Industrial Data Space

1. © Fraunhofer Prof. Dr. Boris Otto Fraunhofer IML/ISST TU Dortmund University Birmingham · April 14th, 2016 THE INDUSTRIAL DATA SPACE

2. © Fraunhofer 2 AGENDA  Towards a »Smart Service Welt«  »Industrie 4.0« and Smart Manufacturing  The Industrial Data Space

3. © Fraunhofer 3 Innovative business models combine digital services and lot size 1 production Product and Production Strategy at adidas In-Store ProductionSmart Service »Runtastic« Source: Handelsblatt, August 6, 2015, No. 149; http://www.adidas-group.com/de/medien/newsarchiv/pressemitteilungen/ 2015/adidas-gruppe-erwirbt-runtastic; image source: adidas Group (2016).

4. © Fraunhofer 4 Successful value propositions are becoming increasingly hybrid Product-Service Bundling at adidas Image sources: otto.de (2015), techglam.com (2015), soccerreviews.com (2015), appfullapk.co (2015). Time »Hybridity« Physical Product (Running Shoe) »Traditional Service« (Work-Out Monitor) Digital Service (Runtastic)

5. © Fraunhofer 5 Industrial machinery manufacturers are offering app stores on top of their tangible products Hybrid Products at TRUMPF Image sources: ihs-gmbh.de (2016); silicon.de (2016). Digital Value-Added ServiceTool Machine as a Tangible Product

6. © Fraunhofer 6 Digital value propositions follow a platform logic Digital Business Architecture Sources: Working Group Smart Service Welt (2015). Principles of the Platform Economy»Smart Service Welt« Architecture  Services can be separated from physical platforms  Architectural layers are de-coupled  Products turn to platforms - and vice-versa  Ecosystems form around platforms  Innovation happens in co-opetition modes SMART PRODUCTS SMART SPACES SMART DATA SMART SERVICES

7. © Fraunhofer 7 Agricultural machinery manufacturers are driving comprehensive digital farming solutions Digital Business Ecosystems Image sources: wiwo (2015), traction-magazin.de (2014). Source: Beecham Research Ltd. (2014). Players in the Food & Farming EcosystemDigital Farming Digital Farming Ecosystem Machine Providers Crop Science Companies Farmers Wholesale Technology Providers Influencers

8. © Fraunhofer 8 Smart services are a response to changing customer demands Smart Service Welt End-to-End Customer Process Individualization Ubiquitous Service Availability Information Transparency Source: Working Group Smart Service Welt (2015).

10. © Fraunhofer 10 Industrie 4.0 is a response to these changing requirements Evolution of Production Systems Source: Koren (2010), cited in Bauernhansl (2014). Image sources: https://en.wikipedia.org (2015), https://www.impulse.de (2015), audi.de (2015), o2.co.uk (2015), computerbild.de (2015). Production Volume per variant No. of Variants 1850 1913 1955 1980 2000 Ford Model T VW Beetle Production Audi Configurator Mass Production Individualization »Sharing Economy« Complexity Globalization iPhone 3D Printed Car

11. © Fraunhofer 11 In the Industrie 4.0 global material and information flows are closely aligned at all times Banana Supply Chain Enabled by Maersk and Ericsson Solution Components  Monitoring of climate conditions in oversea containers  GSM and satellite communication Business Benefits  Improved ripeness level of bananas in stores  Improved port operations  Improved fuel consumption and carbon footprint balances »Banana Supply Chain« Source: Maersk, Ericsson (2014); image source: jnfoxandsonsltd.co.uk (2016). Legend: GSM – Global System for Mobile Communications.

12. © Fraunhofer 12 In the Industrie 4.0, production systems are getting autonomous Solution Components  No fixed assembly line  Close integration of pre and serial production  Autonomous AGVs – no fixed transport systems Business Benefits  Increased flexibility and agility  Coping with complexity through self- controlled processes R8 Production at Audi Source: Audi (2016); image source: blog.audi.de (2016). Legend: AGV – Automated Guided Vehicle.

13. © Fraunhofer 13 In the Industrie 4.0 devices in the warehouse are getting smart flexibility Solution Components  Autonomous navigation in the shelf  No lift needed  Flexible use of multiple vehicles Business Benefits  Functional and cost advantages compared to state-of-the-art  Increased flexibility of storage systems  Reduced fixed costs  No bottleneck through lift, thus reduced storage cycle times RackRacer Developed at Fraunhofer IML Source: Fraunhofer IML (2014); image source: Fraunhofer IML (2014).

