Virtual Engineering Industrie 4.0 – an Overview Dr. Markus Damm, Fraunhofer Institute IESE [email protected] 1 © 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! 3 © 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 4 © 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 5 © 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 6 © 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? 9 © Fraunhofer IESE The Industrie 4.0 networking paradigm shift… 10 © Fraunhofer IESE …and today‘s automation protocol reality EtherNet/IP Modbus RTU AS-i Profibus EtherCAT CIP BSAP ControlNet DeviceNet DF-1 Ethernet Powerlink TTEthernet Ethernet Global Data Fieldbus PieP OpenADR OSGP PROFINET IO Sinec H1 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 11 © Fraunhofer IESE Industrie 4.0 – the standardization challenge • 2013 survey in German industry • From: Recommendations for implementing the strategic initiative INDUSTRIE 4.0 12 © 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 14 © 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,… 15 © 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 16 © 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 20 © Fraunhofer IESE.