Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems

碩士 === 國立交通大學 === 工業工程與管理系所 === 103 === Facing the sharp competitiveness in twenty-first century, the advanced technology and sophisticated manufacturing process are necessary for manufacturers to meet the consumer’s requirements. Developing innovative products, improving product quality and reducin...

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Main Authors: Wu, Cheng-Mao, 吳承懋
Other Authors: 唐麗英
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/42247124042956765273
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spelling ndltd-TW-103NCTU50311112016-08-12T04:14:07Z http://ndltd.ncl.edu.tw/handle/42247124042956765273 Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems 應用熵權重法與灰色理論最佳化多品質問題 Wu, Cheng-Mao 吳承懋 碩士 國立交通大學 工業工程與管理系所 103 Facing the sharp competitiveness in twenty-first century, the advanced technology and sophisticated manufacturing process are necessary for manufacturers to meet the consumer’s requirements. Developing innovative products, improving product quality and reducing production cost are effective ways to maintain market competitiveness. Therefore, finding the optimal factor-level combination in a multi-response process under the restricted experimental cost, experimental time and machine feasibility becomes a very important issue for manufacturers. Design of Experiments (DOE) is often applied in industry to determine the optimal parameter setting of a process. However, DOE can only be utilized to optimize single response. Although many studies have developed optimization procedures for multi-response problems, they still have some shortcoming. Therefore, the main purpose of this study is to develop a method of optimizing multiple responses simultaneously using Grey Relation Analysis (GRA), Entropy Weight Method and Dual Response Surface Methodology (DRSM). Finally, a real case from a semiconductor factory in Taiwan is utilized to verify the effectiveness of the proposed procedure. 唐麗英 洪瑞雲 2015 學位論文 ; thesis 33 zh-TW
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description 碩士 === 國立交通大學 === 工業工程與管理系所 === 103 === Facing the sharp competitiveness in twenty-first century, the advanced technology and sophisticated manufacturing process are necessary for manufacturers to meet the consumer’s requirements. Developing innovative products, improving product quality and reducing production cost are effective ways to maintain market competitiveness. Therefore, finding the optimal factor-level combination in a multi-response process under the restricted experimental cost, experimental time and machine feasibility becomes a very important issue for manufacturers. Design of Experiments (DOE) is often applied in industry to determine the optimal parameter setting of a process. However, DOE can only be utilized to optimize single response. Although many studies have developed optimization procedures for multi-response problems, they still have some shortcoming. Therefore, the main purpose of this study is to develop a method of optimizing multiple responses simultaneously using Grey Relation Analysis (GRA), Entropy Weight Method and Dual Response Surface Methodology (DRSM). Finally, a real case from a semiconductor factory in Taiwan is utilized to verify the effectiveness of the proposed procedure.
author2 唐麗英
author_facet 唐麗英
Wu, Cheng-Mao
吳承懋
author Wu, Cheng-Mao
吳承懋
spellingShingle Wu, Cheng-Mao
吳承懋
Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems
author_sort Wu, Cheng-Mao
title Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems
title_short Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems
title_full Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems
title_fullStr Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems
title_full_unstemmed Applying Entropy Weighting Method and Grey Theory to Optimize Multi-response Problems
title_sort applying entropy weighting method and grey theory to optimize multi-response problems
publishDate 2015
url http://ndltd.ncl.edu.tw/handle/42247124042956765273
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