of waste material. It is true that most waste metal is eventually recycled, even if the disposal method is not designed for recycling specifically. What is more, any metal that does end up in land fill will result in insignificant levels of carbon emissions. However, this does not take into account the sorting and processing of waste at disposal facilities. Although it is anticipated that this may be quite energy intensive, most of the energy is expected to come from labouring activities and as such any additional contribution is expected to be small.

Many of the extra additions mentioned in this sections can in themselves be seen as relatively minor or inconsequential, but together can tally to total non-trivial amounts. Other omissions are unknown for their severity and until further research can be conducted, their impact on the lifecycle emissions of the components discussed will remain unexplored.

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Palmer, K. Sigman, H. and Walls, M. (1996), The Cost of Reducing Municipal Solid Waste, Resources for the future, Discussion paper 96 – 35

Stahel, W. R. (1995), Caterpillar Remanufactured Products Group, The Geneva Environment Meetings, found at http://www.product-life.org/en/archive/case-studies/caterpillar-remanufactured-products-group, last accessed 01/10/10

Steinhilper, R. (2006) interview by Gray, C. (2006), Remanufacturing and Product Design, Wax RDC ltd, found at http://www.cfsd.org.uk/events/tspd12/abstracts/Gray_abstract.pdf, last accessed 01/10/10

Tondeur, D. (2009), Carbon Capture and Storage (CCS), SciTopics, found at http://www.scitopics.com/Carbon_Capture_and_Storage_CCS.html, last accessed 04/10/10

Ugaya, C. M. L. and Walter, A. C. S. (2004), Life Cycle Inventory Analysis - A Case Study of Steel Used in Brazilian Automobiles, International Journal of Life Cycle Assessment, Volume 6, pp. 365 – 370

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WP3.3 – Roadmap for Distributed AM & WP4 – Digital Distributed Supply Chain Configuration

Introduction

This section is intended to explain the key aspects of the potential additive supply chains and lists the main assumptions that have been used in this study. This report is designed to aid the reader in understanding the methodology behind the findings highlighted in Atkins.

This study has adopted a collaborative approach in prophesising how possible additive supply chains may look. The findings are anticipated to provide the basis of establishing a detailed depiction of the potential additive supply chain steps associated with the series of component parts identified by the Atkins partnership.

Material Selection

All of the parts selected for Atkins (WP1) were chosen because of the potential for additive layer manufacturing (ALM) production methods to reduce the emissions that they create during their lifecycle. There are many ways in which these saving may come about, especially following a ‘redesign’ of the parts. Among other benefits, ALM can result in much lighter weight components and provides the possibility to use less energy intensive materials whilst retaining strength characteristics and material properties.

For a number of the parts, there is potential for the parts to be manufacturing using a range of different materials, namely aluminium, titanium and stainless steel, and potential polyamide (PA) and acrylonitrile butadiene styrene (ABS). Different levels of optimisation can be used depending on the material used, as each material holds different strength qualities and will be able to withstand different loads. Therefore, each of the load bearing parts may be presented using a number of geometries and materials.

The materials used in additive processes are based on existing materials that have been used for traditional processes. Therefore, the ‘additive materials’ used have each been aligned to a traditional counterpart and as such are assumed to require the same amount of energy in production and traditional processing. The materials have been aligned in the following way;

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Material class Material grade Additive material

A413.2: LM6 - M, cast (Al-12Si) MTT Technologies Group, (Al-Si12) Aluminium A356.0 (a): LM25-M, cast (Al/7Si/Mg) EOS, Aluminium (Al-10Si-Mg) Cobalt Superalloy, CCM, wrought, annealed (high carbon) Arcam, ASTM F75 CoCr alloy EOS, Stainless Steel PH1 EOS, Stainless Steel GP1 Stainless steel AISI 316L, wrought, austenitic CONCEPT Laser GmbH, LaserCUSING CL 20ES ProMetal, an Ex One Company, S3 MTT Technologies Group, Titanium, Ti-6Al-4V Titanium Alpha-beta alloy, Ti-6Al-4V, cast EOS, Titanium, Ti-6Al-4V Arcam, Titanium, Ti-6Al-4V ABS ABS, Unfilled, injection moulding, plateable Stratasys, ABS PA, Type 11, unfilled EOS, PrimePart® PA PA, Type 12, unfilled 3D Systems, DuraForm® PA PA, Type 12, unfilled EOS, PA2200

In terms of the specific grades chosen, the materials used to manufacture the ‘additive’ components do not compare exactly with the materials used to manufacture the ‘traditional’ components. This is due to limitations in sourcing powder, but it is anticipated that the energy requirements of producing similar materials will be closely related.

Processes

The parts will be produced using a series of ALM processes. The particular process chosen will depend on the properties required in the final part and the geometry of the redesign.

The processes consist of;

Direct Metal Laser Sintering (DMLS) - EOS Electron Beam Melting (EBM) - Arcam Fused Deposition Modelling (FDM) - Stratasys Selective Laser Sintering (SLS) - EOS Selective Laser Melting (SLM) – MTT / Renishaw

Energy monitoring tests conducted during this project by Loughborough University have been used to investigate the energy intensity of each process and assign a quantity of electricity (kWh) to the parts per unit mass (kg) of material processed.

All energy figures used for the additive processes during this investigation have been supplied by Loughborough University.

No one ALM technology is capable of processing the full range of materials; instead certain processes lend themselves to manufacturing particular materials. The range of processes being considered and the materials appropriate for each process are listed below;

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Process Vendor Material class Material

Aluminium EOS, Aluminium (Al-10Si-Mg) EOS, Stainless Steel PH1 DMLS EOS Stainless Steel EOS, Stainless Steel GP1 Titanium EOS, Titanium, Ti-6Al-4V Titanium Arcam, Titanium, Ti-6Al-4V EBM Arcam Cobalt Arcam, ASTM F75 CoCr alloy FDM Stratasys ABS Stratasys, ABS Aluminium MTT Technologies Group, Al Si 12 CONCEPT Laser GmbH, LaserCUSING CL 20ES SLM MTT Stainless Steel ProMetal, an Ex One Company, S3 Titanium MTT Technologies Group, Titanium, Ti-6Al-4V Polyamide 3D Systems, DuraForm® PA 3D Systems SLS Type 11 – EOS, PrimePart®? EOS Polyamide / Type 12 – EOS, PA2200?

Material Preparation

The materials listed are not typically produced in a state appropriate for the ALM to take place and therefore some form of preliminary preparation process has to be conducted that converts the materials into a condition that is ready to be fed into the ALM machine. Each particular application requires a specific material form; among other criteria, the particular preparation process that will be conducted will depend on both the material used and the ALM process. In some circumstance there may be multiple preparations options that are suitable.

Material Material Additive material class Preparation MTT Technologies Group, (Al-Si12) Aluminium Atomisation EOS, Aluminium (Al-10Si-Mg) Cobalt Arcam, ASTM F75 CoCr alloy Atomisation EOS, Stainless Steel PH1 EOS, Stainless Steel GP1 Stainless steel Gas atomisation CONCEPT Laser GmbH, LaserCUSING CL 20ES ProMetal, an Ex One Company, S3 MTT Technologies Group, Titanium, Ti-6Al-4V Titanium EOS, Titanium, Ti-6Al-4V Plasma atomisation Arcam, Titanium, Ti-6Al-4V ABS Stratasys, ABS Extrusion EOS, PrimePart® PA 3D Systems, DuraForm® PA Grinding EOS, PA2200

Assumptions made for material preparation processes are independent of the geometries made in Atkins. They will vary with the material and the process only.

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Metal powder forming

All of the metal based ALM processes considered here require the material to be prepared into a powder form. Powder metallurgy covers a broad spectrum of manufacturing processes and includes both mechanical methods and chemical / electrochemical methods of producing various metal powders. The powders that are produced usually have to meet specific quality criteria, including;

spherical shape; high cleanliness; rapid solidification; and homogeneous microstructure.

Any fusible material can be atomised through several techniques which allow considerable control over the size ranges of the grain populations at large production rates.

Reference: Colton (2009)

Atomisation is the dominant method for producing metal and pre-alloyed powders from iron, steel, stainless steel, tool steel, super alloy, titanium alloy, aluminium and brass. This is primarily because pre-alloyed powders can only be produced by atomisation and because high production rates favour economy of scale (EPRI, 2000).

Atomisation is defined as the process of disintegrating liquid metal into fine droplets, which are simultaneously cooled down and solidified to form metal powders. To break up the liquid metal into droplets, there must be a force exerting to a liquid metal. The force can be in the form of atomising media impingement, centrifugal force or liquid metal explosion.

Following the atomisation process, there will often be fractions of oversized and undersize granules that remain after the required size fractions have been extracted for the customer. In most circumstances, it is possible to recycle the remnant although in the case of more reactive materials such as aluminium and titanium it is not. The result is that more material has to be produced to account for the losses of the process. On the other hand, aluminium remnant that cannot be recycled back into the process can be sold on for other applications such as paint / pigments (fines) and the chemical welding industry (oversize). For titanium likewise, it is probable that the atomiser will be able to sell other parts of the size distribution elsewhere even if it only goes into the metallurgical industry for making alloying additions (Kearns, 2010).

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For the purposed of this study, the atomisation process cannot be broken down into sub-processes resulting in discrete outputs, nor can system expansion be applied as no single displaced product can be identified for the co- products. Despite being sold on, the primary driver for the production is to create the required size fraction used by the original customer.

It could be conservatively suggested that for the more reactive materials (aluminium and titanium) the yield can be as low as 60%, effectively requiring 1.67 times the required material to be produced. Of this it is assumed that 80% of the value can be assigned to the desired fraction. Less reactive materials (stainless steel) go through a more efficient process. For these it is assumed 80% of the yield is suitable and 90% will be allocated for the additive process.

As a result, this study will suppose the following:

Yield of suitable Allocated to Multiplier for material Material fraction atomisation requirement Aluminium 60% 80% 1.33 Stainless steel 80% 90% 1.13 Titanium 60% 80% 1.33

The electrochemical process of atomisation is assumed to be equal to that of the more general metal powder forming, in terms of the amount of energy needed by the process. This energy is believed to be entirely electrical.

Blending regularly occurs following the powder forming process. This is where fractions of different materials are brought together to form a mix. Energy used during this process is assumed to be non-critical and has not been investigated.

Atomisation can be classified into a number of different techniques including two-fluid atomisation, centrifugal atomisation and vacuum atomisation. Currently, this study does not differentiate between the different atomisation techniques.

