Achieving Robust Design from Computer Simulations

References

• Allen, T., Bernshteyn, M. and Kabiri-Bamoradian, K. (2003). Constructing meta-models for computer experiments. Journal of Quality Technology, 35, pp. 264–274.
   Google Scholar
• Bates, R.A. and Wynn, H.P. (2000). Adaptive Radial Basis Function Emulators for Robust Design, in Evolutionary Design and Manufacture, I C Parmee (Ed.), 343–350, Springer Verlag.
   Google Scholar
• Bates, R.A., Buck, R.J., Riccomagno, E. and Wynn, H.P. (1996). Experimental design and observation for large systems. Journal of the Royal Statistical Society, Series B, 58, 77–94.
   Google Scholar
• Bates, R.A., Giglio, B., and Wynn, H.P. (2003). A global selection procedure for polynomial interpolators. Technometrics, 45, 246–255.
   Google Scholar
• Bates, R.A., Kenett, R.S., Steinberg D.M and Wynn, H.P. (2004). Robust design using computer experiments, Proceedings of the 13-th European Conference on Mathematics for Industry (ECMI), 21–25 June 2004, Eindhoven, the Netherlands , Springer Verlag.
   Google Scholar
• Broomhead, D.S. and Lowe, D. (1988). Multivariate functional interpolation and adaptive networks. Complex Systems, 2, 321–355.
   Google Scholar
• Bursztyn, D. and Steinberg, D.M. (2005). Comparison of designs for computer experiments. Journal of Statistical Planning and Inference, in press.
   Google Scholar
• Friedman, J.H. (1991). Multivariate adaptive regression splines. Annals of Statistics, 19, 1–141.
   Google Scholar
• Huang D., Allen T. (2005), Design and analysis of variable fidelity experimentation applied to engine valve heat treatment process design. Journal of the Royal Statistical Society, Series C — Applied Statistics, 54, pp. 443–463.
   Google Scholar
• Kenett, R.S. and Zacks, S. (1998). Modern Industrial Statistics: Design and Control of Quality and Reliability, Duxbury Press, San Francisco, CA.
   Google Scholar
• Kennedy, M.C. and O’Hagan, A. (2001). Bayesian calibration of computer models. Journal of the Royal Statistical Society, Series B, 63, 425–464.
   Google Scholar
• Li, R.L. and Sudjanto, A. (2005). Analysis of computer experiments using penalized likelihood in Gaussian Kriging models. Technometrics, 47, 111–120.
   Google Scholar
• Moorhead, P.R. and Wu, C.F.J. (1998). Cost-driven parameter design. Technometrics, 40, 111–119.
   Google Scholar
• Phadke, M.S. (1989). Quality Engineering Using Robust Design, Prentice-Hall, New York, NY.
   Google Scholar
• Reese C., Wilson A., Hamada M., Martz H., Ryan K. (2004), Integrated Analysis of Computer and Physical Experiments. Technometrics, 46, pp. 153–164.
   Google Scholar
• Romano, D. and Vicario, G., (2002), Reliable Estimation in Computer Experiments on Finite Element Codes. Quality Engineering, Vol.14, Issue 2.
   Google Scholar
• Sacks, J. and Welch, W.J. (1991). A system for quality improvement via computer experiments. Communications in Statistics—Theory and Methods, 20:477–495.
   Google Scholar
• Sacks, J., Welch, W.J., Mitchell, T.J. and Wynn, H.P. (1989). Design and analysis of computer experiments. Statistical Science, 4, 409–435.
   Google Scholar
• Santner, T.J., Williams, B.J. and Notz, W.L. (2004). The Design and Analysis of Computer Experiments, Springer, New York, NY.
   Google Scholar
• Shoemaker, A. C., Tsui, K.-L. and Wu, C.F.J.(1991). Economical Experimentation Methods for Robust Parameter Design. Technometrics, vol. 33, pp. 415–428.
   Google Scholar
• Steinberg, D.M. (1996). Robust design: Experiments for improving quality, in Handbook of Statistics, Vol. 13, ed. by S. Ghosh and C.R. Rao, Elsevier Science, 199–240.
   Google Scholar
• Steinberg, D.M. and Bursztyn, D. (1994). Dispersion effects in robust design experiments with noise factors. Journal of Quality Technology, 26, 12–20.
   Google Scholar
• Steinberg, D.M. and Bursztyn, D. (1998). Noise factors, dispersion effects and robust design. Statistica Sinica, 8, 67–85.
   Google Scholar
• Taguchi, G. (1986). Introduction to Quality Engineering, Kraus International Publications, White Plains, NY.
   Google Scholar
• Taguchi, G. (1978). System of Experimental Design. Unipub/Kraus International Publications and American Supplier Institute 1978.
   Google Scholar
• Thomke, S. (2001). Enlightened experimentation: The new imperative for innovation. Harvard Business Review, February, 67–75.
   Google Scholar
• Thomke, S., Holzner, M., and Gholami, T. (1999). The crash in the machine. Scientific American, 280, 72–77.
   Google Scholar
• Urban, G.L. and Hauser, J.R. (1993). Design and Marketing of New Products, Prentice-Hall, Englewood Cliffs, NJ.
   Google Scholar
• Vining G G and Myers R H (1990). Combining Taguchi And Response-Surface Philosophies — A Dual Response Approach. Journal of Quality Technology 22 (1): 38–45.
   Google Scholar
• Wheelwright, S.C. and Clark, K.B. (1992). Revolutionizing Product Development. The Free Press, New York, NY.
   Google Scholar