Combined and Product Array Approaches in Simultaneous Optimization of Multiple Responses

다특성 동시최적화를 위한 통합배열과 교차배열 접근의 비교연구

  • Lee, Jae-Hoon (Department of Statistics, Seoul National University) ;
  • Park, Sung-Hyun (Department of Statistics, Seoul National University)
  • Published : 2006.12.31

Abstract

Robust parameter design is an off-line production technique for reducing variation and improving the quality of products and processes by using product arrays. However, the use of the product arrays usually requires a large number of runs. To overcome the drawback of the product array, the combined array can be used. Also optimizing multiple responses is increasingly important in industry. Using simultaneous optimization measures, we can deal with the multiple response case. In this paper we compare the simultaneous optimization using the Taguchi's product array with using the combined array. And models possible to set on combined arrays are also investigated and compared with the cases of product arrays.

Keywords

References

  1. Box, G. E. P. and Jones, S.(1990), 'Designing Products That Are Robust to the Environment', Total Quality Management, Vol. 3, pp. 265-282
  2. Kwon, Y. M.(1994), Simultaneous Optimization of Multiple Responses for Robust Design, Doctoral Thesis, Department of Statistics, Seoul National University
  3. Nair, V. N.(ed.)(1992), 'Taguchi's Parameter Design: A Panel Discussion', Technometrics, Vol. 34, pp. 127-16l https://doi.org/10.2307/1269231
  4. Park, S. H.(1996), Robust Design and Analysis for Quality Engineering, Chapman & Hall, London, England
  5. Taguchi, G. (1986), Introduction to Quality Engineering, White Plains, NY Quality Resources
  6. Taguchi, G. and Wu, Y.(1985), Introduction to Off-Line Quality Control, Central Japan Quality Association, Nagoya, Japan
  7. Taguchi, G., Chowdhury, S., Wu, Y.(2001), The Mahalanobis- Taguchi System, McGrawHill Press, New York
  8. Vining, G. G. and Myers, R. H.(1990), 'Combining Taguchi and Response Surface Philosophies : A Dual Response Approach', Journal of Quality Technology, Vol. 22, pp. 38-45 https://doi.org/10.1080/00224065.1990.11979204
  9. Welch, W. J., Yu, T. K., Kang, S. M., and Sacks, J.(1990), 'Computer Experiments for Quality Control by Parameter Design', Journal of Quality Technology, Vol. 22, pp. 15-22 https://doi.org/10.1080/00224065.1990.11979201