目前市場上商品需求型態千變萬化,導致無法正確預測商品需求數量、以及無法快速滿足顧客需求等問題,因此近年來所發展的供應鏈管理策略中經常被運用之延遲策略(postponement strategy),是很適合目前市場為滿足消費者的最佳方式之一,有效的延遲策略就是如何運用製造及物流兩者活動之整合,以幫助企業降低成本以及增加利潤。 本研究要探討的主要是製造延遲策略,研究的環境設定為多樣化產品的製造業者,適用對象主要是提供不同型態的多樣化商品,並將延遲策略與產品差異化運用於其中來建構出一生產流程,此生產流程具有推式模式與拉式模式;於推式模式中,共通性零組件或共通型模組大量生產,當顧客訂單到達時,依照訂單的產品種類與數量於後端的拉式系統進行組裝,此生產流程中建立成本模型,包含存貨成本、生產成本、缺貨成本;而生產流程可因產品差異化的分界點位置不同而區分為數個方案,並以模擬軟體來進行模擬與分析,計算系統總成本,分析與比較之後,找出產品的差異化界限在製造生產流程的最佳分界點,進而尋求推/式系統的最適化。 本研究亦針對不同的情境來進行模擬與成本分析,未來不同的產業可依照與產業特性相似的情境進行修改與運用,以求得對該產業的推/拉系統界線的最適點。此外,亦冀望研究成果能提供未來相關研究之參考。
Traditional supply chain manufacturing strategies are often categorized as either push or pull strategies. In the last few years a number of multi-nation corporations, such as DELL and HP, have started to employ a hybrid approach, so called push-pull supply chain strategy. In a push-based supply chain, production decisions are based long-term forecast, while the decisions are based on true customer demand for a pull- based supply chain. In a push-pull strategy, some stages of the supply chain are operated in a push-based manner while the remaining stages employ a pull-based strategy. Postponement, or delay product differentiation, is an example of a push-pull strategy. In postponement, the manufacturing process starts by producing a generic product up to that point in the process, which is differentiated to a specific end-product when order is received. In this research we focus on the manufacturing postponement which the first k operations are common operations to end-products. We call operation k as the last common operation, or push-pull boundary. In order to evaluate the implications of manufacturing postponement; i.e., deferring the last common operation k, we develop a simple expression for the total relevant cost based on a (s, Q) inventory control policy for the generic product. The total relevant cost for a given system that has operation k as the last common operation includes the processing costs, the inventory cost, and the stockout costs. We apply this model to analyze different scenarios that focus on the two-product example. Our experimental analysis shows that coefficient of variation in order size, unit holding cost, and stockout cost are the major factors that affect the location of the push-pull boundary in the manufacturing system. In our future studies, we plan to analyze the investment cost and the process time variation in the manufacturing system.