利用電腦輔助工程選取供應鏈中跨廠協同設計之零件

Using Computer Aided Engineering selected Collaborative Manufacturing parts in the Supply Chain

馬千琇(Chien-Hsiu Ma)

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(2011年)

https://doi.org/10.6838/YZU.2011.00366

摘要

現今全球化的趨勢使得企業面臨著激烈的競爭，對於產品生命週期越來越短，品質要求越來越高，對於產品的功能性也相當重視，並且產業生產的型態已由傳統的單一廠區生產，轉換成多廠區的生產環境，根據不同廠區的資源、生產技術及製造特性，規劃產品零件的挑選，透過跨廠區資源的協同整合完成產品生產，以滿足顧客需求，也增加了產品的多變性；為了能夠協同整合跨廠區的資源達到產品品質優良且符合消費者的需求，除了考量各個工廠的製造特性外，許多工廠導入電腦輔助工程分析(Computer Aided Engineering ,CAE)軟體對產品零件進行機械性能的測試分析，以產品機械性能指標為依據，評估分析出各零件的CAE分析值，並規劃多零件的組裝CAE值，除了讓產品實用外，也滿足了穩固耐用的功能。
本研究將利用對於規劃零件選取與排列有顯著效果的粒子群演算法，做為產品元件跨廠區分派組裝的求解工具，以總效益最大化為目標，演算法中以製造成本、壞料成本、運送成本及跨廠協同下的CAE資訊傳遞成本，同時也加入產能限制及品質水準為限制，計算總成本低亦滿足產品總CAE分析評估值高的的產品零件組合以及其各零件的工廠指派，獲得最佳產品的零件組合和最佳總效益值，提高求解的效率及最佳解品質。

關鍵字

電腦輔助工程分析 ； 跨廠協同 ； 粒子群演算法

並列摘要

Today the trend of globalization makes the enterprises are facing competition for shorter product life cycles, increasing quality requirements for product functionality is also attached considerable importance. Industrial production patterns from traditional single-plant production to a multi-plant production, depending on the plant's resources and production technology, through the collaborative manufacturing parts in the supply chain to satisfy customer demand. Many plants into Computer Aided Engineering(CAE) software for mechanical properties of the product test and analysis. Base on different mechanical properties to assess the value of each part of the CAE analysis, and then planning multi-part assembly CAE value. Not only making the products practical, but also satisfying the strong and durable.
This study use the selection and arrangement of particle swarm algorithm, as the product assembled to solve cross-plant distribution tools to maximize the total benefits as the goal. The total cost including manufacturing costs, bad material costs, transport costs and cross-plant collaboration under the CAE information delivery costs. The capacity constraints for suppliers, quality and lead time requirements for the parts are also considered in the model. This way we can provide information of the best benefit with different parts in different manufacturers.

並列關鍵字

Computer Aided Engineering ； Mutli-plant Planning ； collaborative ； Particle swarm optimization ； Taguchi Method

參考文獻

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