Polymer powder forming

Polymer is normally produced in the form of small pellets. This form lends itself particularly well to injection moulding processes. However, the pellets are too large to be fed directly into SLS machines and the pellets have to be reduced in size to powder form, as with the metallic materials.

However, unlike the chemical atomisation process used to form metal powder, polymer powder is formed through the mechanical process of grinding. At this moment no data has been sourced for this process and the energy required to grind lead (commercial purity, corroding), a relatively soft metal, has been used in its place. This pre- process technique is used to prepare material used in selective laser sintering processes.

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Reference: Colton, (2009)

Polymer powder production includes the preparation of individual powders as well as the mixing and dispersion of appropriate powder constituents. The particle size, shape, size distribution and bulk density of the powder and flow of powdered materials must be matched to the capabilities of the SLS machine as well as the infiltration steps that follow.

The approach of this study is to consider that the grinding process is has a material efficiency of 90.9%, i.e. 10% more material is produced and process to fulfil customer requirements. Although, fractions of the ground polymer are expected to be small, it is assumed that any remaining material cannot be recycled or be sold on with an economic value.

Yield of suitable Allocated to Multiplier for material Material fraction atomisation requirement Polyamide / Nylon (PA) 91% 100% 1.10

Extrusion

Fused deposition modelling is a process that is being considered that does not require the material to be formed into powder. Instead the Acrylonitrile butadiene styrene polymer (ABS) is extruded into a filament or wire.

The performance of an extruder is determined in equal parts by the machine and the characteristics of the feedstock. Feedstock properties that affect the extrusion process include bulk properties (e.g. density, compressibility, particle size and shape), melt flow properties (e.g. shear, elongation viscosity) and thermal properties (e.g. specific heat, transition temperatures, melt temperatures, latent heat of fusion, thermal conductivity).

The approach of this study is to consider that the extrusion process has a 100% material efficiency, any waste streams are assumed to be negligible.

Yield of suitable Multiplier for material Material Allocated to extrusion fraction requirement ABS 100% 100% 1.0

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Support Structure

A drawback to many ALM process is in varying degrees, an inability to produce geometry in free space without a ‘supporting layer’ or structure. Overhanging portions cannot be produced, freely suspended in space where there is no part of the object in direct contact with the other facets in the final geometry of the object. Therefore, support structure has to be formed by depositing material under the ultimately suspended portions of the object.

Parts with undercuts can be manufactured without a support structure so long as the angle between the vertical axis and the surface of the undercut is less that a certain point (approximately 45°). If the angle exceeds this point the overhanging features have to be fixed by a support structure to avoid or minimise distortion during the building process.

The accuracy of the more severe overhangs depends on the position and shape of the support structure. In this respect the choice of support structure is an important one and parts that encompass a range of different features may require a series of support types to fulfil their production requirements. Typical support types include;

block supports; line supports; point supports; gusset supports; web supports

Each type of support uses a different ratio of material to fill the void between the overhanging features of the part and either the up facing features below or the platform at the bottom of the build chamber.

The amount of support needed will therefore depend on the orientation of the build and parts do have to be designed with the consideration of support structure placement during the build.

It should be noted that, support structures are also used to anchor the part to the build platform during the build process and as well as enabling the production of over-hanging features.

A level of support will be included for all the additively produced components. These figures will be determined by a combination of real part builds and estimations made by Econolyst / enlighten / Loughborough University

Of the processes considered in this study, selective laser sintering (SLS) is the exception to the constraints of support structure, as the part rests on and within the non-sintered powder.

Control Parameters

Packing Efficiency & Orientation

A number of ALM components are often built in the same build chamber in an attempt to fill the largest work area possible and maximise the space available. As the preparation time and material deposited on each layer is relatively constant regardless of the number of parts being built and the area of the work bed used, this helps to improve the economic and time efficiency of the processes (Choi and Samavedam, 2002). Designers therefore

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regularly have to consider how best to arrange multiple parts in a single build. This can lead to stacking one part above another or rotating orientations to a better fit a space occupied by an array of parts.

However, utilisation of the maximum is not always feasible or even possible. Some circumstances make packing on the z-axis (vertical) unworkable, batch sizes requirements can be low, or there may be CAD / software memory limitations that hamper the slicing of a large number of STL files.

Altering the orientation of the parts will also have an effect on other aspects of the build, for instance, a rectangular box orientated at 0° or 90° will occupy less space, stand at a lower height (z-axis) and require less support structure than one orientated at 45°.

In some circumstances the designer will have to deal with a trade-off between apparently conflicting advantages. For example, on the one hand, a part orientated with the intention of minimising the height in the z-axis will result in fewer slices and hence a reduction in build time (as long as layer thickness and scan speeds remain constant). On the other hand, this may take up more space in the xy-axis leading to a poorer packing rate.

Similarly, rotating a part may result in a better packing efficiency but it can also lead to more overhanging features each requiring additional support structure.

Packing efficiency and optimisation has been considering in the work done by Loughborough University and the energy figures for the ALM process are thought to reflect parts built under average conditions.

Post-Processing

Parts produced using ALM technologies have traditionally failed to achieve the material / mechanical properties of their moulded or machined counterparts. In this respect, there have been issues with accuracy, detail and surface finish, although since receiving more widespread research these issues have witnessed significant improvements (Hopkinson and Dickens, 2003). The technology has been developed and setting certain process parameters can result in low surface roughness, whilst others can take advantage of simple surface treatments after use. Indeed, laser melting technologies have progressed, driven by the need to produce near fully dense objects, with more comparable mechanical properties to those of bulk materials, and the desire to avoid lengthy post-processing cycles (Kruth et al., 2005).

Nevertheless, to counteract some of the shortfalls, especially where aesthetic appearance is important, post processing is still regularly used. Not only can this extend the cost and the time of the build, but post processes also require energy and can offset some of the other benefits of ALM.

The level of post-processing performed on each of the parts will vary depending on the use for which they are intended. For many non-visible components, under-the-bonnet parts for instance, surface finish is less of an issue. Likewise, non-load bearing parts may not require any heat treatments as the material properties following the ALM process may be sufficient.

For parts build with support, this must be removed and as a general rule bead blasting may be used to procure a better surface. Post heat treatments or hot isostatic pressing may be used to increase the mechanical properties of

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the materials (Kong, 2010). As each of the parts has its own strengths and weaknesses, post processing requirements will be decided on a case-by-case basis.

As of yet no data has been sourced on the bead blasting, heat treatment or HIPping processes.

Support Removal

Once a build is completed, support structure is typically removed manually. Distortion can be avoided during this process by the stiffness of the part itself. Manual support removal is not attributed any energy or CO2 footprint in this study. Some aspects of this process will have an impact but this is expected to be negligible. For instance, the technicians will use pliers / cutters to remove the support, but the same tools are used for a large amount of material removal and considering these aspects is beyond the purposes of this study.

Small levels of machining may be used on certain regions. Figures that correspond to dressing / finishing will be used to approximate the energy requirements for these processes. Although these processes seem particularly energy intensive when considering them / kg of material removed, the main focus of this type of machining is not material removal and the figures are only applied to a minor amount of material.

As well as the removal of support, parts produced using metallic ALM processes have to be removed from the bed of the chamber. This is

In the case of the metallic processes, waste material is assumed to be treated as scrap and recycled. Polymer waste on the other hand is assumed to be discarded as commercial waste.

Logistic Factors

The partners involved in this project all have a varying degree of existing involvement with AM processes. Some have almost no experience with additive parts, whereas others already produce working parts that can be used on commercial vehicles. None however have established supply chains that are capable of producing large quantities of additively manufactured parts and therefore the mapping of the logistical structures in supply chains is hypothetical.

Therefore, research has been conducted as part of this project that has attempted to position processes in practical locations that could likely reflect potential additive supply chains.

The location of raw material extraction and production is not likely to change as a result of the shift towards additive supply chains. Hence, this is taken either to match that of the traditional supply chains for similar materials or as a location deemed a major producer of the respective material. As with the traditional supply chains, it is likely that recycled content can be sourced from suppliers much closer to point of process.

Though not hugely common, atomisation facilities are not exactly rare and can be found throughout developed manufacturing nations in Europe and North America. Facilities generally produced a range of similar materials. For instance, some suppliers will specialise on steels whereas other will focus on more reactive metals such as aluminium and titanium.

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It is expected that the powders used for the metallic ALM processes could be sourced from an appropriate atomiser without having to add massive transport distances to the supply chains. A few large atomising facilities have been assigned to this process in the additive supply chains.

One of the early suggestions of this project was the potential to locate additive processes themselves proximate to the final assembly point. The rationale was that this would cut transportation burdens and allow parts to be produced as and when needed.

However, the results of the investigations conducted so far have deemed transportation burdens to be of minor importance to lifecycle footprints. Machine utilisation and packing efficiencies have been found to be much more important and therefore centralised production facilities remain necessary in additive supply chains.

Even so, in the hypothetical situation that additively produced parts could replace their traditional counterparts, production quantities are such that it is expected that each of the partners would be able to meet high utilisation in-house if required. The ALM processes have either been located near current facilities or at large third party facilities.

All other locations are not expected to be affected by a hypothesised move to additive supply chains. Auxiliary and assembly operation will still be conducted at existing locations.

The vehicles used for transportation similarly are not expected to change. The same assumptions are made regarding loading scenarios and return journeys and the same factors are used for calculate CO2 emissions.

Usage

All the parts that have been considered during this project have been redesigned with the intention of directly replacing traditional parts with additive alternatives. In this respect, the additively produced parts fulfil the exact same function as the traditional part during usage.

At the moment it is not possible to assess the advantages or disadvantages of the two considered supply chains in respect to maintenance and repair because the expenditure of repair typically depends on the extent and place of the damages in each case. In general redesigned parts are not anticipated to need any more maintenance nor are they anticipated to need replacing any more or less often.

The only difference that is considered is the fuel savings that are expected as a consequence of the reductions in part weight. These are accounted for by using emission factors that are relevant to the mass as well as the distance of transportation.

End of Life

End of life considerations are treated in the same as with the traditional supply chains, any changes that may come about from a movement to additive supply chains has not been considered.

It is possible that in reality, design changes could result in the part becoming more or less easy to disassemble, reuse, recycle or remanufacture.

