Smart Ecosystems: An Enabler for Future Innovations

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1 Smart Ecosystems: An Enabler for Future Innovations Prof. Dr. Dieter Rombach Fraunhofer IESE Kaiserslautern, Germany SEC Special Seminar: Software Engineering and Business Innovation at the Era of IoT Tokyo,

2 AGENDA Applied Research: The Fraunhofer-Gesellschaft On the way to the Digital Society 2.0 Challenges for Software and Systems Engineering

3 Joseph von Fraunhofer ( ) Researcher Discovery of the Fraunhofer lines in the solar spectrum Inventor Development of new methods for lens processing Entrepreneur Director and partner in a glass manufactory Deutsches Museum Fraunhofer-Gesellschaft Fraunhofer Lines 3

4 Fraunhofer-Gesellschaft, the largest organization for applied research in Europe Applied Research for Economy and Society 2 billion About 23,000 employees 66 institutes and research institutions Research Volume Contracted Research 1.7 billion 2013 About 30% of base funding from federal and state government Above 70% of industry contracts and publicly funded research projects 4

5 Fraunhofer Worldwide Glasgow Gothenburg San José Vancouver London East Lansing Boston Cambridge Plymouth Storrs Maryland Newark Dublin Southampton Brussels Wrocław Paris Vienna Budapest Bolzano Graz Porto Thessaloniki Jerusalem Cairo Dubai Beijing Seoul Sendai Tokyo Bangalore Ampang Singapore Salvador Campinas São Paulo Jakarta Santiago de Chile Subsidiary Center Project Center ICON / Strategic Cooperation Representative / Marketing Office Senior Advisor Stellenbosch Sydney 5

6 Fraunhofer Fields of Research Health and Environment Mobility and Transportation Communication and Information Energy and Resources Safety and Security Production and Services 6

7 Fraunhofer Institute for Experimental Software Engineering Founded in 1996 One of the leading software engineering institutes in Europe and worldwide Over 200 employees Itzehoe Rostock Lübeck Bremerhaven Bremen Hannover Potsdam Berlin Teltow Braunschweig Magdeburg Cottbus Oberhausen Dortmund Halle Schkopau Leipzig Duisburg Schmallenberg Dresden St. Augustin Jena Aachen Euskirchen Chemnitz Wachtberg Ilmenau St. Ingbert Saarbrücken Karlsruhe Pfinztal Ettlingen Stuttgart Darmstadt Würzburg Erlangen Kaiserslautern Fürth Freiburg Kandern Efringen- Kirchen Nürnberg Freising München Holzkirchen 7

8 Our Formula for Your Success 8

9 The Basis of Our Success 9

10 Core Competencies of Fraunhofer IESE for innovative Systems SOFTWARE-ENABLED INNOVATIONS 10

11 Core Competencies of Fraunhofer IESE ES/CPS Smart Ecosystems IS/Mobile SOFTWARE-ENABLED INNOVATIONS 11

12 How do we help? We create evidence! We analyze software and systems to create evidences 12 that enable us to provide sound evaluation results and decision support

13 AGENDA Applied Research: The Fraunhofer-Gesellschaft On the way to the Digital Society 2.0 Challenges for Software and Systems Engineering

14 Integration: A Driver in Private Life 14

15 Integration as Driver for Business Life: Integration Enables Innovation! in Information Systems as well as in Embedded Systems 15

16 Physical Objects Get a Digital Life Physical objects (things, living objects, people) produce data (through observation using sensors) have a history (enabling prediction) are influenced by data (using actuators) context-dependent Location-aware in real time across software system boundaries [Picture from Cheri Ellis] 16

17 [Bosch Software Innovations 2012] 17

18 IT Mega-Trend: Integration Big Data / Data Analytics 18

19 Societal Changes through Smart Ecosystems Digital Society 2.0 Digital Society 1.0 Closed Systems (IS, ES) Open Systems (IS, ES) Integrated Systems Systems of Systems Emergent Systems Cyber- Physical Systems Smart Ecosystems 19

20 Smart Ecosystems A Trend across Domains Industry 4.0 Smart Farming Smart Mobility Smart Ecosystems Smart Health Smart Energy Smart X 20

21 Example: Smart Cars In open ecosystems, the question is no longer What is the customer going to pay for? but Who might be willing to pay? [Roland Berger] 21

22 Example: Smart Farming Preventive error avoidance No standstill during harvesting period Optimized harvest logistics Explicit consideration of various influencing factors Protection of field soil Coordination of agriculture machines Foresighted planning Use of real-time data streams Minimizing fuel consumption Prediction and control of machine routes Automated control of harvesting speed Coordination of agriculture machines and their routes Innovation through connected & integrated software systems and context-dependent & location-based services [CLAAS] 22

23 The Fourth Industrial Revolution Research initiative to answer four major challenges of the modern world Global competition Resources shortages Demographic changes Urbanization Role of software and IT in connected production facilities Presentation of the final report Industry 4.0 at Hanover Fair

24 Example: Smart Production in Industry 4.0 TODAY Which events can be isolated and handled by a service employee? Which errors influence the operation of a complete industry plant? Is there a correlation between the errors? REACTIVE 80% FALSE ALARMS PROACTIVE Compare to history, identify trends, and predict errors 20% QUALIFIED SIGNALS FUTURE Machine-tomachine communication Analysis of machine and surrounding data Estimation of machine s condition Predict errors & maintain machine Avoid downtime Avoid unnecessary maintenance [agendacps] 24

25 Industry 4.0 History Software is the key to innovation and productivity boost Smart ecosystems and integrated cyberphysical systems SPS-based automation technology Assembly-line organization, electrical drives Mechanical production facilities, hydropower, steam engines 25

