Developing a Two-phase Model for Selecting Green Supplier for Product Part Change
|關鍵字:||產品零件變更;綠色零件供應商評選;模糊層級分析法;人工免疫系統;粒子群演算法;Product Part Change;Green Supplier Selection;Fuzzy Analytic Hierarchy Process;Artificial Immune System;Particle Swarm Optimization|
|摘要:||在激烈的全球化產業競爭下，企業必須持續改善現有產品，才能保持競爭力。藉由產品零件變更(Product Part Change, PPC)的活動，來降低成本及提升品質，是改善產品的方法之一。當產品有變更零件之需求時，須改變或重新設計部份之零件，故變更後之零件需重新選擇供應商。此外因為環保意識的抬頭及相關環保規範的要求，評選供應商之過程考量綠色準則已是必然的趨勢。過去的研究都是假設變更之零件已知的情況下，針對變更後的零件考量多種評估準則，以從供應商候選者中挑選出最具競爭力的合作夥伴，至於哪些零件最具變更潛力與價值的問題則甚少被探討到，且評估準則中也未考慮到綠色準則相關的議題。因此，本研究之主要目的是提出一個兩階段模式以在產品需變更零件的情況下，快速而系統化地評選出最具改變或重新設計價值之零件組合及變更之後符合環保規範和具備成本、時間效益的最佳零件供應商組合。本研究以高度模組化的產品為研究對象，利用物料清單(Bill of Material, BOM)了解產品中模組與零件的組成結構，在第一階段中以產品模組為候選方案，利用專家訪談的方式，使用模糊層級分析法(Fuzzy Analytic Hierarchy Process, FAHP)選出產品中最值得變更的模組，該階段除了考量品質、時間、維護、成本等因素外亦同時考量歐盟提出的WEEE/RoHS 指令等綠色準則，再按照品質、成本目標對該模組底下的零件進行改變或重新設計；第二階段則是針對變更後的模組中之各零件，發展一套最佳零件供應商組合之評選模式。本階段參考上一階段之評估準則建構最佳化數學規劃模式，並利用人工免疫系統(Artificial Immune System, AIS)結合離散二元版本粒子群演算法(Discrete Binary Version of The Particle Swarm Algorithm, DBPSO)求解數學模式，以找出最適合之零件供應商組合。當產品有變更需求且決策者無法決定將資源用於變更產品中之哪些零件時，透過本研究提出的二階段評估程序，即可以最小的評估成本與時間，快速而有系統化地找出最具變更價值的模組，及在符合環保規範下挑選出該模組變更後之零件供應商之最佳組合，以有效提升變更後的新產品之價值，並儘快上市，搶佔先機，以保有市場之競爭力。|
With fierce global competition, enterprises must continue to improve their existing products and remain competitive. One way to improve products is to reduce costs and improve quality by the activity of Product Part Change (PPC). When product parts need to be changed or re-designed, suppliers for the modified product parts need to be re-selected. In addition, taking green standards into account is an inevitable trend for the evaluation process of the selection of suppliers, because of arising awareness and related regulations about environmental protection. Previous studies normally assumed that changed parts are given, considered multiple evaluation standards for the changed parts, and then chose the most competitive supplier among candidate suppliers. However, it has been hardly investigated which parts have the most potential and value to be changed, and green standards have not been taken into account for the evaluation standards. Therefore, the purpose of this study is to develop a two-phase model regarding product parts that need to be changed. The two-phase model can quickly and systematically select not only the part combinations that are most worth being changed or re-designed but also the suppliers that are most cost-effective and time-efficient and meet the requirements of environmental protection for the changed parts. The subjects of the present study are highly modular products. This study is to understand the structure of product modules and parts using Bill of Material (BOM). In the first phase, product modules are considered the candidate solution, and with interviewing experts, Fuzzy Analytic Hierarchy Process (FAHP) is used to select the module that is most worth being changed among products. In addition to the factors such as quality, time, maintenance, and cost, the green standards like WEEE/RoHS proposed by the European Union are also taken into account. Then the parts of the module are changed or re-designed according to the required quality and cost. In the second phase, for each part of the changed module, a selection model for the selection of the best parts suppliers is developed. This phase constructs the best mathematical programming model by referring to the evaluation standards in the first phase, and solves the mathematical model by using Artificial Immune System (AIS) combined with Discrete Binary Version of The Particle Swarm Algorithm (DBPSO) to identify the most suitable parts suppliers. When products need to be changed and the decision maker cannot decide which parts the resource should be applied to, the two-phase evaluation processes proposed by this study can quickly and systematically select the module that are most worth being changed with the minimal evaluation cost and time but also select the best combination of parts suppliers for the changed module according to the requirements of environmental protection. This model not only can enhance the value and competitiveness of new changed products but also can introduce the products into the market as soon as possible to seize opportunities.