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References

Choi, S. H. and Samavedam S. (2002), Modelling and Optimisation of Rapid Prototyping, Computer in Industry, Volume 47, pp. 39-53

Colton, J. S. (2009), Metal Powder Processing, Manufacturing Processes and Engineering, Georgia Institute of Technology

Electric Power Research Institute (2000), Metal Powder, Industry Segment Profile, EPRI Centre for Materials Production

Kearns, M. (2010), Personal communications, Powder Group Director, Sandvik Osprey Limited

Hopkinson, N. and Dickens, P. (2003), Analysis of Rapid Manufacturing – using layer manufacturing processes for production, Journal Mechanical Engineering Science, Vol. 217, Part C, Proc. Institution Mechanical Engineers

Kruth, J. P., Mercelis, P., Froyen, L., Rombouts, M. (2005), Binding Mechanisms in Selective Laser Sintering and Selective Laser Melting, Rapid Prototyping Journal, Vol. 11, Number 1, pp. 26–36 http://www.niro.com/polymer-powder.html

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AM Supply Chain Analysis of Additive Bentley Components

Part: Transmission Mount Bracket

Materials Aluminium: 6082, wrought, T6 Size (bounding box) 24 x 21 x 62 mm Weight of final part 0.59 kg Volume of final part 218.91 cm3 Redesign process Topological optimisation Component image

Additional material requirements:

Production stage Mass Assumption (kg) Final part mass 0.59 Additional material removed during finishing + 2% Removed through dressing processes 0.60 Additional material needed for support + 21% Removed manually 0.73 Additional material needed to account for SLM losses + 5% 0.77 Additional material needed for atomisation losses + 33% Raw material requirements 1.02

Supply Chain Data

Item Assumption Reasoning Recycled content Industry standard Matched with processes in traditional supply chain

Supply chain stage Assumed location Reasoning Raw material extraction / production India Atomisation Germany Matched with processes in Selective Laser Melting Germany traditional supply chain Finishing machining Germany

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Supply Chain Analysis of Additive Boeing Components

Part: Eggcrate Clip

Materials Titanium: Alpha-beta alloy, Ti-6Al-4V, cast Size (bounding box) 11.8 x 12.5 x 36.5 mm Weight of final part 0.15 kg Volume of final part 33.36 cm3 Redesign process Topological optimisation Component image

Additional material requirements:

Production stage Mass Assumption (kg) Final part mass 0.15 0.5 mm removed from flat side Additional material removed during finishing + 1.28 cm3 through dressing processes 0.153 Additional material needed for support + 10% Removed manually 0.17 Additional material needed to account for SLM losses + 5% 0.18 Additional material needed for atomisation losses + 33% Raw material requirements 0.24

Supply Chain Data

Item Assumption Reasoning Recycled content 100% Virgin content Partner questionnaire

Supply chain stage Assumed location Reasoning Raw material extraction / production Japan Atomisation USA (Ohio) Matched with processes in Selective Laser Melting Italy traditional supply chain Finishing machining Italy

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Supply Chain Analysis of Additive Delphi Components

Part: Pump Housing

Materials Aluminium: 6082, wrought, T6 Size (bounding box) 12.9 x 12.1 x 7.9 mm Weight of final part 0.38 kg Volume of final part 135.80 cm3 Redesign process Topological optimisation Component image

Additional material requirements:

Production stage Mass Assumption (kg) Final part mass 0.38 Removed to smooth holes by dressing Additional material removed during finishing + 1% processes 0.38 Additional material needed for support + 10% Removed manually 0.42 Additional material needed to account for SLM losses + 5% 0.44 Additional material needed for atomisation losses + 33% Raw material requirements 0.59

Supply Chain Data

Item Assumption Reasoning Recycled content Industry standard Partner questionnaire

Supply chain stage Assumed location Reasoning Raw material extraction / production Australia Major producer of aluminium Atomisation United Kingdom Matched with processing in Selective Laser Melting United Kingdom traditional supply chain Finishing machining United Kingdom

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Supply Chain Analysis of Additive Virgin Components

Part: Upper Class Monitor Arm

Optimised for 150 lb Loading Optimised for 300 lb Loading Materials Aluminium: A356.0 (a): LM25-M, cast Aluminium: A356.0 (a): LM25-M, cast (Al/7Si/Mg) (Al/7Si/Mg) Size (bounding box) 9.2 x 30.3 x 4.0 mm 9.2 x 30.3 x 4.0 mm Weight of final part 0.34 kg 0.52 kg Volume of final part 120.71 cm3 186.77 cm3 Redesign process Topological optimisation Topological optimisation Component image

Additional material requirements:

Production stage Mass for 150 lb Mass for 300 lb (kg) (kg) Final part mass 0.34 0.52 Additional material removed during finishing + 0% + 0% 0.34 0.52 Additional material needed for support + 0% + 0% 0.34 0.52 Additional material needed to account for SLM losses + 10% + 10% 0.35 0.55 Additional material needed for atomisation losses + 33% + 33% Raw material requirements 0.47 0.73

Supply Chain Data

Item Assumption Reasoning Matched with supply chain of Recycled content Virgin content other components

Supply chain stage Assumed location Reasoning Raw material extraction / production India Atomisation United Kingdom Matched with supply chain of Selective Laser Melting United Kingdom other components Finishing machining United Kingdom

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Findings

This section will endeavour to provide an estimated of the CO2 footprint of the redesigned additive components.

As with the traditional supply chains, the footprinting process predominantly considers the primary processing activities conducted in the supply chain and excludes the majority of the supportive and auxiliary processes, which may or may not add significant CO2 contributions to the supply chain.

Energy values are also reported in this section.

Results tables

A series of results tables are presented, as follows;

Table 21 – Additive Components assessed

Table 22 – Additive footprints per component

Table 23 – Additive footprints per kg

Table 24 – Additive % by life cycle stage

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Raw material Raw material Material Company Part Final part mass location mass efficiency kg kg % Bentley Transmission Mount Bracket India 1.0 0.59 58% Boeing Eggcrate Clip Japan 0.2 0.15 63% Delphi Pump Housing Australia 0.6 0.38 64% Virgin Upper Class Monitor Arm (150 lb) India 0.5 0.34 71% Virgin Upper Class Monitor Arm (300 lb) India 0.7 0.52 71%

Table 21 – Additive Components assessed

Raw Company Part Process Transport Usage Disposal Total Material

(kg CO2-eq.) Bentley Transmission Mount Bracket 45 15 2 92 0 180 Boeing Eggcrate Clip 16 4 2 9,674 0 9,699 Delphi Pump Housing 21 10 1 72 0 117 Virgin Upper Class Monitor Arm (150 lb) 36 8 2 22,046 0 22,091 Virgin Upper Class Monitor Arm (300 lb) 5 12 4 34,108 0 34,178

Table 22 – Additive footprints per component

Final part Raw Company Part Process Transport Usage Disposal Total mass Material

kg (kg CO2-eq. / kg) Bentley Transmission Mount Bracket 0.59 75 26 3 156 0 304 Boeing Eggcrate Clip 0.15 108 27 16 65,458 0 65,629 Delphi Pump Housing 0.38 54 26 3 191 0 310 Virgin Upper Class Monitor Arm (150 lb) 0.34 106 23 6 65,458 0 65,592 Virgin Upper Class Monitor Arm (300 lb) 0.52 106 23 7 65,458 0 65,592

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Table 23 – Additive footprints per kg

Raw Company Part Process Transport Usage Disposal Material % Bentley Transmission Mount Bracket 29% 10% 1% 60% 0% Boeing Eggcrate Clip 0% 0% 0% 100% 0% Delphi Pump Housing 20% 9% 1% 70% 0% Virgin Upper Class Monitor Arm (150 lb) 0% 0% 0% 100% 0% Virgin Upper Class Monitor Arm (300 lb) 0% 0% 0% 100% 0%

Table 24 – Additive % by life cycle stage

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Findings and discussion

The lifecycles patterns of the additively produced components appear to mirror those of the traditionally produced parts.

In terms of % split of the emissions between lifecycle stages, the usage phase again dominates, especially when viewing the aerospace components. Emissions related to raw material production are also significant for both automotive parts, namely Bentley’s Transmission Mount Bracket and Delphi’s Pump Housing. For these parts, processing adds non-trivial contributions of approximately 10% of the total.

Raw Material

As a result of the improved material efficiencies, raw material emissions are reduced for all but two of the parts when compared to their traditional counterpart.

There first exception to this is when comparing the additively produced Transmission Mount Bracket with the traditional equivalent that was produced by casting (Scenario 2). This part was highlighted as performing particularly well in this area traditionally. The part made use of a low energy Zinc-Aluminium alloy and a casting process which produced little waste.

The second exception is Delphi’s Pump Housing. The reasons for this lie at the assumptions that have be made regarding the production location. In the absence of actual data, the hypothetical additive scenario sources material from Australia, a major producer of Aluminium but also a location with a particularly poor energy mix.

Processing

As anticipated, the emissions arising from processing additively are higher than those arising from processing traditionally. Although effectively less material is processed due to the improved material efficiencies and lower part weights, additive processes have been found to be massively more energy intensive per kilogram of material processed.

Increasing emissions are seen for each of the additive parts for this lifecycle stage, by at least a factor of 3. However, processing emissions remain low in real terms and the increased burdens are easily outweighed by other savings.

Transport

A combination of a lower final part mass and an improved material efficiency mean that transport emissions are lower in additive supply chains than in traditional supply chains.

It has been assumed no airfreight transportation steps occur in any of the additive supply chains and routes taken generally mirror those taken in the traditional supply chains.

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Usage

Usage emissions are significantly lower in the additive supply chains, due to lower final masses of each of the components. All other aspects of usage are anticipated to remain equal and therefore this can be wholly attributed to the reduction in part mass.

End-of-Life

Due to the methodology taken in this investigation, emissions allocated to end of life remain negligible. As with the traditional supply chains, waste metal will most likely be recycled either within processing facilities or externally at specialist recyclers.

The material efficiency of the additive supply chains does mean that less primary material will end up as waste, although the different forms of the metals may mean that different recycling paths are taken. For instance, oversize and undersize remnants of the atomisation processes may be sold onto other industries for use in paints and pigments or in the chemical welding industry.

Simply considering the boundaries of the components considered the emissions remain unchanged.

Waste in Company Part Waste traditional supply chain kg kg Bentley Transmission Mount Bracket 0.4 11.4 / 0.1 Boeing Eggcrate Clip 0.1 2.0 Delphi Pump Housing 0.2 1.2 Virgin Upper Class Monitor Arm (150 lb) 0.1 2 Virgin Upper Class Monitor Arm (300 lb) 0.2

Totals

The result of the preliminary testing of the alternative additive supply chains is incredibly positive. Increases in process energy appear to be massively outweighed by savings elsewhere in the supply chain, most notably in usage.

