[2002. 10. 30.] 김광재 교수님, QMOD 학회 발표
작성자
quality
작성일
2020-02-16 00:37
조회
2358
Kim, K., Byun, J., Min, D., and Jeong, I., "Multiresponse Surface Optimization: Concept, Methods, and Future Directions," International Conference on Quality Management and Motivation for Qrganizational Development (QMOD), Busan, Korea, October 29-31, 2002.
<요약문>
Response surface methodology (RSM) consists of a group of techniques used in the empirical study of the relationship between the response and a number of input variables. Consequently, the experimenter attempts to find the optimal setting for the input variables that maximizes (or minimizes) the response. Most of the work in RSM has been focused on the case where there is only one response of interest. A common problem in product or process design, however, is the selection of optimal parameter levels which involve simultaneous consideration of multiple response variables, called a multiresponse problem. Various attempts have been made to model and solve a multiresponse problem, including priority-based approach, desirability function approach, and loss function approach. In this talk, we first formally define a multiresponse problem, and then review the existing work in this field. The strengths and weaknesses of the existing methods will be presented. Finally, some promising topics for future research will be discussed.
<요약문>
Response surface methodology (RSM) consists of a group of techniques used in the empirical study of the relationship between the response and a number of input variables. Consequently, the experimenter attempts to find the optimal setting for the input variables that maximizes (or minimizes) the response. Most of the work in RSM has been focused on the case where there is only one response of interest. A common problem in product or process design, however, is the selection of optimal parameter levels which involve simultaneous consideration of multiple response variables, called a multiresponse problem. Various attempts have been made to model and solve a multiresponse problem, including priority-based approach, desirability function approach, and loss function approach. In this talk, we first formally define a multiresponse problem, and then review the existing work in this field. The strengths and weaknesses of the existing methods will be presented. Finally, some promising topics for future research will be discussed.
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