接單裝配生產環境中物料清單內各品項之生產規劃決策問題; Make to Stock or Make to Order for BOM items in ATO Environment

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Title:	接單裝配生產環境中物料清單內各品項之生產規劃決策問題;Make to Stock or Make to Order for BOM items in ATO Environment
Authors:	陳郁鈞;Yu-Jiun Chen
Contributors:	工業管理研究所
Keywords:	規劃策略;接單裝配生產;接單式生產;計畫式生產;物料清單;Poisson process;Assemble-to-Order;Product Structure;BOM;Inventory/Production;Planning Strategy;AMPL/MINOS
Date:	2004-06-14
Issue Date:	2009-09-22 14:13:56 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	本論文旨在解決接單裝配生產環境(Assemble to Order, ATO)下，多樣產品之BOM內各階層各品項的生產規劃策略問題。所謂物料清單（Bill of Material, BOM），是指各個產品所有次裝配品、零件、原物料和所需要的數量之清單，而為了符合接單裝配生產的特性，我們使用variant BOM取代一般較常使用的單一產品物料清單。variant BOM是利用class item來描述多樣最終產品差異的品項。在問題中我們以一固定的比例分配來描述多樣產品間需求的不同。給定一variant BOM，決定那一個品項適合於接單式生產(Make to Order, MTO)，哪一個品項適合於計畫式生產(Make to Stock, MTS)。問題中具有MTO與MTS並存的生產環境之特性。本研究延伸陳景雯 (2003) 研究，不同於接單生產環境，我們針對接單裝配生產環境，建立多樣產品之BOM品項的生產決策問題(MTS/MTO)之非線性、整數規劃模型。目的為求得最小化成本下BOM 內各項生產規劃方式。MTS品項通常有一存貨政策 (inventory policy)，MTO品項則不儲存任何存貨。在應用方面，我們將所提出的數學模型以及啟發式演算法應用在不同的案例當中。利用不同的系統參數設定來評估是否模型能夠產生我們事先所預期的結果，再藉由比較窮舉演算法及啟發式演算法所求得的解及系統執行的時間，以獲得其差異所在。 This paper studies how to decide a planning strategy for each assembly and raw material included in a variant Bill of Material (variant BOM) in the Assemble-to-order (ATO) environment. The arrival rate of the customer order which contains many different types of products follows a stochastic process. The individual arrival rates of different types of products are determined by a set of fixed probabilities. We try to determine each BOM item whether it would be assigned to make-to-order (MTO) planning strategy or make-to-stock (MTS) planning strategy. Furthermore, MTS items follow a (Q, r) inventory/production policy and are procured externally whereas MTO items are produced internally. On the basis of ATO manufacturing environment, we conduct a nonlinear, integer programming model to decide each BOM item whether it would be assigned to MTO or MTS and determine the replenishment batch Q and reorder point r for MTS item at the same time. For the Poisson demands, our objective is to lower the production lead time and minimize the total cost such as setup cost, holding cost, backorder cost and penalty cost. We extend the heuristic developed by [Chen, 2003] and use the AMPL/MINOS mathematical software to solve the model. The proposed model has been implemented by AMPL/MINOS. In the validation, we want to test whether this model can react our expected system behaviors by setting different parameter values. In the evaluation, we want to see how good and how fast does our heuristic show by comparing the complete enumeration approach.
Appears in Collections:	[Graduate Institute of Industrial Management] Electronic Thesis & Dissertation

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