The methodology taken in this study allocates usage emissions in the same way as freight mass, meaning that reductions in emissions directly correlate to reductions in mass. Whilst this may be a simplistic approach, further research (Helms, et al., 2009) suggests the levels of savings are not unreasonable.

The dominance of usage emissions suggests component mass is a critical feature of the supply chain and that the focus of redesign to lightweight components is not misplaced.

Significant savings seem to also be achievable in raw material burdens. A combination of the reduced final mass of the parts and the impressive material efficiencies of the additive processes mean considerable savings can be

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experienced. Even accounting for additional losses that come as a result of material preparation processes and part finishing processes, material efficiencies remain much improved in the additive supply chains.

The extent to which additive supply chains can positively affect CO2 emissions depends on a whole range of factors. Clearly one of the most important factors is the starting point on which the comparisons will be based. The majority of the current supply chains appear particularly inefficient especially with regard to material efficiency. The high energy intensity of the materials and constraint to only use virgin material means the implications of poor buy-to-fly ratios of Boeing’s aerospace components are magnified.

Where there is a better material efficiency in the traditional supply chains the savings will be somewhat reduced. For instance, the Bentley’s Transmission Mount Bracket shows the potential of findings savings elsewhere beside additive alternatives. The zinc-aluminium alloy casting performs incredibly well compared to the aluminium original in terms of raw material and process burdens. Even so the additive version still is the best performing part out of the three alternatives albeit by a narrow margin.

WP1 was geared towards selecting parts that seem particularly suited to a transition to additive processing. The early results of the comparisons would suggest that this is an important aspect of the process and that a shift towards additive supply chains, although suitable in many circumstances, may not be a case of one solution fits all. This is by no means an unexpected finding of this study and the focus on transportation seems a good early fit as a sector where significant savings may be achievable.

References

Helms, H., Lambrecht, U. And Höpfner, U. (2009), Energy Savings by Light-Weighting, Final Report, Institute for Energy and Environmental Research, Heidelberg GmbH, Commissioned by the International Aluminium Institute

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WP3 & 4 outcome – Low Carbon Supply Chain Software Toolkit

As has been established throughout the various sections of this report, greenhouse gases are emitted by a whole variety of operations that occur between materials being produced through to the disposal of a product at the end of its effective useful life. All the actions between these two points are known as the product lifecycle.

Material production and processing are both key factors in environmental decision making, but it is also important to consider the transportation, storage and retail operations that are needed before a product is sold to the consumer. Even after this point the usage, maintenance, repair and disposal of a product will all add contributions to the lifecycle CO2 emissions of the product.

The countless variations that can occur in product lifecycles mean no-one stage can be singled out as the most important for all products. To only investigate a solitary aspect of a supply chain limits understanding and can exclude significant contributions to lifecycle emissions.

But considering such a wide and diverse range of activities is a difficult task for all but experienced sustainability professionals. Even high level analyses of carbon footprints have traditionally been time-consuming and reliant on a high level of user expertise. Supply chains that can stretch over many different countries and stakeholders make data collection very difficult to source without top-down commitment and large investments, while suppliers or customers that assume they have little to gain can hinder the process even further. Understanding the impact that changes have on emissions adds a whole new level of complexity, as even small changes can be amplified when considering a product lifecycle. enlighten

One of the outputs of this project is a software tool that is capable of easing this practice and aiding the decision making process of choosing between different parts and their lifecycle footprints with environmental considerations in mind.

This software has been named ‘enlighten’. Considering emissions generated at every stage of a product’s lifecycle, the intention of enlighten is to enable its users to quickly and easily understand the impact that their choices have on energy use and carbon emissions across consistent criteria whilst using reliable datasets.

All the energy monitoring data arising from this study, along with other research, will feed into enlighten and allow the user to build extensive additive supply chains. But as importantly, all the figures are set against a backdrop of traditional manufacturing processes and other supply chain activities, meaning the scenarios can be placed in context of existing practices. The aim of enlighten is to encourage users to engage with the software, make alterations to their supply chains and understand the impact of change.

By doing this the user begins to understand the key points in building low carbon supply chains and becomes more informed when deciding between traditional and additive processes.

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The intention is to continue research into a whole range of different activities and supply chain operations to expand the current catalogue of data.

Approach

Footprinting software tools are already commercially available in the marketplace, but there is a great disparity between the market offerings. On one side, there are simple models which allow users to investigate energy use of a single step for instance transportation. On the other side, massively complex systems exist which attempt to allow the user to investigate every last detail. Very few are able to offer a balance between simplicity and usefulness.

The aim of enlighten is widen the pool of potential users beyond sustainability experts to designers, engineers and supply chain professionals and provide them with the necessary tools to rapidly identify environmental ‘hotspots’ over product lifecycle, either retrospectively or long before a product is ever brought to market.

Bringing this sort of system to a new market brings a number of potential issues. Firstly, it is likely that these users will have little, if any experience with carbon emissions. Early market research suggested enlighten needs to be quick and simple but provide an output that was valuable to a wide range of potential customers. enlighten has therefore been designed with ease-of-use a key consideration, aiming to ensure that building extensive lifecycles was neither a long or arduous task. A novel drag-and-drop approach has been selected as an easy way of building and modifying lifecycles. This is supported by a logic system which links supply chain stages ensuring that the consequences of change is felt up and down the supply chain, without the need for the user to go through and change all their values.

Recognising the need to consider complex systems, enlighten also allows parts to be assembled and evaluated as part of a larger multipart projects.

The output of enlighten is a clean, thorough and flexible report that offers immediate support for those wishing to make decision on an environmental basis. Figures can be compared and contrasted with one another, and environmental hotspots can be recognised, identifying potential areas for more research. Different reports can be generated on individual parts, multipart assemblies or on comparison projects which weight up the pros and cons of different scenarios.

It is envisaged that developing a library of guidelines, case studies and recommendations that advise the decision makers on better ways of arranging their supply chain and designing their parts will be especially valuable. Eventually, integrating such a library with structured problem solving mechanisms will enable advice to be targeted to the individual requirements of the user.

The core functionality of enlighten is complimented with a suite of intelligent supporting features, such as an applet which analyses CAD files to estimate raw material requirements, build times and that all important cost, whilst considering support volumes, orientations and build scenarios. What’s more, the applet can help you to optimise these aspects and provide you with the ideal build.

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Using a web-based format is believed to bring many benefits to the tool, in maintaining up-to-date content and presenting it in a highly visual and interactive way. This also offers fantastic networking opportunities for the user, enabling distributed users to contribute to singular projects and share information and feedback. Recognising that time constraints are also an important issue with designers and engineers alike, the web based approach positions the tool in an accessible location allowing it to be integrated into daily life. Its accessibility and functionality encourage the user in creating many components and building them to understand the implications of multipart products and larger systems.

Development of web based software solution for AM carbon footprint analysis

Enlighten supply chain sustainability tool is a web base software solution for the assessment of conventional and Additive Manufacturing supply chains. The follow document provides a description of the software and how it is used.

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Welcome 2012

Quick Start Guide Beta Testers

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enlighten

Welcome to enlighten, your supply chain sustainability toolkit. This guide will help you to quickly get up-to-speed with enlighten, by explaining how to complete some of the most common tasks and the logic behind them. Why do you need enlighten?

The reality of climate change is an increasingly critical part of the world we live in, affecting us both in our personal lives and in our business endeavours.

Environmental considerations are no longer a footnote hidden away or ignored by businesses; they are an important and valued component of the decision making process. Just as much as enlighten is geared towards helping users in their efforts towards social responsibly; it is also born out of the recognition that good environmental sense by and large makes good business sense.

enlighten arrives as a tool intended to aid the environmental decision making process. Considering emissions generated at every stage of a product’s lifecycle, enlighten enables its users to quickly and easily understand the impact that their choices have on energy use and carbon emissions.

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What you’ll need

There’s very few things that you’ll need in order to get started with enlighten. Here’s what you need;

Viewer User Profile Web Browser JAVA Mouse Keyboard Interface

You will need to hold As a web-based To make the most of The STL analyser is You’ll need a mouse A keyboard will be a registered account software system, that the software, you’ll available as an added to click buttons, make needed to enter text to log on to the makes use of some need a nice big feature to enlighten. selections, and and other data. software. novel functionality, screen, we interact with the drag This applet runs using you’ll need an up-to- recommend a 16:9 and drop interface. In case you forget, Java. Most computers date web browser. aspect ratio. your username will be will already have Java Tablet hardware is not your email address. During the beta test installed but you may currently supported programme we are need to install it if by enlighten. If you don’t have one supporting Internet not. already, you can sign Explorer version 7 and up @ www.enlighten- above only. toolkit.com

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How To enlighten brings a fresh approach to analysing and comparing the environmental performance of parts and products, boasting plenty of novel functionality and many new features that you may not have experienced before.

Nevertheless, with simplicity and ease of use at the centre of enlighten’s approach, it should not take long to get up to speed with the toolkit.

There are currently five main aspects to enlighten:

. Your Dashboard. . The Supply Chain Builder. . The STL analyser. . Assemblies and Comparisons. . Reporting.

Understanding each piece of the software is fundamental to maximising the usefulness of enlighten and getting the most out of the toolkit.

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How To

Dashboard

The Dashboard is your enlighten homepage. In essence it has two main functions. Firstly, it allows you to create projects, such as parts, assemblies and comparisons, just by ‘right clicking’ on your top level directory (or any other folder you wish to create a project within).

Secondly, it is where your completed projects are stored and organised.

By navigating to the dashboard you will be able to access all your saved projects. You can see a summary of these projects by clicking on them in the sidebar and viewing the preview window. You are also able to go back and edit your projects simply by choosing the edit options in the right click menus.

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How To

Supply chain Builder

As you may expect, the Supply Chain Builder, or the SCB, is where your supply chains are built. Simply find your required supply chain activities in the context menus in the sidebar and drag them to the correct place in the working area. You can only create logical supply chains; you won’t be able to cast your part after machining it for example.

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How To

STL Analyser

The STL analyser is your chance to speed up the process of finding that all important geometry data. Just load your files from a location on your computer, orientate the part to your requirements in the part viewer, generate support structure if needed (for Additive Manufacturing) and see the data appear on screen.

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How To

Assemblies and Comparisons

Assemblies and comparisons allow you to go further than just creating independent, single material parts.

