Future Supply Chains and Impact on Factory Operations

Transcription

1 UBS Industry Leader Network, Nov Future Supply Chains and Impact on Factory Operations Prof. Dr. Torbjørn Netland D-MTEC, ETH Zürich My focus is on anticipated developments in manufacturing factories in the next 5-10 years

2 Prof. Dr. Torbjörn Netland, Chair of Production and Operations Management In close cooperation with industry, the Chair of POM conducts empirical research into the technologies and management processes that provide productivity improvement in manufacturing. Research with Volvo AB (automotive), E.ON (energy), Jotun (process industry), Kvaerner (engineering), and many other industrial firms Since fall 2016, Tenure Track Assistant Professor of Production and Operations Management, D-MTEC MSc and PhD Norwegian University of Science and Technology, NTNU, Trondheim, Norway Research visit at Center for International Manufacturing, IfM, Cambridge University, UK, fall 2014 Research visit at McDonough School of Business, Georgetown University, Fellow of the World Economic Forum s Global Future Council on Production Board Member of the European Operations Management Association (EurOMA) Blog

3 A fourth industrial revolution? Change 1. Velocity Exponential (not linear) development of technologies Time 2. Breadth and depth Multiple technologies Effect on economy, business, society, individuals Bio World 2016 Tech 3. System impact Interdependent system change Connectivity and speed (e.g. smart phones, social media) Individuals It is difficult to understand digitalization and fully grasp its implications. Source: Schwab, K. (2016) The Fourth Industrial Revolution, WEF, p. 3 Torbjörn Netland 01-Nov-17 3

4 Vision cyber-physical production systems AI Platforms Data analysis Databases BI SCM Middle-ware Digital shadow (object model) Software Sensors Smart plant Raw data R&D Product Development Sour cing Logistics & Sales Use Fabrication Circular economy

5 Hype driven by consultants, media and politicians Roland Berger Torbjörn Netland 01-Nov-17 5

6 Statements by a leading consulting company The fourth manufacturing revolution will change everything More growth (again), fueled by productivity increase by >33 % More wealth distributed to everyone Growing markets in China and Africa China will not be the factory of the world anymore More employment at home / reshoring of production Regional production for regional markets Less global trade flows Automation of customized products Smaller, flexible factories serving local markets A chance for all of us Typical industry 4.0 illustration We need a much more surgical view on what will happen in manufacturing. Don t get carried away by consultancies selling credence goods.

7 Beyond the buzz For manufacturing, the classic challenges remain: 1. Globalization and competition 2. Internal effectiveness and efficiency 3. Supply chain visibility and transparency 4. Risk management 5. Meeting tougher customer demands 6. HSE and CSR Digitalization and new technologies can assist us solving these challenges.

8 Physical processes are more important than digital processes today and tomorrow.

9 Manufacturing is essentially about processes Data analysis Decision support Database Software PLM Digital shadow Simulation SRM APS Middleware ERP MES CRM Autonomous people-free processes require full error-free horizontal and vertical integration CAD Machine data Sensors (an utopia) Raw data R&D Product Development Sour cing Fabrication Logistics & Sales Use

10 Lights-out factories Lessons from General Motors Roger B. Smith Implementing technology for the sake of leading the technological race is a risky strategy.

11 Technology will continue improving processes (Big) Data analytics Data analysis Decision support AI for business intelligence Digital shadow Database Software Raw data R&D CAD PLM Product Development Simulation SRM Sour cing APS ERP Business software Additive Manufacturing Middleware MES Machine data Sensors Fabrication Advanced robotics Blockchain CRM Machine learning IoT sensors / Wearables VR/AR Logistics & Sales Drones Use

12 Examples 3D printing of tools at Volvo AB, Lyon (Source: Stratasys) Digital Shadow of injection molding tool exchange (Source: Geberit) RFID/NFC: Hand-free scanning / error-proofing (Source: Drones for semiautomated stock taking (Source: Infinum) Raw data R&D Product Development Sour cing Fabrication Logistics & Sales Use There is no sweeping revolution, but continuous process innovation in niches of manufacturing

13 Making processes simple is harder but better than making them complex today and tomorrow.

14 How do you improve the processes (before digitalizing or automating them) State-of-the-art of Industrial Engineering: Lean thinking (or Six Sigma, Word Class Manufacturing, TQM, TPM ) Raw data R&D Product Development Sour cing Fabrication Logistics & Sales Use

15 Industry 4.0 won t replace people ( ) For me, it is not a revolution that involves some huge digital leap forward. It is not as if what is valid today suddenly no longer applies. But one thing will change significantly: BMW, like other companies, needs people with a keen interest in a knowledge of systems. ( ) I don t think there will be a digital leap of 20 to 30% in productivity. But I am happy about small, day-to-day productivity gains. Just 5% would be a lot if you map that onto two million vehicles a year. We build about 8,000 cars a day, so our responsibility is to be efficient day in, day out. Harald Krüger, CEO BMW (in interview with Roland Berger, Accessed Nov. 2016) Torbjörn Netland 01-Nov-17 15

16 If lean takes time (Insights from Volvo AB) Philosophy / Lean culture Management system Operating system 2-3 y 5-6 y 8-10 y SUMMER 2014 MIT SLOAN MANAGEMENT REVIEW page 86

17 Human learning is far more important than machine learning today and tomorrow.

18 Summary Physical processes are more important than digital processes. Making processes simple is harder but better than making them complex. 1. See through the fuzz and fog: There is no sweeping revolution in most manufacturing industries. 2. Increase process efficiency step-by-step by picking the right technology projects (it depends on your process) using your own realistic vision of the future. 3. Do not digitalize or automate broken processes. 4. Get lean if not focused before, certainly now is the time. Human learning is far more important than machine learning. 5. Use an engineering sandbox. 6. Nurture a culture of learning and CI (leadership) 7. Encourage open (process) innovation.

19 Thank you! Prof. Dr. Torbjörn Netland Chair of Production and Operations Management D-MTEC ETH Zürich Torbjörn Netland 01-Nov-17 19