- Volume 20 Issue 3
DOI QR Code
Using the Maximin Criterion in Process Capability Function Approach to Multiple Response Surface Optimization
다중반응표면최적화를 위한 공정능력함수법에서 최소치최대화 기준의 활용에 관한 연구
- 정인준 (대구대학교 경영학과)
- Received : 2019.03.25
- Accepted : 2019.08.10
- Published : 2019.09.30
Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.
Supported by : 대구대학교
- 박영택 2014. 품질경영론, 서울:한국표준협회미디어.
- 정인준 2018. "쌍대반응표면최적화를 위한 사후선호도반영법: TOPSIS를 활용한 최고선호해 선택," 지식경영연구 (19:2), pp. 151-162. https://doi.org/10.15813/kmr.2018.19.2.008
- 정인준 2017. "대화식 절차를 활용한 공정능력지수 기반 다중반응표면 최적화," 품질경영학회지 (45:2), pp. 191-208. https://doi.org/10.7469/JKSQM.2017.45.2.191
- 정인준 2011. "다중반응표면최적화: 현황 및 향후 연구방향," 품질경영학회지 (39:3), pp. 377-390. https://doi.org/10.7469/JKSQM.2011.39.3.377
- 표인수, 이재광 2016. "QFD를 이용한 기업 법무 서비스 품질 측정 및 개선에 관한 연구," 지식경영연구 (17:2), pp. 1-26. https://doi.org/10.15813/kmr.2016.17.2.001
- Ardakani, M. K. and Wulff, S. S. 2013. "An Overview of Optimization Formulations for Multiresponse Surface Problems," Quality and Reliability Engineering International (29:1), pp. 3-16. https://doi.org/10.1002/qre.1288
- Chan, L. K., Cheng, S. W., and Spiring, F. A. 1988. "A New Measure of Process Capability Cpm," Journal of Quality Technology (20:3), pp. 162-175. https://doi.org/10.1080/00224065.1988.11979102
- Ch'ng, C. K., Quah, S. H., and Low, H. C. 2005. "Index Cpm* in Multiple Response Optimization," Quality Engineering (17:1), pp. 165-171. https://doi.org/10.1081/QEN-200029001
- Hsiang, T. C. and Taguchi, G. 1985. A Tutorial on Quality Control and Assurance - the Taguchi methods, In: ASA Annual Meeting, Las Vegas, Nevada, USA.
- Jauregi, P., Gilmour, S., and Varley, J., 1997. "Characterisation of Colloidal Gas Aphrons for Subsequent Use for Protein Recovery," Chemical Engineering Journal (65:1), pp. 1-11. https://doi.org/10.1016/S1385-8947(96)03154-3
- Juran, J. M. 1974. Quality Control Handbook (3rd ed.), New York: McGraw-Hill.
- Kane, V. E. 1986. "Process Capability Indices," Journal of Quality Technology (18:1), pp. 41-52. https://doi.org/10.1080/00224065.1986.11978984
- Khuri, A. I. 1996. "Multiresponse Surface Methodology." Handbook of Statistics: Design and Analysis of Experiment (Vol. 13) (eds. A. Ghosh and C. R. Rao), pp. 377-406.
- Kim, K. and Lin, D. 2006. "Optimization of Multiple Responses Considering Both Location and Dispersion Effects," European Journal of Operational Research (169:1), pp. 133-145. https://doi.org/10.1016/j.ejor.2004.06.020
- Miettinen, K. 1999. Nonlinear Multiobjective Optimization, Boston: Kluwer Academic Publishers.
- Myers, R. H. 1999. "Response Sur face Methodology - Current Status and Future Directions," Journal of Quality Technology (31:1), pp. 30-44. https://doi.org/10.1080/00224065.1999.11979891
- Myers, R. H., Khuri, A., and Carter, W. H., Jr. 1989. "Response Surface Methodology: 1966-1988," Technometrics (31:2), pp. 137-157. https://doi.org/10.1080/00401706.1989.10488509
- Myers, R. H., Montgomery, D. C., Vining, G. G., Borror, C. M., and Kowalski, S. M. 2004. "Response Surface Methodology: A Retrospective and Literature Survey," Journal of Quality Technology (36:1), pp. 53-77. https://doi.org/10.1080/00224065.2004.11980252
- Plante, R. D. 1999. "Multicriteria Models for the Allocation of Design Parameter Targets," European Journal of Operational Research (115:1), pp. 98-112. https://doi.org/10.1016/S0377-2217(98)00119-2
- Plante, R. D. 2001. "Process Capability: A Criterion for Optimizing Multiple Response Product and Process Design," IIE Transactions (33:6), pp. 497-509. https://doi.org/10.1080/07408170108936849
- Sullivan, L. P. 1984. "Targeting Variability - A New Approach to Quality," Quality Progress (17:7), pp. 15-21.
- Sullivan, L. P. 1985. "Letters," Quality Progress (18:4), pp. 7-8.
- Steuer, R. E. 1986. Multiple Criteria Optimization: Theory, Computation, and Application, New York: John Wiley & Sons.