Using these functions you can create part relationships that will allow you to see the combined impacts of multiple parts and compare parts against one another to see which perform best and which could be improved.

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How To

Reporting

Rather than simply throwing out random facts and figures, enlighten is capable of organising all your data into a clear and concise report.

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Welcome 2012

An introduction to the key concepts and features of enlighten Beta Testers

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Table of contents

Contents

Contents ...... 2 enlighten ...... 1 An introduction ...... 1 So what are Lifecycle Assessments? ...... 3 Your Supply Chain Sustainability Toolkit ...... 4 Your Dashboard ...... 4 Creating other content ...... 8 The ‘Supply Chain Builder’ ...... 10 STL analyser ...... 27 Creating other content ...... 29 Managing Your Parts ...... 40 Creating other content ...... 44 Some Basics...... 46 Beta Testing Platform ...... 48 enlighten Approach ...... 48 Key Assumptions ...... 48

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An introduction

enlighten An introduction

The reality of climate change is an increasingly critical part of the world we live in, affecting us both in our personal lives and in our business endeavours.

It is widely accepted in the scientific community that emissions need to be cut and our dependence on emitting carbon needs to be reduced. So much so that international governments have committed us to drastically reducing our emissions in the coming decades.

Environmental considerations are no longer a footnote hidden away or ignored by businesses; they are an important and valued component of the decision making process. This is not simply the product of a worthy uprising of social responsibly; it is just as much born out of the recognition that good environmental sense by and large makes good business sense.

A product that uses less material and consumes less energy is not only likely to emit less carbon but it is also likely to cost less. Inefficiency and waste hit the bottom line and ultimately this is the issue that the majority of businesses are most interested in.

But it is not always immediately obvious what the most environmentally favourable option is to a business, especially when considering long and complex supply chains

enlighten arrives as a tool intended to aid this decision making process. Considering emissions generated at every stage of a product’s lifecycle, enlighten enables its users to quickly and easily understand the impact that their choices have on energy use and carbon emissions.

Even considering short lifecycles has traditionally been a daunting prospect for designers, engineers and even environmental and supply chain professionals.

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An introduction

Understanding the impact that changes have on emissions adds a whole new level of complexity. Users can witness even how small changes can be amplified when considering a product lifecycle.

By using enlighten it is not only easy to build extensive lifecycles using a novel drag- and-drop approach, it’s also easy to modify them as enlighten’s logic links supply chain stages ensuring that the consequences of change is felt up and down the supply chain.

Recognising the need to consider complex systems, enlighten also allows parts to be assembled and evaluated as part of a larger multipart projects.

And what’s more, all the information entered on a lifecycle can be pulled together into a clear, concise and valuable report using just a few clicks of the mouse button. Different reports can be generated on individual parts, multipart assemblies or on comparison projects which weight up the pros and cons of different scenarios.

Consider a product design change for instance, the consequences of this will filter down the supply chain and impact emissions over the entire course of a lifecycle.

Not only may the amount of material needed change, the amount of transport and processing may change. The design adjustment may also mean different processing methods needs to be used; again affecting the amount of material production needed and transport requirements, as well as the amount and type of waste produced. The design change may affect product performance; a more robust product may last twice as long for instance, but what is the importance of this when considering that the additional weight reduces the energy efficiency of the product during use? At the end of the lifecycle, how will the product(s) be disposed of, are they easily dismantled, can they be recycled and so on. The ramifications of the change can seem endless.

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So what are Lifecycle Assessments?

Greenhouse gases are emitted by a whole variety of operations that occur between materials being produced, which enable a product to be manufactured, through to the disposal of a product at the end of its effective useful life. All the actions between these two points are known as the product lifecycle.

The operations that make up a product lifecycle are generally grouped into the following 5 categories;

The countless variations that can occur in product lifecycles mean no-one stage can be singled out as the most important for all products. To only investigate a single aspect of a supply chain limits understanding and can exclude significant contributions to lifecycle emissions.

Lifecycle considerations are at the heart of enlighten’s approach, ensuring that you appreciate emissions generated at every stage of your products existence.

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Your Dashboard

Your Supply Chain Sustainability Toolkit

Now that you’re acquainted with the concepts of enlighten, the next step is to learn how to make use of its key features.

The following sections will guide you through the fundamentals of the software toolkit. Your Dashboard

The dashboard is the page you first see when you log into enlighten and it is the location that stores all your projects and files.

On first sight this area may appear a little empty, but eventually it will host a vast collection of your parts, project folders, assemblies, reports and other content.

If you already use Windows, you’re most of the way there to knowing the way around your dashboard. The way that you organise your content is up to you, but we recommend that you create a series of folders to store your projects in. This will allow you to keep your dashboard organised and effortlessly find whatever file you are looking for.

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Your Dashboard

The Sidebar and the Preview Window

The dashboard consists of two key areas; the sidebar and the preview window.

Just like a browser window that you may use on Windows, the sidebar shows a directory of all the content that is contained within your account. Eventually this will include folders, parts, assemblies and comparisons. Different icons are used to illustrate what type of content an entry is related to.

Depending on what is selected in the sidebar, different information will be shown in the preview window. Selecting a part, assembly or a comparison will trigger the preview window to display a glimpse of the content inside that item. This is useful for getting a good idea of what content relates to without entering the supply chain builder (see The ‘Supply Chain Builder’).

Creating Parts and Folders

To create an item within your dashboard, simply ‘right click’ on the directory in which you wish to create the content. If it is the first folder you are creating, right click on the directory and select ‘New Folder’. You will then be asked to name the folder.

If on the other hand you wish to create a new part, select ‘New Part’. Again you will be asked to name the part as well as defining some other key details.

If you happen to create a folder or part in the wrong directory, simply drag (see Drag and Drop) the item you wish to move using the left mouse button to the correct location.

Assemblies and comparisons can also be created in the dashboard; more information is available on these features later on in this guide (see STL analyser

The core functionality of enlighten is complimented with a suite of intelligent supporting features, such as the STL applet which analyses CAD files to estimate raw

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Your Dashboard

material requirements, build times and that all important cost, whilst considering support volumes, orientations and build scenarios. What’s more, the applet can help you to optimise these aspects and provide you with the ideal build.

The STL analyser is launched from within the Supply Chain Builder, simply by clicking on the STL Analyser button found at the bottom of the working window.

A Java window will then be launched, note you must have Java installed on your machine and allow your system to run the file by clicking ‘OK’ and trusting the application by clicking ‘Run’.

The STL Analyser will then be run in a separate window to your Web Browser. This means all the calculations and computational work will be done on your local machine, rather than over the Internet. This allows the calculations to run much quicker and independent of your network connection. It also ensures that you can be safe in knowledge that your STL files are safe and never leave your system.

The STL currently boasts a number of features providing data that are useful in both additive and traditional supply chains.

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Your Dashboard

Just by loading your STL file, the applet will provide you with important data on the;

width; volume; and length; surface area. height;

These data can then be simply copied and pasted to the nodes contained in the SCB. For instance, you can directly copy the part volume across to enlighten. Alternatively, you may use the dimensions of your part to calculate a bounding box which may be used to estimate raw material requirements.

The STL Analyser also contains the functionality to view your part, thus enabling you to ensure that to have the correct part and orientation. To do this, simply click on the View button and another window will be launched showing your STL file.

The STL Analyser also boasts a smart support generator which is capable of estimating realistic support volumes for different build scenarios. The software is capable of recognising features in your file and projecting different support styles.

You may decide to orientate your part to minimise the level of support.

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Creating other content

Individual parts are the fundamental building blocks that relate to all other content within enlighten. Data entered in the supply chain builder relates to single, discrete parts that are made from the one material chosen upon creation of the part.

But systems are often much more complex than this, being made of numerous parts each possibly manufactured in a different way and out of a different material. enlighten can be used for more than just creating parts and folders (see Creating Parts and Folders); you can also use enlighten to create an assortment of assemblies, comparisons and reports; these are detailed in the following sections.

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Creating other content

Assemblies and Comparisons).

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The ‘Supply Chain Builder’

The ‘Supply Chain Builder’ is central to everything you do on enlighten, and as you may expect it is used to build your supply chain.

Lifecycle stages

The following section will guide you through the five important lifecycle categories. Whilst we hope that you will use the builder in the way that suits you best, there are a few rules that are important to bear in mind.

Raw Material You will notice that there are only four of the five categories listed vertically in your supply chain builder; raw material has been omitted from this list as this was specified when the part was initially created (see Error! Not a valid bookmark self-reference.).

The raw material node is not editable and you cannot change the material or directly manipulate the amount of material needed. Instead, the raw material requirement is calculated based on the data entered in the manufacturing stages later in the supply chain (see Manufacture).

If you choose your first process as ‘Investment Casting’ for instance, the pour weight will be used to establish how much material is needed at the beginning of the lifecycle. This in turn will be used to calculate the energy demand and CO2 emissions of raw material production. This will be specific to the material grade and recycled content defined when first creating the part.

In this respect, when you first enter the supply chain builder the material requirements will be equal to zero. Only when you begin to populate the supply chain will raw material production begin to make an impact.

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The ‘Supply Chain Builder’

Manufacture Manufacturing processes are categorised into primary and ancillary processes.

Primary Processes enlighten defines primary processes as those that form the part into a size and shape that closely resembles the final piece. These processes often have a dramatic impact on the size and shape of the part. Primary processes typically have the largest bearing on the overall emissions generated during manufacturing.

Whilst certain processes may be available for selection in one supply chain, they may not necessarily be available in another. This is because all processes are related to a specific range of materials, meaning that depending upon your selection, only a subset of enlighten’s full list of materials may be available in the sidebar. enlighten’s intelligent logic system filters out all the nonsensical processes ensuring that only practical scenarios can be constructed in the builder. In short enlighten knows that you cannot investment cast a plastic material or injection mould a steel material and does not allow you to do so.

This is one reason why it is important that you take care in making your material selection when creating your parts, as this is a key step in building your supply chain and defining the processes that are available to you.

In certain circumstances, a process may not be available for selection even when it makes logical sense that it should be. Although, we believe our data coverage is good for the processes we have researched, there will be gaps in our data. Where no data is held for a material-to-process combination, the process will not be available for selection. We are continuously working on expanding our datasets.

Ancillary Processes

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The ‘Supply Chain Builder’

Ancillary processes describe two types of different operations; namely material preparation and part modification.

