Digitalisation as day-to-day-business

Transcription

1 Digitalisation as day-to-day-business What is today feasible for the company in the future Prof. Jivka Ovtcharova INSTITUTE FOR INFORMATION MANAGEMENT IN ENGINEERING Baden-Württemberg Driving force for the fourth industrial revolution in Germany I Dialogue with South Korea I Seoul I September 9 th 2016 Karlsruhe Institute of Technology (KIT) The Research University in the Helmholtz Association

2 Digitalisation as day-to-day-business What is today feasible for the company in the future Prof. Jivka Ovtcharova INSTITUTE FOR INFORMATION MANAGEMENT IN ENGINEERING Baden-Württemberg Driving force for the fourth industrial revolution in Germany I Dialogue with Japan and South Korea I September, 2016 Karlsruhe Institute of Technology (KIT) The Research University in the Helmholtz Association

3 Profile in brief 1825 Karlsruhe University (TH) 2009 Karlsruhe Institute of Technology The Research University in the Helmholtz Association 1956 Helmholtz Research Center EDUCATION Focused interdisciplinary RESEARCH collaboration: INNOVATION Division I Division II Division III Division IV Division V Biology, Chemistry and Process Engineering Informatics, Economics and Society Mechanical and Electrical Engineering Natural and Built Environment Physics and Mathematics 3 9 th of September 2016

4 Division III - optional clusters of institutes Product / Production Engineering and Logistics Automation Applied Materials Mechanics & Fluid Machinery Nano and Micro Systems Power Plant Technology Information & Communication Electrical Energy Vehicle Technology Legend: assignment of institutes Mechanical Engineering University Electrical Engineering Helmholtz Association Mixed 4 9 th of September 2016

5 Triad of digitalisation under one roof Institute for Information Management in Engineering at KIT Lifecycle Engineering Solutions Center at KIT Research Division Intelligent Systems and Production Engineering at FZI Research assistants 20 Promotions (1st Advisor) 28 External / Industry Ph.D. students 12 Student assistants 30 EDUCATION RESEARCH INNOVATION 5 9 th of September 2016

6 Engineering 360 KNOWLEDGE GROUP 2 Knowledge Management Engineering Data Modeling and Simulation Human- Maschine Interaction Virtual & Experimental Validation GROUP 3 Smart Immersive Environments (Big) Data Analytics EDUCATION VALUE GROUP 1 Lifecycle Engineering (Engineering) Data Acquisition LIFECYCLE Knowledge Screening RESEARCH INNOVATION Feedback Management Practical Implementation 6 9 th of September 2016

7 Group 1- Lifecycle Engineering Research topics: Strategic Portfolio Planning Product Lifecycle Information Management Model-based Systems Engineering Computer-Aided Design and Simulation Real-time Tooling and Execution Business Process Management Complete data acquisition from multiple unstructured data sources and end-to-end process simulation 7 9 th of September 2016

8 Group 2 - Knowledge Management Research topics: Recording of Various Machine Parameters Control for Balanced Load Distribution Fast Knowledge Extraction Reduced Energy Load Peaks Self Learning Data Analysis Historical Data Processing for Forecasting Energy Consumption Measurement 8 9 th of September 2016

9 Group 3 - Smart Immersive Environments Virtual Reality Engine PolyVR New Interaction Methods for VR/AR Algorithms for Dynamic Virtual Scenes Optimization of Human-Machine-Interaction Multi Dimensional Service Prototyping Extensive 3D-Scanning and Reconstruction 9 9 th of September 2016

10 Lifecycle Engineering Solutions Center: Infrastructure Lifecycle Engineering Solutions Center Content Creation Lab Training and Development with CAx/PLM Virtual Environments Lab Stereoscopic 7-channel VR projection system, ART tracking system Communication Lab Shared space for lectures, project meetings and workshops Value Creation Lab Demonstration and transfer of research results Mixed Reality Lab Mobile projection, ART tracking system and haptic devices Energy Experience Lab Mixed reality platform solutions for energy efficiency Cooperation Lab Spatial and technical cooperation platform Tea Lab Creativity pool 10 9 th of September 2016

11 Main questions What does the digitalisation and Industry 4.0? Why digitalisation everything changes? Where are potentials for the day-to-day business? How it looks in the implementation? What is already possible today? Pictures: Lifecycle Engineering Solutions Center 11 9 th of September 2016

12 Degree of Innovation The challenge Industry 4.0 Industry 1.0 Mass production Industry 2.0 Mass distribution Industry 3.0 World economy Industry 4.0 World society Mechanisation hydro- and steam power Electrification electrical power and vehicle mobility Automation computer and information technology End of the 18th century Beginning of the 20th century Beginning of the 70's Today Cyberisation smart devices and interconnections of business and society Time Source: Industry 4.0 Collaboration Lab 12 9 th of September 2016

13 Transformative businesses Value DIGITAL ANALOGOUS Time Elimination of the local principle in the market, new business models, customer driven value creation Graphics: M. Linse, KPCB, July th of September 2016

14 Reference Architecture Model (RAMI 4.0) Levels of Added Value Lifecycle Phases Network of Functions Consolidation of guidelines, norms and standards Source: Plattform Industrie 4.0, RAMI 4.0 VDI, VDE and ZVEI 14 9 th of September 2016

