Using social network analysis to group the machine in FMS

碩士 === 國立臺灣科技大學 === 工業管理系 === 95 === In traditional industry, FMS has become a common production method to solve the change of the environment of production. The throughout efficiency of FMS is belong to the implement of grouping method in machine grouping, and the result of grouping played an impor...

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Main Authors: Chin-Ming Tsou, 鄒錦銘
Other Authors: Chao Ou-Yang
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/8uj828
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spelling ndltd-TW-095NTUS50410692019-05-15T19:48:55Z http://ndltd.ncl.edu.tw/handle/8uj828 Using social network analysis to group the machine in FMS 以社會網路分析法進行彈性製造系統機台分群之研究 Chin-Ming Tsou 鄒錦銘 碩士 國立臺灣科技大學 工業管理系 95 In traditional industry, FMS has become a common production method to solve the change of the environment of production. The throughout efficiency of FMS is belong to the implement of grouping method in machine grouping, and the result of grouping played an important role in this perspective. As so far, most research took a lot of care on the results of the planned objective function by counting the index of efficiency. However, the grouping method be chosen is not perfectly in hypothesis, including the sequences of production process, the direct and indirect relationship between machines and the dissimilar in parameters of hypothesis. Those factors do affect on the result of grouping. Once a new part or process added in the original production system, the lack of flexibility in the re-operation of grouping also be the problem. This research hoped to improve the grouping method and solved the probably problem and restricts by using the social network analysis. In the process of the part manufacturing in the FMS system, the log file will produce automatically. Social network analysis method used the inside information to count the relationship between machines and transform into the matrices of correlation. Finally it combined the Linkage grouping method to get the grouping results. This research applied many process routing data to compute the results of grouping in each chosen reference, and compared to the original grouping method to establish the supporting foundation of this viewpoint. Chao Ou-Yang 歐陽超 2007 學位論文 ; thesis 69 zh-TW
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language zh-TW
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description 碩士 === 國立臺灣科技大學 === 工業管理系 === 95 === In traditional industry, FMS has become a common production method to solve the change of the environment of production. The throughout efficiency of FMS is belong to the implement of grouping method in machine grouping, and the result of grouping played an important role in this perspective. As so far, most research took a lot of care on the results of the planned objective function by counting the index of efficiency. However, the grouping method be chosen is not perfectly in hypothesis, including the sequences of production process, the direct and indirect relationship between machines and the dissimilar in parameters of hypothesis. Those factors do affect on the result of grouping. Once a new part or process added in the original production system, the lack of flexibility in the re-operation of grouping also be the problem. This research hoped to improve the grouping method and solved the probably problem and restricts by using the social network analysis. In the process of the part manufacturing in the FMS system, the log file will produce automatically. Social network analysis method used the inside information to count the relationship between machines and transform into the matrices of correlation. Finally it combined the Linkage grouping method to get the grouping results. This research applied many process routing data to compute the results of grouping in each chosen reference, and compared to the original grouping method to establish the supporting foundation of this viewpoint.
author2 Chao Ou-Yang
author_facet Chao Ou-Yang
Chin-Ming Tsou
鄒錦銘
author Chin-Ming Tsou
鄒錦銘
spellingShingle Chin-Ming Tsou
鄒錦銘
Using social network analysis to group the machine in FMS
author_sort Chin-Ming Tsou
title Using social network analysis to group the machine in FMS
title_short Using social network analysis to group the machine in FMS
title_full Using social network analysis to group the machine in FMS
title_fullStr Using social network analysis to group the machine in FMS
title_full_unstemmed Using social network analysis to group the machine in FMS
title_sort using social network analysis to group the machine in fms
publishDate 2007
url http://ndltd.ncl.edu.tw/handle/8uj828
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