Material preparation processes can be used to significantly change the form of the raw material, but do not create an output that resembles that of the final piece. As the name suggests, they are used to prepare material into the appropriate state needed by a primary process. Examples include the atomisation of powders used in additive manufacturing or powder metallurgy, or the extrusion of polymers used as machining stock.

Part modification processes can be used to alter the size, shape, surface finish or material properties of a component. These often follow the primary processes and usually modify the part less significantly than primary processes. Examples of part modification processes include electrochemical de-burring, polishing and etching.

There are a few processes that can be classified as both a material preparation and a part modification process. For instance heat treatment may be used to prepare material prior to a primary process or it may be used to improve the material properties after a primary process has been done.

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The ‘Supply Chain Builder’

Distribution Transporting an object or load between two points is not always a straightforward affair; energy use and CO2 emissions resulting from transporting can vary significantly depending on the vehicles used and the routes taken. enlighten endeavours to allow you to calculate emissions specific to your distribution chains by asking you to select a vehicle type from a list of air, sea, rail and road vehicles.

This helps us to make some assumptions on probable vehicle loading, driving styles, return journeys and so forth based on vehicle averages.

In all probability even the distances travelled will vary depending on your choice of vehicle; we therefore apply a series uplift factors in order to account for the potential routes taken. For example, whereas aircraft may travel in relatively straight lines, it is probable that a much further distance would be travelled between the same locations using rail transport.

As well as the distances travelled and the mode of transport used, enlighten also considers the mass of the part being transported. This again is defined by the manufacturing processes that precede and succeed it. Currently, enlighten does not consider any additional emissions that may arise as a result of additional packaging weight.

Distribution steps not only help us to calculate the impacts of transportation, but also define where operations take place. It is important that we know these details as the location of each lifecycle step will have a bearing on the CO2 emissions generated. For instance, a part manufactured using CNC machining in India will have a different amount of embedded carbon than the same part made using CNC machining in Finland. This is because India and Finland have very different electrical

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The ‘Supply Chain Builder’

energy generation mixes, resulting in different levels of CO2 per unit of electricity generated.

For this reason it is vital to build a detailed supply chain location map detailing at least the countries where major processing and usage activities occur.

Adding distribution nodes In order to add a distribution node to your supply chain, you must find the relevant vehicle in the sidebar. There is a whole range or air, land and sea vehicles available for you to choose from.

Once you have selected the relevant vehicle, you must drag and drop (see Drag and Drop) it to the appropriate space in the working window.

This journey will then be added as a node in your supply chain. If it is the first journey added, you will have to specify both the start and end point of the journey. This is done using a few simple selections. Both the start and end points are defined in the same way; first by selecting a continent, then a country and finally a city.

This allows us to present you with filtered menus based on your selection. For example, if you select Europe as the continent, only European countries are then shown in the country dropdown menu. Likewise only UK cities will be displayed if you were to select the United Kingdom as the country.

The menus are also filtered as you type. Begin by typing a ‘B’ and only cities beginning with a ‘B’ are shown. Extend this to ‘Bir’ and you will be shown all the cities with ‘Bir’ at the start of their name. This is especially useful when there are many locations in one place.

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The ‘Supply Chain Builder’

Only 15 locations are shown in any one dropdown, if the selection you are looking for is not shown, try typing a few more letters to see a cut down list.

As you add more distribution nodes into your supply chain, you will notice how enlighten will populate the start location of your distribution nodes. This is defined by the end-point of the preceding distribution step. We have found this to be a great time saver and very useful for ensuring continuity in the supply chain. It is important to remember that changing the end-point of a distribution will go on to change the start point of the node that succeeds it.

To ensure that you can build as accurate a supply chain as possible, we have populated enlighten with plenty of locations in every corner of the world and you should have no trouble in finding the location you are looking for.

Some countries hold a greater level of detail than others; countries such as the USA, Germany and the UK all hold thousands of locations. Other locations hold more limited datasets; countries such as Fiji and Bhutan for instance may be limited to a small selection of locations. Nonetheless, all the countries contained in our dataset contain a ‘Geographic Centre’ location ensuring that you will always be able to find a location that is relatively close to your requirement.

The level of specificity you decide to impart in your supply chains is up to you. We generally suggest that a new journey should be created with each change of vehicle. For instance, it would be recommended that you not only define the start and end points of a distribution phase but aim to identify all the ports, airports and

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The ‘Supply Chain Builder’

distribution centres that are passed through along the way. Using different vehicles to distribute goods can have a significant bearing on the emissions calculated.

You may wish to increase the number of distribution nodes in your supply chain where longer journeys are undertaken. This ensures the routes calculated closely match those taken in the actual supply chain.

Editing distribution nodes If you decide that you need to move journeys around, this is possible, but you must make sure you understand how the supply chains will change. A distribution node pulled between two existing journeys will change the route taken to pass through the new node.

The way this works is that, the origin of the node that has been moved will be pushed through as the destination of the preceding transportation step. You can edit this if you wish, but you will only be able to do so as the destination of the preceding step. The destination of the node that has been moved will likewise be pulled through from the origin of the subsequent transportation step.

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The ‘Supply Chain Builder’

Usage The focus of enlighten has so far centred on parts used in the transportation sector and accordingly we have focused on this sector when considering the usage phase of a parts life.

As with other transportation steps, usage contributions are based on mass being transported over distance using a specified vehicle. Usage phases are often calculated based on hypothetical scenarios; for instance lifetime distances may be approximated using industry average data on annual mileage and typical service lives. enlighten can be used to build any part you please, but as of yet it is only transport parts that can be assigned any emissions during usage.

Contributions to lifecycle emissions at the usage phase can arise from a whole variety of different applications from the use of electricity, fuel, water and so on. But it is difficult to assign these to the individual components that make up a product. Should your fridge handle be allocated a proportion of the refrigerant and electricity used by a refrigerator? Should a toothpaste tube be allocated a proportion of the water used whilst brushing ones teeth? This is very much subjective and depends on what units are being considered or compared. enlighten apportions usage contributions based on mass, effectively assuming that a kilogram of mass requires the same amount of fuel regardless of its location on a vehicle. We hope to extend our usage section to consider different product applications in the near future.

For every kilogram of mass removed on a vehicle, ‘light-weighting’ adjusts the fuel economy at a different rate than the average fuel economy of the vehicle per kilogram. We are currently working on means of assigning different figures to modifications that result in design changes for fuel efficiency.

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The ‘Supply Chain Builder’

End of Life End-of-life contributions are intended to aid decisions between direct disposal methods and recycling and recovery alternatives.

At the end of a products life, material may be reused or recycled in similar or different products, energy may be recovered through incineration and other waste- to-energy (WtE) processes or the product may be simply sent to landfill.

The way enlighten works is to consider recycled content rather than recyclability. In this respect, burdens are effectively avoided when inputs arrive from more favourable sources. Attributing ‘credits’ at the end-of-life would cause issues with double- counting and would assume that recycling material always substitutes an equal amount of the same material. This is clearly not the case.

All contributions made by the actual process of recycling, energy recovery and so forth are therefore assigned to the products that make use of them as inputs. Only disposal / landfill options therefore make contributions to the emissions during the end of life phase. As metals are almost always recycled and as inert materials contribute zero emissions at landfill, end-of-life considerations can be extremely low.

We are working on developing a means of assigning emissions to processes such as disassembly and sorting, along with emissions caused by non-metallic parts during landfill.

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The ‘Supply Chain Builder’

Create a Part

Now that you’re up-to-speed with the principals behind enlighten’s approach to lifecycle stages, you can begin to create your library of parts and products.

The first thing that you must do in building your supply chain is to create the part for which the supply chain will be built.

After deciding on where you wish to position your part and selecting the ‘New Part’ option from the right click menu (see Creating Parts and Folders), you will then be asked to define some aspects of your part.

The better described your part; the better it will be understood in the future. Although the ‘Part Number’ and ‘Part Description’ fields are not imperative to the creation of your parts, accurate information will help you search for and identify your parts in the times to come.

Besides the name, reference and description of the part, the primary material is selected here. The choice of material is an important one. It is recommended that you take care when completing these details as the material fields cannot be edited at a later date.

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The ‘Supply Chain Builder’

Material section A whole range of materials are available for your selection. To help you find your required material we have categorised our materials in increasing specificity in terms of the material class, type and grade. Starting at the highest level, the selections you make will influence the manufacturing options available to you at the subsequent stages.

Once you have selected your material, the next step is to define the proportion of input from primary and secondary sources. There are four options here; you can choose to use 100% virgin content, 100% recycled content, industry standard levels of recycled content or you can define the percentage of recycled content yourself.

If you do not know this information we recommend that you choose industry standard levels. We use data that is specific to the grades and material classes available for selection.

If we do not think that a material can be recycled, the option to select recycled content will be disabled.

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The ‘Supply Chain Builder’

Building your supply chain

Once you have successfully entered your part details and clicked ‘Create’, you will arrive at the supply chain builder. The ‘Supply Chain Builder’ is where you add all the key information on your products’ lifecycles and where you see your parts really start to take shape.

Finding your way around the ‘Supply Chain Builder’ The builder contains all the features you need to build your supply chain and shows running totals on each phase as they are added.

The composition of the supply chain builder window is explained in the following sections.

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The ‘Supply Chain Builder’

Part Information & Raw material information To ensure that you always know what part you are building and what it relates to, we have included a brief part summary at the top of the Supply Chain Builder.

Here you can see the details that were defined when the part was created. Whilst the part information is editable from the dashboard, the raw material selected cannot be changed (see Raw Material).

Sidebar The Supply Chain Builder sidebar is where all the supply chain activities are held ready to be added to your supply chains as you please.

Activities are categorised into the lifecycle stages which are located on the left-hand side of the sidebar. Clicking on one of these stages will expand the relevant menu where the activities will be found. Sub-menus can be expanded and collapsed by clicking on the plus and minus signs that appear next to the menu headings.

In order to add an activity to your supply chain, you need to simply drag-and-drop the item from the sidebar to the relevant location in the working area. Only logical activities can be dragged from the sidebar to the working area, so be sure to drop the activity in the correct place in your supply chain.

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The ‘Supply Chain Builder’

The activities available in the sidebar will very much depend on your material selection. If you have selected a plastic material, then logically only plastic processes are available. Likewise, metal process will be available for parts that use metals.

Working area The working area holds all the activities that you have added to your supply chain. After dragging an activity from the sidebar into the working area it should hold in place enabling you to add the relevant information which the calculations will be based on.

Activities within the working space are ordered chronologically, with the activities occurring first appearing at the top of the area. Modifying the data contained in a node can have ramifications across the lifecycle.