15 Reference Architecture Model (RAMI 4.0) Levels of Added Value Lifecycle Phases Network of Functions Consolidation of guidelines, norms and standards Source: Plattform Industrie 4.0, RAMI 4.0 VDI, VDE and ZVEI 15 9 th of September 2016

16 Industry 4.0 value creation loop HUMAN EXPERIENCE (Front-Side) Realistic (logical, intuitive) human perception and human-machinecommunication in real time and in space DATA AND TECHNOLOGY (Back-Side) Sensors, Network, Factory Infrastructure, Common Data Models and Algorithms Video: Microsoft HoloLens 16 9 th of September 2016 Source: Deloitte analysis

17 Current practice: Simulated reality Example: Robot simulation What has changed in recent years? Video: General Motors 17 9 th of September 2016

18 Future: Experienced reality Example: Virtual factory planning What does that mean? Video: Lifecycle Engineering Solutions Center 18 9 th of September 2016

19 Future: Experienced reality MENTAL FEEDBACK REAL TIME INTERACTION IMMERSION Natural Human-Computer Interaction Video: InReal 19 9 th of September 2016

20 Human-centred technologies Virtual, augmented and mixed reality Largely accessible high-speed network technologies Entertainment and gaming industry, 3D movies and TVs, Microsoft HoloLens, Oculus Rift, Samsung Gear VR headsets Novel input devices Kinect, Leap Motion, wearables 3D scanning and printing software, services Source: Lifecycle Engineering Solutions Center The next platform where anyone can experience anything they want. Zuckerberg I Source: IndustryWeek, 25 February th of September 2016

21 Human-centred engineering methods Team workplace Decision-oriented Real time processing Space motion interaction 21 9 th of September 2016 Pictures: Lifecycle Engineering Solutions Center

22 Main principal Virtual Engineering - view of the whole, at any moment! Source: Industry 4.0 Collaboration Lab 22 9 th of September 2016

23 Industry 4.0 Collaboration Lab Target Group: Small- and medium-sized companies in Automation, Manufacturing and Services Goal: Strengthening of competitiveness through extensive digitalisation, networking and real-time-enabled solutions for day-to-day business Solution: Test and qualification platform Solving business problems individually and pragmatically, through action Opening Ceremony September 24, 2014 Hannover Messe April 14, 2015 Source: Industry 4.0 Collaboration Lab 23 9 th of September 2016

24 Data are necessary but not sufficient Data Information Knowledge Solution 24 9 th of September 2016

25 Digitalisation as day-to-day business and life 1. Complete data acquisition from multiple unstructured data sources 2. Intelligent data processing for Internet of Things ((IoT) 3. Operational intelligence algorithms for multidimensional big data 4. Automatic data quality check 5. Real-time data analysis and visualization on mobile devices 6. Subject-oriented (human-centered) business processes 7. Continuous qualification of all parties involved living digitalisation for the day-to-day business and life Source: Industry 4.0 Collaboration Lab 25 9 th of September 2016

26 Example: Skill-based propagation Use Case: Skill-based propagation of plug & produce"-devices for smart reconfigurable manufacturing systems Goal: Increase production system flexibility using collaboration of cyber-physical assets that offer different skills Solution: Cloud-based Asset Management System for manufacturing execution Source: Industry 4.0 Collaboration Lab 26 9 th of September 2016

27 Example: Real-time tool management Use Case: Process optimization and networking taking account of resource flows Goal: Optimizing the design and NC processes via web interface due to technological data from the manufacturing process Solution: Real-time readout of machine data Kinematic CAM simulation with real tooling Source: Industry 4.0 Collaboration Lab 27 9 th of September 2016

28 Example: Virtual twin of a milling machine Use Case: Tool configuration and manufacturing Goal: Manual and automatic operation and configuration of tool machines via a 3D Web interface in the Internet Solution: Virtual twin of the machine and automatic or manual control with a haptic device (six degrees of freedom) in real time Source: Industry 4.0 Collaboration Lab 28 9 th of September 2016

29 Example: Virtual twin for factory planning Use Case: Factory configuration and planning Goal: Validation of large-scale integrated production lines in real time Solution: Integration of semantics, kinematics and actuators of 3D models in AutomationML Control over interactive website directly in the virtual world Connection of mobile devices Source: Industry 4.0 Collaboration Lab 29 9 th of September 2016

30 Example: 3D energy experience Use Case: Energy efficiency management in buildings, cities and factories Goal: Learning data analytics and management of energy experience in immersive environments Solution: Real-time coupling of virtual and real building models Web-based energy efficiency measurement in real time and in space Source: Industry 4.0 Collaboration Lab 30 9 th of September 2016

31 Example: Real-time 3D reconstruction Use Case: Scalable 3D acquisition and analysis of objects, tools or components Goal: Generation of exact volume models in real time performing semantic analysis Solution: Real-time large scale reconstruction of extended and bounded 3D objects and environments using automatic feature extraction and time efficient algorithms Dynamic model update Video: Source: Siemens AG 31 9 th of September 2016

32 The future is now, go for it! Prof. Dr. Dr.-Ing. Dr. h.c. Jivka Ovtcharova Head of Institute Karlsruhe Institute of Technology (KIT) Institute for Information Management in Engineering (IMI) Zirkel 2, Bldg , Room Karlsruhe, Germany Phone: Fax: th of September 2016 Source: Arena2036_1-Digitaler_Schatten_151215

33 The future is now, go for it! Source: Arena2036_1-Digitaler_Schatten_ th of September 2016