14. © Fraunhofer 14 Industrie 4.0 is not an end in itself, but a response to changing market requirements Industrie 4.0 at Audi Individualization of customer demands ↑ Number of models, variants, features ↑ Product life-cycles ↓ Globalization of processes ↑ Process and product complexity ↑ Cost targets ↗ Decision needs (strategic, tactical, operational) ↑ »Autonomization« of manufacturing ↑ Real-time information availability ↑ Interoperability of production systems ↑ Market and Customer Demands Manufacturing and Logistics Implications and Needs for Action Industrie 4.0

16. © Fraunhofer 16 Smart Data Management is a key capability for Industrie 4.0 Smart Manufacturing and Smart Services Public Data Data from the Value Chain Commercial Services Industrial Services Individualization End-to-End Customer Process Ecosystem Ubiquity Smart Data Management Interoperability Human-Machine- Collaboration Autonomous Systems Internet of Things Customer Production Networks Logistics Networks Smart ServicesDataSmart Manufacturing Information flow Material flowLegend:

17. © Fraunhofer 17 Key requirements determine the Industrial Data Space A Network of Trusted Data Sovereignty Data and ServicesTrustworthiness Certified Members Decentralization Federated Architecture Openness Governance Common Rules of the Game Scalability Network Effects Ecosystem Platform and Services Security Data Exchange Neutral and User-Driven

18. © Fraunhofer 18 Company A Internal IDS Connector Upload / Download / Search Internet Industrial Data Space Broker Clearing RegistryIndex AppsVocabulary Industrial Data Space App Store External IDS Connector Upload Download Upload / Download Company B Internal IDS Connector External IDS Connector Third Party Cloud Provider The component architecture follows decentralized design principles The Industrial Data Space

19. © Fraunhofer 19 The Industrial Data Space materializes via a set of apps Functional Frame of Reference Industrial Data Space App Store Basic Data Services Provisioning Data Service Management and Use Vocabulary Management Software Curation Data Provenance Reporting Data Transformation Data Curation Data Anonymization Data Service Publication Data Service Search Data Service Request Data Service Subscription Vocabulary Creation Collaborative Vocabulary Maintenance Vocabulary/Schema Matching Knowledge Database Management Software Quality and Security Testing Industrial Data Space Broker Data Source Management Data Source Search Data Exchange Agreement Data Exchange Monitoring Data Source Publication Data Source Maintenance Version Controlling Key Word Search Taxonomy Search Multi-criteria Search »One Click« Agreement Data Source Subscription Transaction Accounting Data Exchange Clearing Data Usage Reporting Industrial Data Space Connector Data Exchange Execution Data Preprocessing Software Injection Remote Software Execution Data Request from Certified Endpoint Usage Information Maintenance (Expiration etc.) Data Mapping (from Source to Target Schema) Secure Data Transmission between Trusted Endpoints Preprocessing Software Deployment and Execution at Trusted Endpoint Data Compliance Monitoring (Usage Restrictions etc.) Remote Attestation Endpoint Authentication

20. © Fraunhofer 20 The development is framed within an overall Industrie 4.0 architectural model Industrial Data Space Architecture Automotive Electronics Services Logistics Manufacturing Life Sciences Smart Service Domains Smart Services and Products »Smart Data Services« (Alerting, Monitoring, Data Quality etc.) »Basic Data Services« (Data Fusion, Mapping, Aggregation etc.) Internet of Things ∙ Broadband Infrastructure ∙ 5G Real-time Scenarios ∙ Sensors and Actuators ∙ Devices ArchitectureLayers INDUSTRIAL DATA SPACE

21. © Fraunhofer 21 Multiple use scenarios are emerging on top of the Industrial Data Space Vertical Data Space Ecosystems Image sources: Johns Hopkins University (2016), Umweltbundesamt (2016), Smellgard, Schneider & Farkas (2016), ITS International (2016). Material Sciences Energy Life Sciences High Performance Supply Chains Traffic Management Exchange of material and product data across the entire lifecycle from research and development to decommissioning Shared use of condition data from operations for predictive maintenance of wind energy plants Shared, federated data platform for development and testing of pharmaceutical products Exchange of quality data for transport items along the entire supply chain Use of traffic management data for innovative services in the car and to better control traffic INDUSTRIAL DATA SPACE

22. © Fraunhofer 22 Kick-started by German user companies, the initiative is aiming at an international footprint Industrial Data Space Association

23. © Fraunhofer 23 Industrial Data Space Video http://www.fraunhofer.de/de/forschung/fraunhofer-initiativen/industrial-data-space.html

24. © Fraunhofer 24 Prof. Dr. Boris Otto Fraunhofer IML & ISST TU Dortmund University Boris.Otto@iml.fraunhofer.de https://de.linkedin.com/pub/boris-otto/1/1b5/570 https://twitter.com/drborisotto https://www.xing.com/profile/Boris_Otto http://www.researchgate.net/profile/Boris_Otto http://de.slideshare.net/borisotto Thank you very much for your attention! Your Speaker

25. © Fraunhofer Prof. Dr. Boris Otto Fraunhofer IML/ISST TU Dortmund University Birmingham · April 14th, 2016 THE INDUSTRIAL DATA SPACE