Activities that have been added to the working area are called nodes.

Supply chain nodes Lifecycles are built step-by-step by adding ‘nodes’, which relate to individual activities within a supply chain. These activities can be grouped into five main categories (see The reality of climate change is an increasingly critical part of the world we live in, affecting us both in our personal lives and in our business endeavours.

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The ‘Supply Chain Builder’

But it is not always immediately obvious what the most environmentally favourable option is to a business, especially when considering long and complex supply chains

Even considering short lifecycles has traditionally been a daunting prospect for designers, engineers and even environmental and supply chain professionals. Understanding the impact that changes have on emissions adds a whole new level of complexity. Users can witness even how small changes can be amplified when considering a product lifecycle.

Recognising the need to consider complex systems, enlighten also allows parts to be assembled and evaluated as part of a larger multipart projects.

And what’s more, all the information entered on a lifecycle can be pulled together into a clear, concise and valuable report using just a few clicks of the mouse button.

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The ‘Supply Chain Builder’

Different reports can be generated on individual parts, multipart assemblies or on comparison projects which weight up the pros and cons of different scenarios.

Consider a product design change for instance, the consequences of this will filter down the supply chain and impact emissions over the entire course of a lifecycle.

). We have used a consistent colouring scheme so it is always easy to identifiable what lifecycle stage a node relates to.

All of the operations from the extraction of raw materials to the disposal or recycling of those materials can be classified into one of these categories. Within enlighten we refer to these activities as nodes.

Nodes should be ordered in chronological order. Although it is also best to add them to working space this way, it is not essential and nodes can be added in any order as long the supply chains remain logical.

Raw materials are always automatically positioned at the top of your builder; material additions can only be made by creating a project (see Creating Parts and Folders) or by modifying the quantities needed in processing.

Supply chain Builder Buttons The buttons we have included are all intended to ease the process of building supply chains.

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The ‘Supply Chain Builder’

- Back to Dashboard – A link that allows you to navigate back to your dashboard.

Be sure to save your progress before navigating away from your builder, as changes will not be stored unless they are saved by the user. - Save – Saves your progress whilst in the builder.

We recommend you save promptly after creating a new project and at regular intervals whilst building your supply chain. Because enlighten is a web based ‘cloud’ toolkit, we can only save data when instructed by the user - Show Info – Transforms the data that you have entered into the ‘Supply Chain Builder’ into a report format that details key information and calculations. Show info can also be exported in MS-Word and PDF formats. - STL Analyser – This tool allows you to interrogate a 3D CAD file saved in the STL format, to establish the volume, surface area and size of the part being assessed. - Collapse All – Minimises all the supply chain nodes into a single line banner heading.

Useful when you only wish to see the summary information of each node.

Useful when you have a particularly long and complex supply chain with multiple nodes of operation. - Expand All – Expands all nodes to show more detail on input values and selections

Useful for finding particular figures and editing your supply chains.

Recommended when you have a relatively small number of nodes in a supply chain. It is suggested that nodes are expanded one-by-one when the supply chain builder is heavily populated.

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STL analyser

The core functionality of enlighten is complimented with a suite of intelligent supporting features, such as the STL applet which analyses CAD files to estimate raw material requirements, build times and that all important cost, whilst considering support volumes, orientations and build scenarios. What’s more, the applet can help you to optimise these aspects and provide you with the ideal build.

The STL analyser is launched from within the Supply Chain Builder, simply by clicking on the STL Analyser button found at the bottom of the working window.

A Java window will then be launched, note you must have Java installed on your machine and allow your system to run the file by clicking ‘OK’ and trusting the application by clicking ‘Run’.

The STL currently boasts a number of features providing data that are useful in both additive and traditional supply chains.

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STL analyser

Just by loading your STL file, the applet will provide you with important data on the;

width; volume; and length; surface area. height;

You may decide to orientate your part to minimise the level of support.

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Creating other content

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Creating other content

Assemblies

You may have noticed that the ‘Supply Chain Builder’ limits you to one raw material per part. This helps ensure that only reasonable processing options are available for selection and that energy and CO2 data is applied based on the specific material being handled.

Assemblies are your chance to merge multiple projects into a single item, allowing you to see the combined impacts of supply chains. This can be incredibly useful when design changes have an effect on a collection of parts or when you want to compare large systems and more complex project proposals.

Creating assemblies is straightforward, just simply right click on the folder where you wish to place your assembly and use the ‘New Assembly’ option. Then just drag in the parts which you want to include in the assembly (see Drag and Drop). The parts that you decide to drag in don’t have to be in the same folder as the assembly.

You’re free to add and remove parts as you wish, the assembly will track the changes and describe whatever is in the assembly at that time.

You should also note that editing the supply chains of parts contained in an assembly will cascade through to the assembly itself. Therefore you don’t need to worry about updating your assemblies every time you update your parts.

If you do wish to edit a supply chain without changing the data held for an assembly, you must create a duplicate part (see

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Creating other content

) where the changes can be made.

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Creating other content

Comparisons

Comparisons, as you may expect, are enlighten’s way of allowing you to evaluate a series of parts and compare the emissions generated. In a sense, comparisons are similar to assemblies, but rather than adding together the sums of the parts involved comparisons match up the relevant stages allowing one to see the impacts that design changes and other supply chain considerations have on lifecycle emissions.

The method of creating comparisons closely matches that used for creating assemblies (see

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Creating other content

). Once you have decided where the comparison should be placed, simply right click on your chosen folder and select the ‘Create Comparison’ option. Just like with assemblies, simply drag in the parts which you wish the Comparison to contain.

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Creating other content

Assembly and Comparison tips

Although creating assemblies and comparisons is easy, there are a few things that you should bear in mind, as there are many ways in which you may wish to employ these functions. You may wish to combine your projects to represent a whole system or you may just want to see the total impacts of a series of related parts. Either way, it is useful to define the basis for the assembly / comparison within the respective description – that way when you go back to analyse your findings you’ll know exactly what you’re looking at.

We also recommend that you try and conceptualise your projects in terms of functional units. The functional unit is essentially the item under consideration; this may be a single part or it may be a larger system. For instance, it would be rational to define a functional unit simply as a single tyre. Alternatively, the functional unit may be the tyres on a car; in this case you will be considering four tyres. Another situation may see you considering the use of different tyres during a car’s useful life; here you may have to consider 8, 12 or maybe even more tyres. In this case, you may have to compare the use of 12 types of one tyre against the use 8 more durable tyres. Analysing individual parts is all well and good but when it comes to adding parts, contrasting figures and making comparisons, it becomes vital to ground the assessments in context.

Consider two aerospace parts; Product A and Product B. The production and distribution of Product A produces 25% less emissions than Product B. The choice between the two seems obvious. But when you consider than Product B lasts twice as long as Product A when used as an aerospace component and is 20% lighter, the situation changes. Product B only becomes more favourable when defining your boundaries and standardising the unit of comparison (the functional unit) across the entire lifecycle of the aircraft.

Assembling or comparing projects with non-standardised functional units can result in a great deal of confusion.

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Creating other content

So always try to create your parts and projects in context; are you working on the basis of a single part, are you considering the parts by kilogram of mass or is your whole production run under consideration? enlighten gives you the option to make these considerations and change them as you wish, but it is your responsibility to maintain the grounds for comparison.

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Creating other content

Reporting

Displaying all the key findings and important information in a clear and concise format, the nifty reporting component is one of enlighten’s best features.

Simply clicking on the ‘Show Info’ button leads you directly to an automatically generated report on your chosen item. enlighten’s part reports present a summary on all the individual lifecycle activities and a running total of energy usage, CO2 emissions, product miles and waste creation as well as a whole range of other useful facts, figures and findings.

A part report can be generated at any time within the ‘Supply Chain Builder’, allowing you to see a running total during your build or see the final results when all your data have been added. However, it is important to note that the report will only display information on the data that have been added to the supply chain; if you generate a report on an incomplete supply chain, the result will be that a shortened report is produced.

You don’t have to be in the ‘Supply Chain Builder’ to see information on your items. Selecting an item in your dashboard will also allow you to see some brief detail about that item in the preview window (see

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Creating other content

The Sidebar and the Preview Window). Depending on the type of item selected this will show a selection of the charts and tables contained in the report.

A full report can also be generated within your dashboard. Simply select the show info option that is available in the preview window to launch the report window.

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Creating other content

Report Templates The type of the content on which a report is being created will influence the type of report that is generated by enlighten. Three types of report are currently available, these correlate directly to the three types of content currently produced in enlighten, namely individual parts, assemblies and comparisons.

Part reports Part reports provide information on the individual discrete selected parts. The report is laid out in a portrait template, and begins with sections on the part detail and supply chain summary. The report proceeds to feature information on the each supply chain node and provides charts which breakdown total energy usage and CO2 emissions into their respective lifecycle stages.

Assembly Reports Assembly details are calculated as the sum totals of all the parts that are contained within an assembly. This accelerates the process of appreciating the full impact of a series of components, averting the need to manually add figures together or combine reports.

Assembly reports also provide a breakdown of the individual parts that are contained in the assembly. This aides the identification of the parts which create the most emissions, which is an important step in understanding where reduction efforts should be focused.

By detailing a breakdown of the assembly inventory the user should also be able to quickly realise whether or not the correct parts have been added.

A landscape layout has been chosen as the most suitable fit for this type of report.

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Creating other content

Comparison Reports Comparison reports have been designed to best show the impacts of a series of component parts in a single report.

The report beings with details of the comparison itself, entered when the comparison is created. We recommend this should contain information on the reasoning behind the comparison and the basis for comparison, but will depend on what you have entered as the user.

Comparisons reports will display any items that are added, but it is important to consider a functional unit when creating a report. This is because in order to ensure that a comparison is fair, it is important to judge items when fulfilling the same function (see Assembly and Comparison tips).

As with assembly reports, comparison reports also show a breakdown of all the parts that are held in its inventory. This helps identify which stage if any is responsible for the majority of emissions in a lifecycle. Again, the report is formatted with a landscape layout as to best display the tables and other content.

Document Formats The report window is a great place to see how your build is progressing, but it is not necessarily the best format for further dissemination or personal editing. Therefore, we’ve developed a facility for the user to generate a report in either a .doc (Microsoft Word) or .pdf (Adobe reader) format.

Using this feature is perfect for those wishing to share their reports or expand upon their findings with additional data, personal comment and annotations.

