The Role of Industry 4.0 in Liberty House Group's Strategic Green Steel

The role of Industry 4.0 in Liberty House Group’s strategic green steel vision Wednesday, 6 June 2018 Eric Vitse Chief Technology officer GFG Alliance/Liberty House Group Shane Murphy- Simon Pike- Andrea Fontana: Liberty steel 4.0 incubators

www.gfgalliance.comwww.gfgalliance.com June 2018 1 Agenda

• GFG Alliance • 4.0 fits with our strategic green steel vision • Areas of opportunity for applying cyber physical systems in our existing plants • 4.0 requirements • Example of 4.0 development programs • Already a wide set of practical examples 2

www.gfgalliance.com 2 3 www.gfgalliance.com 3 GFG Alliance

GFG Alliance

Ownership PKG SKG SKG PKG/SKG PKG/SKG Liberty House SIMEC Group Wyelands JAHAMA GFG Foundation Group

Liberty Commodities Liberty Industries

Liberty Engineering Liberty Aluminium Liberty Steel 4

www.gfgalliance.com 4 GFG Alliance Global Footprint

• The GFG Alliance has a presence across 30 countries. • Global turnover of c.US$13bn • Net assets of c.US$2.3bn • Global head offices located in: • London • Dubai • Singapore • Hong Kong • Sydney

5 www.gfgalliance.com 5 GFG Alliance GFG Alliance in Numbers

www.gfgalliance.com 6 4.0 FITS WITH OUR STRATEGIC GREENSTEEL VISION

▸ Our business is experiencing the early stages of an economy wide disruptive change to the 4th generation of industrialisation - cyber-physical systems for business

▸ Liberty house group GREENSTEEL :

• A high efficient production process aiming at first time first choice • A green process using as much as possible renewables raw material as scrap recycling , energy and achieving high steel quality standards • A high level of integration in the complete supply chain and to ensure integrity of final components at customers and optimised lead time. • A breakthrough in terms of automation and robotics aiming at safer manufacturing • A significant improvement in throughput and costs in operations

▸ New context : • Every sensor and actuator can now be optimised and networked • Advancements in big data and powerful analytics meaning that systems can trawl through the huge sets of data and produce insights that can be acted upon quickly. • More solutions providers are available and approaching our group • New dynamics in terms of innovation including in the robotics/automation sectors. • Downstream integration moves our group towards smart factories. 7 • Some of our existing mills technology provides a good foundation for optimisation (as examples one steel Australia, UK specialty steel)

www.gfgalliance.com 7

SOME AREAS OF OPPORTUNITY FOR APPLYING CYBER PHYSICAL SYSTEMS IN OUR EXISTING PLANTS • ‘Smart’ predictive maintenance – sense & predict • ‘Smart’ safety systems – sense & predict • Process analytics and optimisation – collate, analyse and optimise Modern data technologies could allow us to access real-time information more efficiently and to be able use data in process models and self-learning systems aimed to improve process adherence and product quality • ‘Smart’ sensors and actuators – sense & adjust • More robotization and automation • Autonomous vehicles

www.gfgalliance.com 8

Process analytics and optimization opportunities: Horizontal integration: Feed-forward dynamic control

EAF Sec Steel Casting Remelt Rolling Heat treat Inspect Despatch

Excellent bar

Processing Other issue customer

Processing Excellent issue bar

9 Excellent Perfect process and product control allows expansion of funnels bar

www.gfgalliance.com 9 4.0 Rationale in EAF Steelmaking

• Interrogating our data in an efficient and timely manner could really help to improve our processes and therefore our business performance. This can be done by: • Identifying variations in processing identified through process measurement that may influence decisions on later product processing. • Better understanding could help the steel plant to focus on correcting the root cause of process or product deviation and improve manufacturing yield. • One of the main issues that can impact on our customer service is the need to take remedial actions and rework on products during later manufacturing in order to achieve the customer specified properties. • Modern data technologies could allow us to access real-time information more efficiently and to be able use data in process models and self-learning systems aimed to improve process adherence and product quality. • Potential digital twin of the steelmaking processes where we cannot directly measure due to the operating conditions such as inclusion distributions and evolution in ingot casting and impact on 10 finished product properties.

www.gfgalliance.com 10 4.0 REQUIREMENTS FOR SOUND DEVELOPMENT WITHIN OUR GROUP Industry 4.0 will ultimately transform our business and it is clear that it will require big data management More and more data will come from ‘smart sensors’ connected to fast, efficient, resilient and secure networks.  We need to create a developmental framework that uses our organisations existing knowledge and expertise, and use external resources to assist when needed. Develop policies and standards for the minimum functionality and connectivity of new equipment. Identify and implement ‘quick wins’ that clearly demonstrate the value of digitalization of the business for the purpose of getting the support of the senior executive management. Develop a relationship with businesses and institutions that are the leading thinkers in the future of digitalization i.e. big data and scalable analytics. 11 www.gfgalliance.com 11 4.0 DEVELOPMENT PROGRAM EXAMPLE: EAST COAST MILLS - INDUSTRY 4.0 JOURNEY

GETTING STARTED GETTING ORGANISED GETTING INDUSTRY 4.0 How did we begin Where are we now? FIT/READY on Industry 4.0? What lies ahead?

