Robust design models for customer-specified bounds on process parameters

Journal of Systems Science and Systems Engineering

Volumn 15, Issue 1, 2006, Pages 2-18

  Shin, Sangmun ^a   Cho, Byung Rae ^b  

^a Inje University   (South Korea)

^b AMRL   (United States)

Author keywords

constraint method; Optimization; Process bias; Process variability; Response surface methodology; Robust design

Indexed keywords

EID: 33746044498     PISSN: 10043756     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11518-006-0002-4     Document Type: Article

References (34)

1. Ames, A.E., Mattucci, N., MacKonald, S., Szonyi, G., & Hawkins, D.M. (1997). Quality loss function for optimization across multiple response surfaces. Journal of Quality Technology, 29 (3): 339-346
2. Borror, C.M. (1998). Mean and variance modeling with qualitative responses: A case study. Quality Engineering, 11 (1): 141-148
3. Box, G.E.P. & Draper, N.R. (1987). Empirical Model Building and Response Surfaces. John Wiley & Sons, NY
4. Chen, C.H. (2004). Set the optimum process parameters based on asymmetric quality loss function. Quality & Quantity, 38: 75-79
5. Cho, B.R. (1994). Optimization issues in quality engineering. Ph.D. Dissertation. School of Industrial Engineering, University of Oklahoma, OK
6. Cho, B.R., Kim, Y.J., Kimber, D.L. & Phillips, M.D. (2000). An integrated joint optimization procedure for robust and tolerance design. International Journal of Production Research, 38 (10): 2309-2325
7. th Industrial Engineering Research Conference, 650-655, Minneapolis, MN, May, 1996
8. Del Castillo, E. & Montgomery, D.C. (1993). A nonlinear programming solution to the dual response problem. Journal of Quality Technology, 25: 199-204.
9. Geoffrion, A.M. (1968). Proper efficiency and theory of vector maximization. Journal of Mathematical Analysis and Applications, 22: 618-630
10. Karasakal, E.K. & Michalowski, W. (2003). Incorporating wealth information into a multiple criteria decision making model. European Journal of Operational Research, 150: 204-219
11. Khuri, A.I. & Cornell, J.A. (1987). Response Surfaces: Design and Analyses. Marcel Dekker, NY.
12. Kim, D. & Rhee, S. (2003). Optimization of GMA welding process using the dual response approach. International Journal of Production Research, 41 (18): 4505-4515
13. Kim, Y.J. & Cho, B.R. (2000). Economic consideration on parameter design. Quality and Reliability Engineering International, 16: 501-514
14. Kim, Y.J. & Cho, B.R. (2002). Development of priority-based robust design. Quality Engineering,14 (3): 355-363
15. Kim, Y.J. & Cho, B.R. (2002). Development of priority-based robust design. Quality Engineering, 14 (3): 355-365
16. Koksoy, O. & Doganaksoy, N. (2003). Joint optimization of mean and standard deviation using response surface methods. Journal of Quality Technology, 35 (3): 239-252
17. Lin, D.K.J. & Tu, W. (1995). Dual response surface optimization. Journal of Quality Technology, 27: 34-39.
18. Lin, D.K.J. & Tu, W. (1995). Dual response surface optimization. Journal of Quality Technology, 27: 34-39
19. MATLAB. http://www.mathworks.com/
20. Mattson, C.A. & Messac, A. (2003). Concept selection using s-Pareto frontiers. AIAA Journal, 41 (6): 1190-1198
21. Messac, A., Sundararaj, G.J., Taapetta, R.V. & Renaud, J.E. (2000). The ability of objective functions to generate points on non-convex Pareto frontiers. AIAA Journal, 38: 1084-1090
22. MINITAB. http://www.minitab.com/
23. Moghadam, M.B. (2005). Application of robust parameter design methodologies. Quality & Quantity, 39: 175-188
24. Montgomery, D.C., Myers, R.H., Carter, W.H. & Vining, G.G. (2005). The hierarchy principle in designed industrial experiments. Quality and Reliability Engineering International, 21: 197-201
25. Myers, R.H. (1999). Response surface methodology-current status and future directions (with discussions). Journal of Quality Technology, 31 (1): 30-74
26. Myers, R.H. & Montgomery, D.C. (1995). Response Surface Methodology: Process and Product Optimization Using Designed Experiments. John Wiley & sons, NY
27. Robinson, R.J., Borror C.M. & Myers, R.H. (2004). Robust parameter design: A review. Quality and Reliability Engineering International, 20: 81-101
28. Steuer, R.E. (1986). Multiple Criteria Optimization: Theory, Computation and Application. John Wiley & Sons, NY
29. Szidarovszky, F., Gershon, M.E. & Duckstein, L. (1986). Techniques for Multiobjective Decision Making in System Management. Wlsevier, NY
30. Taguchi, G. (1986). Introduction to Quality Engineering. Asian Productivity Organization. UNIPUB, White Plains, NY
31. Tang, L.C. & Xu, K. (2002). A unified approach for dual response surface optimization. Journal of Quality Technology, 34 (4): 437-447
32. Tind, J. & Wiecek, M.M. (1999). Augmented Lagrangian and Tchebycheff approaches in multiple objective programming. Journal of Global Optimization, 14: 251-266
33. Vining, G.G. & Myers, R.H. (1990). Combining Taguchi and response surface philosophies: A dual response approach. Journal of Quality Technology, 22: 38-45
34. Wu, H.H. (2002). A comparative study of using grey relational analysis in multiple attribute decision making problems. Quality Engineering, 15 (2): 209-217