The option to generate .doc or .pdf files is contained within the report window; after generating a report using the ‘Show Info’ button (see Reporting) simply click on your chosen format and this will automatically initiate a file download.

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Managing Your Parts

If you wish to save a .doc or .pdf report you can only save this to your local machine. There is no provision to save reports within the enlighten toolkit, as new reports can be generated on-the ‘fly’ at any time. Managing Your Parts

Once you’ve created and saved your parts, they do not become set in stone and you can go back and edit them as you please.

Folders

It’s important that you organise and maintain your parts over time. If the information on a part changes it may need to be moved to another folder. Don’t be afraid to create new folders as your portfolio of parts increases (see Creating Parts and FoldersCreating).

Editing and deleting

Whether the nature of a part changes over time, you realise you’ve made a mistake or whether more data simply becomes available to you, we understand that you may want to come back and edit a part.

You can choose to go back and edit either the part details (properties) or the supply chain itself as you please. Just right click on your chosen part and select your required option from the drop-down menu. You can also find an option to edit parts within the preview window found in the dashboard.

The only aspect of a supply chain you cannot alter is the raw material selection. This is due to the fact that the selection of your raw material informs the builder of which processes should be presented in any given supply chain. The material selection is such an inherent part of the supply chain that editing it would have too many ramifications on the other stages in a parts lifecycle potentially making stored selections illogical or unjustified.

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Managing Your Parts

NOTE - You must be aware that assemblies and comparisons that have been built based on a part will also change if any parts are edited. If you do not want this to happen, then you need to make a duplicate part prior to editing.

Duplicating

The option for duplicating a part is useful for creating new parts without having to build the supply chain again and again, where for example one wishes to see the impact that a small change (such as a change in part design or supply chain configuration) can have on lifecycle emissions.

It is best used where multiple parts or scenarios share a large proportion of their supply chain but differ in an important way. For instance, a simple change to a product design file (STL) is likely to not only affect the product at point of use, but may also have an effect on the amount of raw material needed, which goes on to affect the energy needed for processing, the weight of material transported over distance, the amount of waste created and so forth. Although the original and the new part may have exactly the same nodes added, the fundamental difference in product mass will be important to consider.

When the duplication is made it will hold information that matches exactly with the original part. We recommend that after creating a duplicate you should edit both the name and description of the part explaining the reason for the duplication. This helps to avoid confusion at a later data.

Duplicate parts often form the basis for both assemblies (see STL analyser

The STL analyser is launched from within the Supply Chain Builder, simply by clicking on the STL Analyser button found at the bottom of the working window.

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Managing Your Parts

A Java window will then be launched, note you must have Java installed on your machine and allow your system to run the file by clicking ‘OK’ and trusting the application by clicking ‘Run’.

The STL currently boasts a number of features providing data that are useful in both additive and traditional supply chains.

Just by loading your STL file, the applet will provide you with important data on the;

width; volume; and length; surface area. height;

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Managing Your Parts

You may decide to orientate your part to minimise the level of support.

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Creating other content

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Creating other content

Assemblies) and comparisons (see Comparisons). Assemblies may comprise of multiples of the same part or very similar parts. Comparisons on the other hand may be used to evaluate the ramification of those comparisons.

Duplicates can also be useful to ensure that assembly and comparison data is retained even when parts are edited. The way assemblies and comparisons work is that they are essentially assigned parts by the use of links and therefore change as the underlying parts are edited. If you wish to edit a part whilst maintaining the data held for an assembly or a comparison, we recommend that a duplicate part is created and used for all the edits. The duplication will copy all the supply chain information across to the new part, it will not however copy any of the links held on a part and consequently the duplicate will not be part of any assemblies or comparisons.

To create a duplicate simply right click on the part you wish to duplicate and select the ‘Duplicate Part’ option, a duplicate part will then be created in the same folder as the original with (copy) added to its name.

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Some Basics

The following section has been created for those of you that are less familiar with some of fundamental operations used in enlighten.

Display Resolution (pixel dimensions) enlighten has been designed for use on a widescreen monitor with 720x576 dimensions. Content may fit on screens with different display resolution settings but for best performance we recommend the 720x576 setting.

Your display resolution cannot be altered within enlighten. However, it can be changed on your PC or laptop in the Personalisation area of your Control Panel. To edit this simply right click on any area on your desktop and select Personalise, then choose the Display Settings option (for Windows only). Here you will be able to edit your screen resolution.

Drag and Drop

Dragging and dropping content can be used to move certain content from one place to another

In order to drag and drop a piece of content, you should;

1. press your left mouse button on the item you wish to move; 2. keep the left mouse button pressed, move your mouse pointer to the location you wish to place the content; and 3. then release the button only when you have positioned the content where you wish it to be placed.

This function is commonly used for organising the content stored in the enlighten dashboard and in adding activity nodes in the supply chain builder.

Saving downloaded content enlighten reporting allows you to generate two types of downloadable content in the form of Microsoft Word (.doc) and Adobe Reader (.pdf) documents.

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Some Basics

Once a download has been triggered within enlighten, you will typically be presented with three available options, namely; open, save and cancel.

As the option suggests, opening the file will open the document upon completion of the download, assuming you have either MS-Word or Adobe reader software loaded onto your computer. The document can then be treated as like a normal document and can be saved as in the normal way (by going to the ‘Save As’ option).

Depending on your web-browser settings all downloads are usually stored in a dedicated download folder or within a temporary files folder.

Using the save option allows you to choose where your file will be stored prior to the download. The file will not open automatically if you choose this option.

Cancelling the download will simply stop the download and no file will be opened or saved.

Downloads are handled by your web browser and settings can only be changed using the browser settings. If your setting prevent downloads from taking place you will not be able to download the files to your desktop.

Session Expiry

Each time you log on to enlighten you begin a session which deals with all your personalised content. This means you are able to save your progress and be safe in the knowledge that your content will be available again when you need it.

When you log out of enlighten your session ends securing your account until the next time you log in.

Your session will also end after a prolonged period of inactivity. This ensures that should you forget to ‘logout’, your session will not remain open for others to make unauthorised changes on your computer. This also means that you must be sure to save your progress on a regular basis. All unsaved content will be lost following the expiration of a session.

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Beta Testing Platform enlighten Approach

The findings of enlighten are designed to provide an approximation of the CO2 implications of your components. Our footprinting process exclusively considers the primary processing activities conducted in the supply chain and excludes the supportive and auxiliary processes, which may or may not add significant CO2 contributions to the supply chain. The reported footprints are therefore expected to underestimate the real life cycle emissions of the components discussed.

This report is intended to report on CO2 emissions, although the importance of other GHGs should be acknowledged. This is based on the level of public and corporate understanding on this subject and the belief that reducing carbon emissions will help to reduce other GHG emissions and will enhance the level of awareness regarding sustainability. What is more, CO2 is the one greenhouse gas contributing most strongly to global warming and as such CO2 is by far the most understood and well researched emission. Key Assumptions

All figures quoted by Enlighten are approximate figures, based on a number of calculations and assumptions.

1. The energy figures and carbon dioxide calculations presented are derived from the direct energy requirements of the processes. a. All figures represent high volume production. i. It should be acknowledged that actual energy requirements will be dependent upon additional factors such as the machine type, capacity, utilisation and throughput. 2. Published embodied energy figures are used to supplement and validate our own findings; a. figures include additional energy requirements for the facility, including lighting, heating, cooling, ventilation, air conditioning, compressors, water pumps and so on. b. figures do not include the ‘tacit energy’ associated with the generation and supply of energy to the processing facility c. figures are derived from; i. the energy required to heat up the base material to its processing temperature; ii. the energy required to heat up and maintain the equipment at its operating temperature; iii. the energy required to deform the material at the processing temperature. 3. Carbon dioxide emissions are calculated from data on electricity and fuel usage; a. A single emission factor is used for natural gas usage, although carbon emissions per unit energy for natural gas will fluctuate regionally very marginally depending on the gas pressure in transmission.

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Key Assumptions

4. Materials leave primary production facilities and recycling facilities in the same state; a. metals are assumed to be produced in billet form b. polymer is assumed to be produced in pellets

5. The emissions resulting from transportation and distribution are based on the CO2 impact of

mass being transported over distance (CO2 / tonne kilometre). Figures are taken from Defra (2008), who categorise the figures in terms of transport type; a. Aviation; i. Average seating capacities, load factors and proportions of passenger km by different aircraft types. b. Passenger cars and vans i. UK driving speeds and cycles, vehicle age and real world effects such as the use of accessories, vehicle payload, maintenance (tyre under inflation, maladjusted tracking, etc), gradients, weather, driving style, etc. c. Heavy goods vehicles i. Average miles per gallon and average loading factor for different sizes of

rigid and articulated HGVs, fuel efficiency, and hence CO2 emissions, varies with vehicle load. d. Light goods vehicles i. UK driving speeds and cycles, vehicle age and real world effects such as the use of accessories, vehicle payload, maintenance (tyre under inflation, maladjusted tracking, etc), gradients, weather, driving style, etc. e. Rail freight i. Average fuel consumption rates of diesel locomotives and estimated freight train km and the total tonne km rail freight moved. f. Ferry freight and other marine freight transport i. Allocated between passengers and freight on the basis of tonnages transported, taking into account freight, vehicles and passengers. ii. Fuel consumption rates for engine power and speed while cruising at sea associated with different vessels. The factors presented in Table 31 refer to gCO2 per deadweight tonne km.

At this stage within the development of enlighten, we do not report on:

1. packaging; 2. chemicals; 3. some secondary processes and operations storage or warehousing; 4. transport loading and return journeys; or

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Key Assumptions

Lifecycle Diagram

The following diagram outlines the life cycle stages and process steps that can be considered in calculating the lifecycle emissions with enlighten. Impacts relating to climate change only are covered within the calculations.

Energy and fuels CO2 emission to air

Raw material Water Waste to landfill manufacture

Chemicals Waste to recycling

Energy and fuels CO2 emission to air Transport Distribution

Waste product Packaging material

Energy and fuels CO2 emission to air

Water Processing Waste to landfill

Chemicals Waste to recycling

CO2 emission to air

Customer and Energy and fuels Waste to landfill assembly

Waste to recycling

Energy and fuels

Transport Usage CO2 emission to air

Inputs considered Maintenance and repair

Remanufacture Outputs considered

Energy and fuels End-of-life CO2 emission to air Inputs / outputs not considered Transport

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CONTACT DETAILS

Document produced by: Dr Phil Reeves – Managing Director, Econolyst Ltd [email protected]