臺灣博碩士論文加值系統

由於供應鏈體系的競爭益趨激烈，製造商亟需一套有效的訂單管理系統來管理及允諾顧客的訂單需求，其中以可允諾量(Available-to-Promise, ATP)的概念備受重視。可允諾量的機制能夠使製造商得以快速地允諾顧客訂單並且可靠地告知顧客訂單的預定交期，進而提高顧客滿意度，同時有效地管理及分配製造商之有限生產與物料資源。
在此同時，為了快速反應顧客需求與減少過多存貨，企業已發展使用模組化與共同性物料的概念，將客製化的時點延遲以滿足少量多樣的顧客需求。採用共同性物料可以減少製造商對於物料的管理成本、與供應商交涉的交易成本，以及由於風險分攤效果所造成的安全存貨水準下降進而減少存貨成本。
本研究運用可允諾量的概念，以製造商的利潤觀點，同時考量其生產、物料、銷售等供給面與需求面限制，建立最佳化可允諾量分配模型，提供製造商作為決策支援參考之用。同時透過實驗設計與模式模擬，探討共同性物料對於可允諾量分配模型的影響。由實驗設計的結果我們得到以下四點結論：
1.共同性物料的風險分攤效果在產能有限的情況下難以顯現；
2.共同訂購為採用共同性物料的主要優點；
3.需求變異對於採用共同性物料的影響顯著；
4.相較於傳統的按比例分配法則，本模型可以使製造商達到較佳的利潤與顧客服務。
本研究證明，在產能有限的情況下，共同性物料由於其共同訂購的優點，就長期而言仍能為製造商帶來較高的利潤，但所獲利潤的高低則受限於需求變異的影響。大體而言，需求變異低時由於穩定的訂貨頻率可以為製造商帶來較高的利潤；當需求變異加大，製造商則因物料訂購頻率降低而遭受較大的違約成本。同時由於本模型將各訂單的收入與成本資訊皆納入考量，在配合顧客需求、物料供給與產能限制的情況下，提供製造商對於各訂單最適的可允諾量，使其能在充分利用產能的同時，獲取最大的利潤。

In a customer-driven market, the customer not only needs an immediate order promise but also wants reliable order fulfillment. Motivated by these challenges, the available-to-promise (ATP) mechanism has increasingly attracted the manufacturers’ attention as an order management tool for enhancing customer service and sustaining profitability. The ATP planning function enables the manufacturer to exploit capacity and material opportunities to promise orders.
At the same time, in order to respond quickly to customer orders with reasonable stock levels, manufacturers have adopted common components to fulfill various demands of small quantities. Common components enable manufacturers to gain benefits from risk pooling and order pooling.
This thesis is aimed to develop an optimization-based available-to-promise allocation model with consideration of common components. The model can provide manufacturers an optimal solution for customers’ orders considering the constraints of both material and production capacities. In addition, we explore the impacts of common components on the performance of the optimization model through design of experiments and simulation. We conclude that:
1.Risk pooling effects are reduced under a limited capacity constraint.
2.Order pooling effects are the main benefits of common components.
3.Demand variation has a significant effect on the performance of common components.
4.Compared to proportional allocation method, the optimization model achieves a higher profit and better customer satisfaction for manufacturers.
We prove that under the condition of limited capacity, adopting common components achieves higher profits in the long run because of the significant order pooling effects. In general, low demand variation results in stable order frequencies of materials and higher profits. As demand variation gets higher, manufacturers achieve cost savings from significant order pooling effects. The optimization model fulfills orders with full consideration of resource constraints and customer demands. It enables manufacturers to achieve higher profits and utilize capacity in an effective and efficient way.

第一章 緒論..................................................1
1.1 研究動機.................................................1
1.2 研究目的.................................................3
1.3 研究方法.................................................4
1.4 論文架構.................................................5
第二章 文獻探討..............................................6
2.1 供應鏈管理...............................................6
2.2 先進規劃與排程系統.......................................7
2.2.1 先進規劃與排程系統的演進...............................7
2.2.2 先進規劃排程之應用架構.................................7
2.3 需求承諾.................................................8
2.4 訂單達交與訂單允諾之相關探討.............................10
2.5 共同性物料...............................................12
2.5.1 共同性物料模型.........................................12
2.5.2 共同性物料指標.........................................15
2.6 小結.....................................................17
第三章 最佳化可允諾量分配模型的建立..........................18
3.1 模型假設.................................................18
3.2 模式建立.................................................19
3.2.1 註標說明...............................................19
3.2.2 決策變數...............................................19
3.2.3 輸入參數...............................................19
3.2.4 數學模型...............................................21
3.2.5 模型說明...............................................22
3.3 小結.....................................................23
第四章 情境模擬與實際資料探討................................26
4.1 情境實驗設計說明.........................................27
4.1.1 參數設計...............................................27
4.1.2 實驗設計...............................................29
4.2 模擬結果分析與討論.......................................32
4.2.1 利潤與訂單滿足率分析...................................32
4.2.1.1 利潤分析.............................................32
4.2.1.2 訂單滿足率分析.......................................42
4.2.2 不同程度之共同性物料對可允諾量分配模型的影響...........49
4.2.2.1 共同性物料對於製造商利潤的影響.......................49
4.2.2.2 共同性物料對於製造商訂單滿足率的影響.................52
4.2.3 小結...................................................55
4.2.3.1 情境模擬之結果.......................................55
4.2.3.2 與之前學者研究結果之異同.............................58
4.3 實際資料探討.............................................61
4.3.1 產品與物料資料.........................................61
4.3.2 最佳化與可允諾量分配模型結果分析.......................63
4.3.3 最佳化模型與傳統之比例分配法則之比較...................67
4.3.3.1 比例分配法則.........................................67
4.3.3.2 兩模式之結果比較.....................................68
第五章 結論與未來研究方向....................................74
5.1 結論.....................................................74
5.1.1 本研究結論.............................................74
5.1.2 研究貢獻...............................................75
5.2 研究限制.................................................75
5.3 未來研究方向.............................................76
參考文獻.....................................................77