26 Industry 4.0 Characteristics Vertical Integration throughout control levels [Siemens] We must be able to control a network of plants distributed all over the world as one global factory Horizontal Integration across enterprises The focus of Industry 4.0 is on real-time capable, comprehensive, intelligent, horizontal and vertical networking of people, machines, objects and IT systems for dynamic management of complex systems [Plattform Industrie 4.0; 26

27 Industry 4.0 Vertical Integration Enterprise Distribution Product Development /R&D) Planning Acquisition Production Logistics Service IT, Shared Services Finance, Tax, Legal Vertical Value Creation 20% 80% Digitalization of value chain [PwC 2014] 27

28 Industry 4.0 Horizontal Integration Supplier Enterprise Customer Supplier Chain Planning 86% Cooperation Partners Acquisition Production Logistics Customers Network 24% Horizontal Value Creation Chain/Network Digitalization of value chain [PwC 2014] 28

29 Industry 4.0 Vision: Industry 2025 Flexible and individualized manufacturing Coexistence of open and closed production networks Connected enterprises Work comfort through intelligent assistance systems Competitive advantages of flexible valuecreation networks New business opportunities in connected industry [BMBF: Zukunftsbild Industrie 4.0] 29

30 Industry 4.0 Example Perspectives Manufacturing Process Processing and transport functions Networked Devices Programmable logic controllers, mobile devices, servers, workstations, etc. Reference Architecture Industry 4.0 Software Applications Business management, production management, control and regulation software Product Engineering Production design & dev., planning, engineering, and services The first challenge is to pull together the perspectives represented by different industries and to establish a common approach [Plattform Industrie 4.0; 30

31 Industry 4.0 Expected Benefits Better planning and control (in the production resp. logistics) 80% 15% 5% High customer satisfaction 67% 27% 6% Large flexibility in the products 62% 27% 11% Short Time-to-Market (in the product development) 54% 32% 14% Improvement of quality 49% 35% 16% Individualization of products 46% 34% 20% 0% 20% 40% 60% 80% 100% High Medium Low [PwC 2014] 31

32 Industry 4.0 Potential Growth (Germany) Industry Sector Gross Added Value [Bn. ] Potential through Industry 4.0 Yearly Increase * Chemical Industry % 2.12% Automotive and Car Parts Machine and Plant Construction % 1.53% % 2.21% Electrical Equipment % 2.21% Agriculture and Forestry % 1.17% Inform. and Comm. Tech % 1.17% Total Potential % 1.74% * Growth due to Industry 4.0 only (economic growth excluded) [BITKOM 2014] 32

33 Industry 4.0 Key Challenges of Implementing Industry 4.0 Standardisation 147 Process/work organisation 129 Product availability 98 New business models 85 Security know-how protection 78 Lack of specialist staff 70 Research 64 Training and CPD 42 Regulatory framework Survey (BITKOM, VDMA, ZVEI 2013): 278 companies mainly from the machinery and plant manufacturing industry. 205 companies < 500 employees. 33

34 AGENDA Applied Research: The Fraunhofer-Gesellschaft On the way to the Digital Society 2.0 Challenges for Software and Systems Engineering

35 Trend in Digitalization of Product- and Service Portfolios The Key to Sustainable Success 29% Digitalization Level 34% + 50% 79% high medium low 37% % 7% [PwC 2014] 35

36 Smart Ecosystems Key Challenges for Software and Systems Engineering Complexity Uncertainty Diversity Safety & Security Smart Data Usage 36

37 Key Challenges of Smart Ecosystems Complexity Smart Ecosystems are the most complex artifacts created by a human being: dynamics and long lifetime require a high degree of complexity reduction This requires: Model-based engineering approaches Scalable architectures Mature development processes 37

38 Key Challenges of Smart Ecosystems Diversity Smart Ecosystems comprise and integrate diverse systems and stakeholders across companies and domains This requires: Interoperable architectures Standardization Quality of Service (QoS) guarantees 38

39 Key Challenges of Smart Ecosystems Uncertainty A system within a Smart Ecosystem must be able to deal with an uncertain environment: players and how to interact with them may change This requires: Flexible architectures Adaptable systems Certifiable runtime qualities Simulation approaches for connecting development and runtime 39

40 Key Challenges of Smart Ecosystems Safety & Security In Smart Ecosystems, highly critical embedded systems are integrated with sensible information systems: the resulting ecosystem needs to address safety and security issues This requires: Integrated security/safety models Context-dependent, integrated data usage control (trust and acceptance) Isolation of critical system parts (e.g., software cages ) 40

41 Key Challenges of Smart Ecosystems Smart Usage of Big Data How are your capabilities? Opportunities are huge! 41

42 Key Challenges of Smart Ecosystems Smart Usage of Big Data In Smart Ecosystems, big data needs to be processed across companies to enable joint value chains and business models This requires: Innovative business models Big data strategies (goals, competencies, and technologies) Approaches for managing data quality ( garbage in, garbage out ) Integrated data usage control Data Velocity Data Variety MB GB TB PB Data Volume [from 42

43 TAKEAWAYS Companies and society can strongly benefit from Smart Ecosystems Opportunity and threat at the same time for companies Software is the USP Context sensitivity, intelligence, and added value are delivered by software Processing power and communication bandwidth are mandatory prerequisites Software Engineering is the key to success Achieve the right goals at the right time with the right level of quality At development time and at runtime Challenges in Smart Ecosystems require guaranteed qualities Fraunhofer IESE provides strong competencies for these challenges

44 THANK YOU!