Flexibility in materials processing

Transcription

1 Flexibility in materials processing Maurits Van Camp 1

2 Who we are A global materials technology and recycling group One of three global leaders in emission control catalysts for light-duty and heavy-duty vehicles and for all fuel types A leading supplier of key materials for rechargeable batteries used in portable electronics and hybrid & electric cars The world s leading recycler of complex waste streams containing precious and other valuable metals 2

3 Our foundations Unique business Unique model business model Supportive megatrends Industry leader in Industry sustainability leader in sustainability metals application know-how Chemistry material science metallurgy material solutions more stringent emission control resource scarcity recycling electrification of the automobile 3

4 Our strategy By 2020 we have clear leadership in clean mobility materials and recycling turned sustainability into a greater competitive edge 4

5 Unique position in clean mobility materials ICE Emission control catalysts (p)hev Battery cathode materials and emission control catalysts BEV Battery cathode materials Fuel cells Electro-catalyst and battery cathode materials 5

6 Unique position in recycling SHORT LOOP Recycling services for customer production scrap and residues LONG LOOP Unique technologies for treating complex residues and by-products Further leverage Umicore s leadership in closed loop solutions for customers Leverage the profitable expansion to 500kt in Hoboken 6

7 Flexibility in materials processing Transition to a knowledge economy and innovation economy 7

8 Flexibility in materials processing Transition to a knowledge economy The Minimalist Approach 8

9 Why Minimalist approach? We live in a risk VUCA world (Volatile Uncertain Complex Ambiguous) Safety, QEHS Recycling as a prime service Sustainability Challenges and its stakeholders Environmental legislation (EU directives, Reach, CMR and local legislation), License to operate, License to market Value chain, Customers, EBIT, budgets, Metal prices, Currencies, Globalization. Quality, ISO 9001, ISO 14001, QEHS, EFQM, 5S, priorities, control, Corporate demands. Strategic Roadmaps, R&D, Transition to knowledge and innovation economy, IP, Security, fake news IT, SAP, communication collaboration Artificial Intelligence.. Maintenance, risk and risk cover, disturbances HR, Competence management, L&D. Murphy s Law Anything that can go wrong, will go wrong 9

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11 Some answers Roger E. Bohn Ramchandran Jaikumar How to learn fast... From Art to Science... How to control complex systems... How to avoid fire fighting... How to organise workforce... How to involve people in learning... What are the stages of knowledge... How to reduce problems... 11

12 The Minimalist Approach Information management Problem reduction Focus on disruptions Knowledge management Learning cycle Knowledge base Managing the learning speed Injecting Life into Information through modeling Physical models Control models Statistical models 12

13 The Learning Cycle Save knowledge control models physical models statistical models Improvements New knowledge Experiments Learning process process team, operators, experts,... experimental design, statistics,... Production Data Input Automatic and stable running process Output 13

14 Stages of Knowledge 1. We do know nothing. 2. We have an idea but can t measure it 3. We have an idea and can measure some variables. 4. We can measure the main variables and can control some 5. Recipe level: measurement and control of main variables 6. First order effects 7. Interactions 8. Know it all 14

15 From Art to Science Knowledge at stage Nature of production Expertise based Procedure based Role of workers Everything Problem solving Learning and improving Location of knowledge Workers head Written and Oral In database or software Nature of learning Artistic Natural experiments Controlled experiments simulations Nature of problem solving Trial and error Scientific method Table look up Method of training new workers Apprenticeship Classroom coaching Teaching Natural type of organization Organic Mechanistic Learning oriented Suitability of automation None high Ease of transfer to another site Low high Feasible product variety High Low high Quality control approach Sorting Statistical Feed forward 15

16 Procedures and Knowledge % 80.00% Zone of ineffefectiveness Degree of procedure 60.00% 40.00% Zone of inefficiency 20.00% 0.00% Sstage of knowledge 16

17 Managing the Speed of Learning Requires managing: Signal noise ratio Information cycle time Fidelity People, people, people 17

18 Injecting life into information Modeling Control models Physical models Statistical models Modeling makes integration of knowledge possible 18

19 Flexibility in materials processing Transition to an innovation economy 19

20 Transition to the knowledge economy Industrial economy knowledge integration learning process improvements experiments production data knowledge economy input automatic & stable running process output Innovation economy Controllable knowledge 20

21 Transition to an innovation economy Industrial economy Precompetitive collaborations knowledge economy Competitive research Innovation economy Controllable knowledge Enablers: multi-stakeholder collaborations people with innovation and entrepreneurship skills 21

22 Chosen path: Triple helix model Triple helix consists of 3 components Industry - Academia - Government All are taking up Societal challenges Interaction drives transitions as it generates a discussion of innovation in innovation Transition: industrial economy knowledge economy innovation economy 22

23 Game changer: New role for Universities: Social-Economic Development Entrepreneurial University Third mission Next to Education and Research: Providing students with new skills, ideas and entrepreneurial thinking Becoming a source of technology generation and transfer 23

24 Precompetitive collaboration and innovation 24

25 Collaboration and innovation STRATEGY PRE-COMPETITIVE COLLABORATION COMPETITIVE RESEARCH & DEVELOPMENT US-EU-Japan trilateral UNEP resource panel European Innovation Platform Networks: CR3, EIT RM Joint projects: H2020, SIM PhDs and education Bilateral agreements R&D projects with BUs 25

26 EIT RawMaterials An impressive partnership Network of 120 active partners in 22 EU member states 6 co-location centers in Lulea, Espoo, Wroclaw, Leuven, Metz, Rome Headquarters in Berlin 26

27 Remade Institute US Department of Energy Institute hosted on Rochester Institute of Technology, campus with leading national labs and universities Officially launched by DOE on 9 May 2017 Mission: accelerating manufacturing innovation and scale-up technologies that enable the recycling, reuse and remanufacturing of plastics, e-waste, fibers and metals to costeffectively recover end-of-life (EOL) and waste materials 27

28 Center for resource recovery and recycling NSF funded industry-university cooperation 28

29 Copper, Lead and refractory consortia Leveraging pre-competitive research in our own competitive field PRE-COMPETITIVE COLLABORATION Setting up and feeding the databases with shared costs COMPETITIVE RESEARCH & DEVELOPMENT Creating new insights using Factage within competitive projects 29

30 Take Home messages Flexibility in materials is knowledge and innovation driven The minimalist approach is for us the accelerator model for knowledge generation in a transition to the knowledge economy Multi-stakeholder collaborations and people with innovation and entrepreneurship skills are the enablers for a transition to the innovation economy. Game changer = new role for universities: Next to Research and education Provide students with new skills, ideas and entrepreneurial thinking 30

31 Thank you for your attention 31