[1]陳飛龍、蔡紹達、洪一仁, “整合供給與需求的供應鏈配銷系統”, Journal of the Chinese Institute of Industrial Engineers, Vol. 17, No. 6, pp. 671-681, 2000.
[2]APICS. Dictionary, 6th ed. Falls Church, VA: American Production and Inventory Control Society, 1987.
[3]Balakrishnan, A. and Geunes, J., “Requirements planning with substitutions: Exploring bill-of-materials flexibility in production planning”, Manufacturing & Service Operations Management, 2(2), 166-185, 2000.
[4]Baker, K.R., Magazine, M.J. and Nuttle, H.L.W., “The effect of commonality on safety stocks in a simple inventory model”, Management Science, 32, 982-988, 1986.
[5]Chen, C.Y., Zhao, Z.Y. and Ball, M.O., “Quantity and due date quoting available to promise”, Information Systems Frontiers 3:4, 477-488, 2001.
[6]Christopher, M., Logistics and Supply Chain Management. London: Pitman Publishing, 1992.
[7]Collier, D.A., “The measurement and operating benefits of component part commonality”, Decision Science, 12, 85-96, 1981.
[8]Collier, D.A., “Aggregate safety stock levels and component part commonality.” Management Science, 28, 1296-1303, 1982.
[9]Douglas, C. Montgomery, “Design and Analysis of Experiments”, Wiley, 5th edition, 2001.
[10]eB2X Inc. “Why promising orders? How strategic order promising helps supply chains compete in the new economy”, http://www.eb2x.com, 2000.
[11]Erengüç, Ş.S., Simpson, N.C., and Vakharia, A.J., “Integrated production/ distribution planning in supply chains: an Invited review”, European Journal of Operational Research, 115, 219-236, 1999.
[12]Eynan, A., “The impact of demands’ correlation on the effectiveness of component commonality”, International Journal of Production Research, 34, 1581-1602, 1996.
[13]Eynan, A. and Rosenblatt, M., “Component commonality effects on inventory costs”, IIE Transactions, 28, 93-104, 1996.
[14]Gerchak, Y., Magazine, M.J. and Gamble, A.B., “Component commonality with service level requirements”, Management Science, 34, 753-760, 1988.
[15]Gerchak, Y. and Henig, M., “Component commonality in assemble-to-order system: models and properties”, Naval Research Logistics, 36, 61-68, 1989.
[16]Hariharan, R. and Zipkin, P., “Customer-order information, leadtimes, and inventories”, Management Science, 41, 1599-1607, 1995.
[17]Hayes, R.H., Wheelwright, S.C. and Clark, K.B., “Dynamic Manufacturing”, The Free Press, New York, 1988.
[18]Hillier, M.S., “Product commonality in multiple-period, make-to-stock systems”, Naval Research Logistics, 46, 737-751, 1999.
[19]Hillier, M.S., “Component commonality in multiple-period, assemble-to-order systems”, IIE Transactions, 32, 755-766, 2000.
[20]Hillier, M.S., “The costs and benefits of commonality in assemble-to-order systems with a (Q,r)-policy for component replenishment”, European Journal of Operational Research, 141, 570-586, 2002.
[21]i2, RHYTHM Factory Planer User Manual, 1999.
[22]Jönsson, H. and Silver, E.A., “Common component inventory problems with a budget constraint: Heuristics and upper bounds”, Engineering Costs and Production Economics, 18, 71-81, 1989.
[23]Kilger, C. and Schneeweiss, “Demand fulfillment and ATP” In: Stadtler, H, Kilger, C, eds. Supply Chain Management and Advanced Planning Concepts, Models, Software and Case Studies Berlin, Germany: Springer, 135-148, 2000.
[24]Manugistics Inc. “Delivering on customer promises — A critical component for eBusiness successs”, http://www.manugistics.com, 2000.
[25]Stadtler, H. and Kilger, C., Supply Chain Management and Advanced Planning Concepts─Models, Software and Case Studies: Springer, 2000.
[26]Taylor, S.G. and Plenert, G.J., “Finite capacity promising”, Production and Inventory Management Journal, 40, 50-56, 1999.
[27]Wacker, J.G.. and Trevelen, M., “Component part standardization: an analysis of commonality sources and indices”, Journal of Operations Management, 6, 219-244, 1986.