Feature-based Approach to Maching Sequences Planning For Parts Using Genetic Algorithms in a Multi-Plant Manufacturing Environment

碩士 === 元智大學 === 工業工程與管理學系 === 96 ===   As product design tends to be diversified in recent years, the process planning of parts also becomes complicated. Enterprises have to expand the number of plants to increase the manufacturing skills and capacity. Process planning in one factory will no more me...

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Bibliographic Details
Main Authors: Yi-Feng Tseng, 曾一峰
Other Authors: Yuan-Jye Tseng
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/42040612785491753596
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Summary:碩士 === 元智大學 === 工業工程與管理學系 === 96 ===   As product design tends to be diversified in recent years, the process planning of parts also becomes complicated. Enterprises have to expand the number of plants to increase the manufacturing skills and capacity. Process planning in one factory will no more meet the demand of product. In a multi-plant manufacturing environment, it not only considers the sequencing of machining operations but also arranges each machining operation to a feasible plant. Therefore, how to developing for multi-plant process planning has been a key issue because the lower cost can be gained by using a good operation sequencing and assignment to manufacturing a part.   This paper constructs from two phases to evaluate and assign a multi-plant machining sequences problem for prismatic parts. The first phase is based on the form features of parts to develop the evaluation of operation sequencing. The matrix of machining precedence constraints is the main constraint represents the precedence relations among operations. This phase also uses operation grouping concepts to formulate the model of operation sequencing evaluation of maximizing the total weighted number value and finds the optimal machining sequence. With the result achieved at the first phase, the second phase integrated the part and plants information to solve the optimal multi-plant operation assignment in minimum total assignment cost. Finally, the results could give managers a referral and aid to arrange the sequencing and assignment of machining operations, and reduce the waste of resources and costs in a multi-plant manufacturing environment.