Virtual Engineering Industrie 4.0 – an Overview

Dr. Markus Damm, Fraunhofer Institute IESE [email protected]

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© Fraunhofer IESE Industrie 4.0 – where does it come from?

§ The term „Industrie 4.0“ was coined in 2011 § Key concept in the German government’s high-tech strategy § Basically synonymous to “Industrial Internet (of Things)” § Short for “4th industrial revolution”

Late 18th century Late 19th century 1970s/1980s Early 21st century

water- and steam- electrification, mass Programmable Internet of Things, cyber- powered machines production Logic Controllers physical systems 2

© Fraunhofer IESE Industrie 4.0 – what does it mean?

§ Industrie 4.0 is typically associated to… § …higher infusion of IT and Big Data in automation § …open, highly interconnected automation systems § …networks spanning from factory floor to headquarters § …flexible, reconfigurable production (lot size 1) § …embedded à cyber-physical

§ It‘s not so much about new technologies… § …but about the smart combination of existing technologies!

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© Fraunhofer IESE Industrie 4.0 – the expected general benefits

§ Flexibility – production lines can be reconfigured easily Þ Better adoption to market needs § Networked Production – factories of one company can be connected to each other, and to suppliers Þ Optimized utilization of capacities, less need for storage § Big Data – in a highly interconnected automation system, a lot of data can be collected Þ Enables applications like predictive maintenance § Smart Products – the products produced are cyber-physical systems themselves Þ Products can tell the production how to produce them, data can be collected from field usage

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© Fraunhofer IESE Example use case – car production

§ A company has two factories for car type X and car type Y, respectively § the car type X currently sells well, but Y doesn‘t § Solution: Use the Factory for Y to produce X § But: This does not work today, the change takes too much time – if it is feasible at all!

§ With Industrie 4.0: § Production systems can be easily re-configured § Machines can be replaced or added in a plug-and-play manner § Production lines might even adapt themselves

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© Fraunhofer IESE Example use case – networked with supplier

§ A certain factory can produce a wide range of products/variants § But: To be able to react to new orders quickly they have to store a lot of different supply material § This needs a lot of space, and costs money

§ With Industrie 4.0: § The factory and the supplier are networked § With every new order, the supplies needed are automatically determined § The supplier is contacted automatically for the orders

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© Fraunhofer IESE Example use case – predictive maintenance

§ A machine in a production line is worn out or broken § Replacement parts or a new machine have to be ordered § Repairs have to be done § … all the while the production is stopped

§ With Industrie 4.0: § A lot of sensor data can be collected from the production § By analyzing this data, looming problems can be detected § e.g. increased lubricant use or machine vibrations § Learning, matching data to past events § Replacements can be ordered automatically 7

© Fraunhofer IESE Example use case – data from products in the field

§ A company’s product sales drop, competitive products sell better § To find out why, analysis is needed § …of the competitor‘s products § …of the own product – does it have unknown flaws ? § …of the product‘s usage in the field

§ With Industrie 4.0: § The product is a cyber-physical product § Usage data is transmitted to the producer § With this data, the product can be improved § Also: New business models might be enabled with this data 8

© Fraunhofer IESE Is all this really new?

§ “…I already use minimal storage because I work tightly with my suppliers!” § “…I already collect data from the cell phones / cars I produce!” § “…I already offer a lot of product variants – my catalogue has 1000 pages!”

§ …that‘s why it‘s a revolution – it‘s already happening! § So why these concerted Industrie 4.0 efforts?

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© Fraunhofer IESE The Industrie 4.0 networking paradigm shift…

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© Fraunhofer IESE …and today‘s automation protocol reality

EtherNet/IP RTU AS-i EtherCAT CIP BSAP ControlNet DeviceNet DF-1 TTEthernet Ethernet Global Data PieP OpenADR OSGP PROFINET IO SERCOS III Modbus Plus RAPIEnet SSCNET Honeywell SDS MelsecNet SERCOS interface MECHATROLINK GE SRTP DirectNet MPI MTConnect CC-Link Industrial Networks SynqNet Modbus PEMEX SafetyBUS p

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© Fraunhofer IESE Industrie 4.0 – the standardization challenge

• 2013 survey in German industry • From: Recommendations for implementing the strategic initiative INDUSTRIE 4.0

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© Fraunhofer IESE How to solve the Industrie 4.0 networking problem?

§ …agree on a common standard? § Candidates which are discussed: § MQTT ? § OPC UA (+TSN for real-time) § Problem: Legacy systems § Especially Small & medium enterprises (SMEs) can’t afford to change everything at once

§ Alternative approach: Use a common middleware application § It can work on top of many automation protocols I40 middleware proprietary § This approach is taken in the BaSys project protocol 13

© Fraunhofer IESE Industrie 4.0 and security

§ Industrie 3.0 already has security issues (e.g. Stuxnet) § But: Industrie 4.0 is not a security solution… § …it‘s a security challenge! § The Industrie 3.0 heterogeneity actually somewhat helps with security. § Decreasing this heterogeneity potentially introduces vulnerabilities! § Generally: Raising interconnectedness introduces vulnerabilities § Also: Issues regarding Privacy and data ownership

Þ The Industrie 4.0 research must address these issues from the start § In Germany: Project IUNO

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© Fraunhofer IESE Digital Twins – an important Industrie 4.0 concept

§ …a.k.a. digital shadow, digital angel, virtual representation … § Idea: Every asset that is part of the production has a digital representation: § sensors and actuators § machines § production lines § the products themselves

§ They contain all the relevant data § E.g. blueprints, parameters, usage history,…

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© Fraunhofer IESE The Industrie 4.0 Administration Shell

§ Concept developed by the association of the German electrical industry § The administration shell is the main contact for every Industrie 4.0 application § Access to the digital twin of the asset § Access to the asset (e.g. the machine) itself

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© Fraunhofer IESE AutomationML – a possible Industrie 4.0 data standard

§ XML-based data format for information exchange of plant data § IEC 62714 § Developed mainly in Germany (e.g. Daimler, ABB, Siemens) starting 2006 § Currently based on 3 existing XML-based formats: § CAEX – Topology. § COLLADA – Geometry & Kinematics § PLCopen XML – Process Logic § Other formats might be integrated in the future

Source: www.automationml.org 17

© Fraunhofer IESE The RAMI 4.0 reference architecture for Industrie 4.0

© ZVEI and Plattform Industrie 4.0 18

© Fraunhofer IESE Example: BaSys in the RAMI 4.0 Model

© ZVEI and Plattform Industrie 4.0 19

© Fraunhofer IESE Conclusion

§ Industrie 4.0 is already happening § New or enhanced production paradigms § New business models § But: To make it work, common standards are needed § Protocols like OPC UA and MQTT are favored by some § Data standards like AutomationML § Reference architectures like RAMI 4.0 § Middleware approach Þ BaSys (future) § It must be possible to introduce Industrie 4.0 gradually! § Industrie 4.0 is a security challenge

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© Fraunhofer IESE