Multi-response Optimization Algorithm with Weight Setting

碩士 === 國立交通大學 === 工業工程與管理系所 === 101 === With the rapid evolution of the times, the trend of globalization makes more competition in every industry, the design of products also become more and more complicated, consequently, one single quality characteristic is not enough to mea- sure the total qu...

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Bibliographic Details
Main Authors: Wu, Jia-Jen, 吳佳蓁
Other Authors: Tong, Lee-Ing
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/8w6ye4
Description
Summary:碩士 === 國立交通大學 === 工業工程與管理系所 === 101 === With the rapid evolution of the times, the trend of globalization makes more competition in every industry, the design of products also become more and more complicated, consequently, one single quality characteristic is not enough to mea- sure the total quality of a product and the optimization of multi-response becomes increasingly important. Many studies developed methods to design the experime- nts to simultaneously optimize multiple quality characteristics using Taguchi met- od or Design of Experiments (D.O.E). Those studies usually integrated multiple response variables into one index and then optimizing the composite index, however, the importance of each response variable may be different, composite integrating these responses into one index without considering the relationship between the importance and the performance of each response composite may not be appropriate. Hence, the main objective of this study is to develop a mult-respo- nse optimization algorithms using Fuzzy Theory, desirability function and Group Method of Data (GMDH) combined with DOE to determine the optimal settings for the factor-level. A case study of the cooling system is used to demonstrate the effectiveness and feasibility of the proposed procedure.