Focus on specific East Coast 2018 2017 April 2017 October Selected optimising projects implemented and evaluated in Mill International benchmarking visits identified cyber Quick wins identified East Coast Mills physical systems applications emerging in steel industry projects Industry 4.0 implementation framework finalised Workstream capability developed 2017 May-July Workstreams identified and teams formed IT/OT structure developed Industry, academic and supplier experts consulted. Steering process initiated:- Standards & protocols developed 2017 August □ Governance, standards & protocols SME networks expanded Automation theme for 2017 Best Practice Conference Share □ Capability, team development & recruiting Line team participation developed Internal SMEs convened and Industry 4.0 implementation learning

framework developed ‘Industry 4.0 Fit/Ready’ integrated with Optimising/Expanding Meltshop/Mill capacity 100 day Beyond 2019 East coast mills current state appraised:- plan stream Industry 4.0 capability built into to org and systems □ Networks/security structures, operating culture and operations strategies □ Data & Data Management 2017 November onwards:- East Coast Mill learning shared through:- □ Process Automation (Field Devices, PLC, SCADA) Levels Workstreams begin activities □ Supply chain 0, 1 and 1.5 □ Stream definition & scoping □ Best practice networks □ Intelligent Automation (analytics, MES, advanced automation) Levels 2 and 3 □ Projects identified & initiated 12 www.gfgalliance.com 12 Metallurgical properties Horizontal integration : 4.0 journey for Liberty UK specialty steel

EAF Sec Steel Casting Remelt Rolling Heat treat Inspect Despatch

Value in use Value in use Magmasoft – Offline scheduler Offline pbp Offline scheduler Through proc

model model casting model scheduler analysis line models line - Magmasoft – Present

Off remelt model Med term Long term Metallurgical Metallurgical Metallurgical Metallurgical Metallurgical Metallurgical

model model model model model model

Process model Auto vetting Auto vetting Auto correction Auto correction Auto correction process model process model process model Level 2 Level process model process model

Optimisation Optimisation Optimisation Optimisation Optimisation Optimisation

routines routines routines routines routines routines

Auto data Auto data Auto data Auto data Auto data Auto data Auto data

capture capture capture capture capture capture capture Level 1 Level

In-line LIBS In-line LIBS In-line profile Temperature UST Trackable gauge control labels/tags

Temperature Temperature Metallurgical Surface profiling Sensors control structure Laser alignment 13

Full feed-forward/feed-back capability www.gfgalliance.com 13 Summary

. Industry 4 or 4th Generation factory has huge potential for Liberty Steel . Very broad subject – but with massive benefits to: . Raw materials flexibility . Mass customisation . Process problem solving and reliability improvement . Product reliability and property precision . Delivery precision . Throughout supply chain and in customers . Requires modern hardware (computers) . Strengthening of the process modelling capability in R&D . Strengthening of automation support for implementation (fte) . Development of novel sensors and measurement – and ability to build for plant application. 14

www.gfgalliance.com 14 Liberty will leverage Australia and UK Industrial Approach

www.gfgalliance.com 15 AUSTRALIA’S PRIME MINISTER I 4.0 TASKFORCE

The Prime Minister's Taskforce was formed following the release of the report of the Australia-Germany Advisory Group in November 2015. The Advisory Group recommended collaboration between government and industry in both countries on Industry 4.0, including initiating a collaborative approach to the development of global Industry 4.0 standards. The Prime Minister’s Industry 4.0 Taskforce has now signed a cooperation agreement with Germany’s Plattform Industrie 4.0.

"Australia should see the fourth industrial revolution as an opportunity. If we establish a broad-based capability to use global engineering and manufacturing platforms based on advanced materials, the often spruiked access by our SME’s to global supply chains are more a reality now than they have been at any time in the past" 16 Jeff Connolly, Chair of the Prime Minister’s Industry 4.0 Taskforce

www.gfgalliance.com 1616 EXAMPLES OF 4.0 AT LIBERTY HOUSE GROUP : APPENDIXES

www.gfgalliance.com 17 EXAMPLES OF I 4.0 AT LIBERTY ONESTEEL AUSTRALIA Big Data Analysis with Swinburne University of Technology Ladle Eye Monitoring and Regulation with Swinburne University of Technology Autonomous and Remote Mining operations Scrap Density Laser Scan at Laverton Automatic Taphole Sanding and Deskulling Automatic Cranes and Yard Management System at Laverton and Sydney CCM Cut-in-Weight and Cut-in-Length System at Laverton and Sydney CCM Mould Oscillation Monitoring System Bundle Bar Counter at Laverton Bar Mill Automatic Jointer for EAF Electrodes EAF Slag Door Pusher at Laverton 18 EAF WiFi Thermocouples at Laverton www.gfgalliance.com 18 BIG DATA ANALYSIS WITH SWINBURNE UNIVERSITY

