供應鏈管理主規劃排程之研究：考量產品結構設計與生產模式

Abstract

在競爭激烈的商業環境中，企業必須整合供應鏈成員中的政策及行為，才能使整體供應鏈利益最大化。而不同的生產模式會有不同型態的存貨，存貨的地點也不相同，供應鏈中採用的生產模式對於整體規劃結果會造成很大的影響，因此本研究在主規劃排程的主軸下，探討不同的生產模式及BOM表設計對供應鏈規劃的影響。 本研究考量三種生產模式：計劃式生產、組裝式生產及接單式生產，在有產能限制、多產品、多層級產品結構下，以間斷模式進行整體供應鏈的規劃。 供應鏈網路問題一般採用線性規劃與混合整數規劃建立模型並求取最佳解，本研究針對生產模式的規劃問題提出混合整數線性規劃模型：以最小化延遲成本、存貨成本及整備成本為目標。在本研究中，成本結構的設定對於各生產模式的規劃結果有很大的影響，因此不僅要考慮各節點的生產模式，也必須考量各成本的大小，才能使整體供應鏈最佳化。 本研究之規劃問題若以混合整數線性規劃模型求解，在問題規模龐大時，解題時間將大幅提升，不保證有解且無解時沒有其他資訊可以找出無解之原因。因此，本研究提出一啟發性演算法，使得本研究問題在有效率的時間下，得到一趨近最佳解之可行解決方案。 本研究啟發性演算法流程為：進行規劃排程之前置作業，接著針對各最終產品做需求群組，找出最佳群組方式，需求群組完成後再依據成本結構的設定進行群組內需求排序，最後則進行群組間的排序，依據此順序規劃每張需求。規劃之步驟為設定網路連結成本，尋找最小成本生產樹，決定最佳出貨時間，最後依據產能及成本的狀況選擇成本最低的規劃方式。 最後，本研究實做出此規劃排程系統，並進行情境分析，比較不同成本設定下對三種生產模式規劃的影響。本研究利用實際案例測試，驗證本演算法確實可行且具高效率性。

In a competitive business environment, it is very important to coordinate the policies and behavior of organizations and facilities in supply chain. Different production environments will lead different types of inventory, and it also causes different storage locations. Therefore, the production environment in supply chain has significant impact on the overall planning outcome. This study discusses three types of production environment: Make-to-Stock, Assemble-to-Order, Make-to-Order. Considering multiple final products, multi-level BOM, limited capacity and multiple discrete periods, this study focuses on “Master Planning” of “Advance Planning and Scheduling”, which is to determine a production and distribution plan of a supply chain network to fulfill all demands. The objective of this study is to minimize total delay cost, total inventory cost, and total setup cost. Owing to the great influence of cost structure configuration on production environment’s planning outcome, the cost should be taken into consideration when planning demands to optimize the performance of the overall supply chain. In previous study, “Mixed Integer Programming” is a popular way to solve the supply chain problems. In this study, a MIP model is also proposed. However, when the problem gets more complex, the MIP model becomes insolvable due to the time and computer resources it required. Therefore, this study proposes a heuristic algorithm named “Production Environment Master Planning Algorithm, PEMPA” to solve the problem efficiently. The algorithm consists of three steps: (1) Do the preliminary procedures. (2) Demand grouping and sorting. Demands will be grouped according to the required products and the capacity of the production tree, and then demands will be sorted by due date or quantity within the group, finally all group will be sorted by due date. (3) Planning demands sequentially until all demands are fulfilled. First, the cost for each link is set and the minimum cost production tree is found. Then, based on the capacity and the cost, PEMPA will choose the best shipping time and the most economical planning methods. To show effectiveness and efficiency of the heuristic algorithm, a prototype is constructed and scenario analysis is illustrated.