While the principle benefits of robust design are widely accepted, there is still a large gap between robust design in theory and in practice. DTU’s annual Robust Design Day aims at bringing together researchers and practitioners focusing on applied Robust Design and Variation Management in Design and Production. The objective is a regular platform for discussions and a fruitful knowledge exchange on experiences, solutions and challenges faced. We hope that you enjoy viewing last year's symposium presentations and discussions!
For more information please contact: Chair: Ass. Prof. Tobias Eifler
Time | Schedule/Event |
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08:30 |
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09:00 |
DTU Robust Design Programme 2.0 - from RD principles to a coherent approach for lifecycle robustnessAss. Prof. Tobias Eifler, Head of Robust Design, DTU-MEKHead of the DTU Robust Design Group and chair of the Robust Design SIG in the Design Society. PhD in Engineering Design Methodology from the Technical University Darmstadt (Germany) and research focus in the field of Robust Design Methodology, Robust Design for Reliability, Variation Management across different organizational units including the benefits of new technologies and data analytics. ![]() |
09:40 |
Inventive Problem Solving (TRIZ) for RobustnessProf. Darrell Mann, The University of Buckingham, CEO & Technical Director Systematic Innovation Ltd.Darrell is one of Europe's leading experts in TRIZ (Theory of Inventive Problem Solving). Dedicated to changing the way organisations approach innovation, he has 25 years of experience in the innovation space from several industries, including aerospace, automotive, medical, etc. He authored the book Hands-on: Systematic Innovation as well as numerous papers on the topic. Technical Director of Systematic Innovation Ltd. ![]() |
10:20 |
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10:40 |
Virtual Robustness - Enabling new manufacturing strategies by variation-based product designDr. Stefan Kemmler, Knorr Bremse, Systeme für Nutzfahrzeuge GmbHStefan is an expert in Reliability Engineering, Virtual Testing, and Verification/Validation strategies. With a PhD on the assurance of mechanical reliability (University of Stuttgart), he is responsible for variation-based product design at Knorr-Bremse Commercial Vehicle Systems in Munich, and is external lecturer at the University of Applied Science Esslingen. ![]() |
11:20 |
Model Based Development Workflows for Improving Robustness of SystemsProf. Kevin Otto, Aalto University, Owner of an Robust Systems and Strategy LLCProf. Otto has been at Aalto University for three years, bring expertise in robust design, quality control, and digitalization. He has executed many variation reduction projects with clients ranging from automotive to industrial equipment including air conditioning systems. He has developed and deployed complete DFSS training courses for several large industrial clients. Lately, he has made contributions to combining modeling and analysis with DFSS best practices to achieve robustness and quality improvements more efficiently. With such methods, 2-10X cycle time improvements are typical. Dr. Otto has extensive academic experience, having authored over 150 peer reviewed articles and two books including the popular textbook Product Design. ![]() |
12:00 |
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13:00 |
Workshop Introduction to Contradictions Analysis - Achieving early robustness beyond Kinematic principles
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15:00 |
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15:20 |
Robust Design in a Prototype Driven Company (Dyson)
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16:00 |
Multidisciplinary design and optimisation for product robustnessAndy Parsley
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16:40 |
Open discussion: No more prototypes? Promises, prerquisites, and potential limitations of a simulation-driven robust design processGiven significant advances of computer aided analyses and simulation platforms over the last decades, the promises of simulation-driven product development are well accepted. At the same time, the existing challenges for a successful implementation of a corresponding strategy are a lot less discussed. Together with our guest and the audience, we will therefore take a closer look at questions such as workflows for prototype and simulation driven approaches, the pros and cons of bot, necessary skills and knowledge, simulation model validity, etc. ![]() |
17:00 |