A program to apply Big Data Analysis methodology to a specific problem was started by Liberty OneSteel and a team of specialists of Swinburne University of Technology, Melbourne. The project identified was the “development of a data-driven real-time prediction solution for billet sticking” This project includes the following tasks: Study and understand the existing the data collection system utilized in Liberty OneSteel through a close consultation and workshops. Investigate possible ways to collect relevant data that has potential to have correlation with the billet sticking at the CCM. 19 www.gfgalliance.com 19 BIG DATA ANALYSIS WITH SWINBURNE UNIVERSITY Outcomes of the project: Develop a data collection system for capturing (1) high quality production process and runs data, (2) data from the relevant production machines and quality control equipment on the production floor, and (3) the relationships of such data. Develop a data analysis tool that will (1) analyse all captured data to compute the probability of blockage and sticking of the steel billets in the real-time, (2) predict such events, and (3) identify contributing factors. This will include the development of a predictive model that can potentially predict possible billet sticking. Conduct a trial of these on the plant to collect sufficient data for analysis and validate the data analysis and prediction tool. Contribute to Liberty OneSteel’s work place transformation by integrating people capability with emerging predictive analytics and data-driven IoT technologies via 20 breakthrough research to build smarter manufacturing plants.

www.gfgalliance.com 20 LADLE EYE MONITORING AND REGULATION Industrial trials are underway at the Laverton Meltshop together with Swinburne University in order to test the effectiveness of sound analysis and digital image analysis on ladle eye phenomena. The aim is to develop a system that automatically adjusts the Argon flow in function of the field signals.

21 sound analysis digitalised ladle eye image www.gfgalliance.com 21 AUTONOMOUS AND REMOTE MINING OPERATIONS

Autonomous and remote operation technologies are transforming Australian mining. While these two streams represent different levels of automation, together they allow sophisticated integration of mining systems delivering major efficiencies in production as well as fundamentally changing the mining process. SIMEC Mining (Liberty’s mining arm) are currently evaluating the use of this technology for future projects.

www.gfgalliance.com 22 SCRAP DENSITY LASER SCAN

Trials were conducted at the Laverton scrap yard using laser scan technology to determine the density of incoming scrap

www.gfgalliance.com 23 AUTOMATIC TAPHOLE SANDING AND DESKULLING

At Laverton Meltshop the EAF taphole sanding operations are fully automated. A remote camera positioned on the roof monitors the taphole after tapping. The sanding hopper is automated. A deskulling ram is remotely operated in case of need.

24 skull over the taphole ram activated skull removed

www.gfgalliance.com 24 AUTOMATIC CRANES AND YARD MANAGEMENT SYSTEM

Currently looking at automating scrap yard, furnace charging, billet yard and warehouse cranes.

www.gfgalliance.com 25 CUT-IN-WEIGHT AND CUT-IN-LENGTH SYSTEM Making use of laser technology to control the billet cut-in-length. Make use of weight signal to adjust the cutting length. System in use at Laverton and Sydney Meltshops Advantages: Improves the cutting precision of the billet Improves the overall yield (meltshop and rolling mill combined)

26 www.gfgalliance.com 26 CCM MOULD OSCILLATION MONITORING SYSTEM

The CCM Monitoring System detects the mould oscillation frequency, amplitude, phase angle, deflection (both horizontal and vertical), strip time, strip rate, deflection rate and trace of oscillation table. Tool currently used at Sydney, Whyalla and being purchased at Laverton Ramon Mould Oscillation Monitoring System depicted

27 www.gfgalliance.com 27 BUNDLE BAR COUNTER An automated vision system was installed at the Laverton Bart Mill to ensure direct delivery to customer with the ability to provide made to order length product with an agreed product piece count tolerance.

www.gfgalliance.com 28 AUTOMATIC JOINTER FOR EAF ELECTRODES

Automatic jointer for EAF electrode currently under evaluation at the Sydney Steel Mill This solutions prevents strains and physical injuries of operators Avoids the usage of torque wrenches Removes all personnel from the furnace floor while changing electrodes

29 www.gfgalliance.com 29 EAF SLAG DOOR PUSHER

An automated robotic arm substituted the man-operated forklift to maintain the EAF slag door at the Laverton Meltshop. The robotic arm was designed in house.

30 www.gfgalliance.com 30 EAF Wi-Fi THERMOCOUPLES

All EAF thermocouples to the furnace hearth and water cooled elements at the Laverton EAF communicate via WiFi to the SCADA system.

31 www.gfgalliance.com 31 Example at UK specialty steel for aerospace part