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研究生： 方賢凱
Fang, Heisan-kai
論文名稱： 分批運送環境下考慮不良品退貨之生產與採購整合模式
An integrated model of production and purchase with returned defective items in lot-splitting delivery environment
指導教授： 張秀雲
Chang, Shiow-yun
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業與資訊管理學系
Department of Industrial and Information Management
論文出版年： 2007
畢業學年度： 95
語文別： 中文
論文頁數： 61
中文關鍵詞： 退貨 、瑕疵品 、整合模式 、偉伯分配 、分批運送
外文關鍵詞： lot-splitting delivery, Weibull Distribution, coordination model, flaw items, return
相關次數： 點閱：121  下載：1 
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    • 過去學者大多在品質穩定下探討及時化分批運送問題，針對個別供應商與採購商決定最佳生產與採購批量，或是整合買、賣雙方成本模式並決定出共同生產與採購批量。現實生活裡，供應商常會因為某些因素在生產過程中產出不良品。有鑑於此，在整合模式架構下，本研究考量買方對於接收到的批量產品採取全數檢驗，在檢測期內發現產品失效或瑕疵品將退回給供應商並要求換新或瑕疵修復的情況。本研究假設產品失效服從指數或偉伯分配並求解整合模式之運送批量、運送次數與生產/採購數量，並且和學者Kim與Ha(2003)未退貨整合模式求解出決策變數與成本作比較。之後，再探討影響決策變數之因子。

    結果上，本模式決策變數可以獨立求解出。參數分析上，當不良率增加後，運送批量增加，運送次數減少。本模式和未退貨模式比較後，所求解的運送批量多於未退貨模式所得出，當失效服從指數分配時，求解出運送次數少於未退貨模式所求解出，當失效服從偉伯分配時，求解出運送次數多於未退貨模式所求解出。最後，探討形狀參數與尺度參數影響決策變數後，當形狀參數越大，尺度參數越小時，運送批量越小，生產/採購數與運送次數越大。相反的，當形狀參數越小，尺度參數越大時，運送批量越大，生產/採購數與運送次數越小。固定尺度參數後，形狀參數越大時，運送批量越小，生產/採購數與運送次數越大。

    In the past, most scholars studied just-in-time lot-splitting delivery problems in well quality environment. Aiming single supplier and single buyer, scholars determined optimal production and order quantity or developed a buyer-supplier coordination model to determine optimal production/order quantity. In practice, suppliers usually produce some defective items during production process. Therefore, on the basis of coordination model, this research considers buyers take complement inspection to receive delivery size. When they find failure or flaw items, they will return defective items back to suppliers and ask suppliers renew and repair flaw items. This research assumes failure follows Exponential Distribution or Weibull Distribution and solves delivery size, the number of deliveries and production/order quantity. In the bargain, we compare decision variables of returned model with that Kim and Ha did at 2003. After that, this research studies factors that influence the value of decision variables.
    In conclusion, decision variables can be solved individually. In parameter analysis, when defective rate increases, delivery size will increase and the number of deliveries will decrease. In comparison, delivery size of returned model is larger than that of without returned model. If failure follows Exponential Distribution, the number of deliveries in returned model is smaller than that without returned model. On the other side, when failure follows Weibull Distribution, the number of deliveries in returned model is larger than that without returned model. Finally, the research studies how the shape and scare parameters influence decision variables. If the shape parameter increases and the scare parameter decreases, delivery size will decrease, production/order quantity and the number of deliveries will increase. On the other side, when the shape parameter decreases and the scare parameter increases, delivery size will increase, production/order quantity and the number of deliveries will decrease. If the scare parameter is fixed, as the shape parameter increase, delivery size will decrease, production/order quantity and the number of deliveries will increase.

    摘要................................................i Abstract............................................ii 誌謝................................................iii 目錄................................................iv 表目錄..............................................vi 圖目錄..............................................vii 第一章　緒論........................................1 　1.1　研究背景與動機...............................1 　1.2　研究目的.....................................2 　1.3　研究範圍限制與流程架構.......................3 第二章　文獻探討....................................5 　2.1　多次運送批量模式.............................5 　2.2　不良品處理問題文獻...........................8 　2.3　生產、採購整合及其它相關文獻.................10 　2.4　小結.........................................11 第三章　模式建立....................................12 　3.1　問題描述.....................................12 　3.2　相關基本假設與符號定義.......................13 　　3.2.1　基本假設.................................15 　　3.2.2　相關符號定義.............................15 　3.3　期望失效數、期望退貨率.......................16 　3.4　退貨下及時化模式建立.........................17 　　3.4.1　產品失效服從指數或偉伯分配之模式建立 ....22 　　3.4.2　退貨後整合模式求解.......................23 　3.5　小結.........................................25 第四章　數值分析....................................27 　4.1　數值範例.....................................27 　4.2　退貨與未退貨模式之決策變數比較...............29 　4.3　影響退貨後求解決策變數值因子分析.............39 　4.4　小結.........................................41 第五章　結論與未來研究方向..........................43 　5.1　研究結論.....................................43 　5.2　未來研究方向.................................44 參考文獻............................................45 附錄A　退貨模式之決策變數求解過程...................48 附錄B　退貨與未退貨模式求解變數與成本差距率圖.......52 自述................................................61

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