以特徵為基之跨廠零件加工次序規劃－應用基因演算法

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

曾一峰(Yi-Feng Tseng)

指導教授 ： 鄭元杰

元智大學/工程學院/工業工程與管理學系/碩士(2008年)

摘要

近幾年來，隨著產品設計的方式日趨複雜，使得零件的加工程序也相對繁瑣，企業必須以擴建新廠區的方式來提昇製造技術與解決產能不足的問題，即形成了跨廠生產規劃問題。在跨廠製造環境下，欲對零件進行加工次序規劃，除了要考慮零件各個加工操作的次序排列外，每個加工操作可以選擇的廠區也具有多種可行組合。因此，過去單廠加工次序方法已不適用，在分工越來越細的情形之下，跨廠加工次序的規劃是必行的。
　　有鑒於此，本研究針對方形加工零件提出兩階段規劃模式求解零件跨廠加工次序問題：1. 零件加工次序評估模式：利用零件的形狀特徵資訊作為基礎，建立加工在先限制矩陣和加工次序評估函數，以最大化總加權次數評估值為目標進行基因演算法，獲得的最佳零件加工次序；2. 零件跨廠加工指派評估模式：整合零件和廠區資訊，建構跨廠加工指派模型，以總指派成本最小化為評估準則下，進行基因演算法的搜尋，並以第一階段所求得之最佳零件加工次序作為輸入，獲得零件的最佳跨廠加工指派結果，提供決策者在多廠區製造環境下作為製程規劃參考的依據。

關鍵字

跨廠 ； 加工次序 ； 形狀特徵 ； 基因演算法

並列摘要

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.

並列關鍵字

multi-plant ； machining sequences ； form features ； genetic algorithms

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