Abstract
Computer simulations are widely used during product development. In particular, computer experiments are often conducted in order to optimize both product and process performance while respecting constraints that may be imposed. Several methods for achieving robust design in this context are described and compared with the aid of a simple example problem. The methods presented compare classical as well as modern approaches and introduce the idea of a ‘stochastic response’ to aid the search for robust solutions. Emphasis is placed on the efficiency of each method with respect to computational cost and the ability to formulate objectives that encapsulate the notion of robustness.
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Notes on contributors
Ron A. Bates
Ron Bates is a Senior Research Fellow in the Department of Statistics at the London School of Economics and Political Science (LSE), London, UK. He has worked on several EU-funded research contracts related to Robust Engineering Design and Product Development and is a consultant in Industrial Statistics for Enterprise LSE. He has a PhD in Robust Engineering Design from City University, London and a BSc in Engineering from Sussex University. He has published over 30 research and conference papers and his research interests include Design of Experiments, multivariate spatial modelling, time-frequency analysis and modelling complex nonlinear engineering and biomedical systems.
Ron S. Kenett
Ron S. Kenett has a Ph.D. degree. He is CEO and Senior Partner of KPA Ltd., an international management consulting firm and Visiting Professor at the University of Torino, Torino, Italy. He has over 25 years of experience in restructuring and improving the competitive position of organizations by integrating statistical methods, process analysis, supporting technologies and modern human resource management systems. As Professor of Management at the State University of New York-Binghamton (1987–1993), he was awarded the General Electric Quality Management Fellowship. For ten years he served as Director of Statistical Methods for Tadiran Telecommunications Corporation and, previously, as researcher at Bell Laboratories in New Jersey and faculty member at the department of Statistics, University of Wisconsin-Madison. His 90 publications are on topics in industrial statistics, biostatistics and quality management. Ron is co-author of four books including — Modern Industrial Statistics: Design and Control of Quality and Reliability (with S. Zacks), Duxbury Press, 1998, Chinese edition, 2004, Multivariate Quality Control: Theory and Applications (with C. Fuchs), Marcel Dekker Inc., 1998 and Software Process Quality: Management and Control (with E. Baker), Marcel Dekker Inc., 1999. Professor Kenett’s Ph.D. is in Mathematics from the Weizmann Institute of Science (1978); he earned a BSc. in mathematics with first class honors from Imperial College, London University (1974). Ron is president elect of ENBIS, the European Network for Business and Industrial Statistics (www.enbis.org). He can be reached at [email protected]. More information on his publications is available at www.kpa.co.il.
David M. Steinberg
David Steinberg is on the faculty of the Department of Statistics and Operations Research of Tel Aviv University. He also is head of the statistical consulting laboratory at Tel Aviv University. He completed his Ph.D. degree in Statistics at the University of Wisconsin-Madison. His main areas of research are experimental design, robust design and computer experiments. He has taught numerous courses indesign of experiments in academia and in industry. He is involved in many applications in a wide range of fields, including industrial projects, biostatisticsand seismology. His more than 70 published papers reflect this broad spectrum of statistical interest. He is an associate editor for Technometrics and has also served as an associate editor for Applied Statistics. David is also the Vice President of the Israel Statistical Association.
Henry P. Wynn
Henry Wynn is Professor of Statistics and Convenor (head) of the Statistics department at the London School of Economics. Previous to that he held senior positions at Imperial College, London, City University, London and the University of Warwick. Until recently he was also part-time Scientific co-Director of EURANDOM in the Netherlands. His extensive track record in theoretical and applied statistics includes working in experimental design, optimisation and robust engineering design. Industrial work includes European-union funded multi-disciplinary research contracts and direct research and consultancy for industry. He is an honorary fellow of several international societies.