本研究探討整合單一產品含機器隨機性當機並(n+1)多次配送且完美重工之最佳生產時間，為兩次生產，兩次配送。假設在不完美的生產過程中，會產出不良品，待生產過程結束後，始可進行重工，本研究假設為完美重工，意即所有不良品皆可完全重工修復為良品。為了更符合業界實際情況，本研究將傳統EPQ(Economic Production Quantity)模型的連續配送假設為(n+1)次配送，後針對此問題建立數學模式。本研究針對上述假設建立三種數學模式：(1)情況一:當機情況發生在第一次生產過程中(第一次配送前)(2)情況二: 當機情況發生在第二次生產過程中(第一次配送後)(3)情況三:第一、二次生產過程皆不含當機情況發生。
最後整合此三種數學模式提出數值例子來驗證，並針對所需參數值做敏感度分析，期望本研究的數學模式能符合現今產業實際之情況，以供業界作為決策之參考。

This study investigated the production run time of a single production containing the random machine breakdown, (n+1) multiple of delivery and perfect rework, the two-stage production and two-stage delivery. Assuming an imperfect production process that will produce defective products, and they can all be reworked and repaired at the end of the production process. In actual situation the traditional EPQ (Economic Production Quantity) model continuous distribution assumption is not practical, we adope (n+1) multiple distribution to address it and build mathematical model for this problem. We study three types of mathematical models based on the above assumptions: (1) when the machine breakdown in the first stage of the production process (before the first delivery) (2) when the machine breakdown in the second stage of the production process (after first delivery), and (3) no breakdown happens.
Finally, integration of these three models are done, and numerical examples validation are provided and sensitivity analysis for the different parameter values are conducted, this study is expected to meet the actual situation of the industry today, and the results can be provided as a reference for their decision-making.

目錄
中文摘要 II
ABSTRACT III
致謝 IV
目錄 IV
圖目錄 VIII
表目錄 X
第一章 緒論 1
1.1 研究動機與目的 1
1.2 研究範圍界定與假設 2
1.3 研究方法 3
1.4 研究流程與架構 4
第二章 文獻探討 5
2.1 當機之相關文獻 6
2.2 多次配送之相關文獻 11
2.3 不良品重工之相關文獻 16
第三章 模式的建立與推導 22
3.1 情況一建構 22
3.1.1 問題描述 22
3.1.2 符號說明 22
3.1.3 情況一假設與推導 26
3.2 情況二建構 30
3.2.1 問題描述 30
3.2.2 情況二假設與推導 30
3.3.1 問題描述 34
3.3.2 情況三假設與推導 34
3.4 整合情況一、情況二、情況三之生產模式分析 38
第四章 實例驗證與敏感度分析(一)配送次數的差別 (N+1)次VS (N)次 39
4.1 實例數值驗證與敏感度分析 39
4.1.1判斷本研究是否存在極小值 41
4.1.2最佳生產時間搜尋之演算法 41
4.2本研究模式一敏感度分析 43
4.3本研究模式一與過去研究(N)次配送比較(方案一) 47
4.4本研究模式一與過去研究(N)次配送比較(方案二) 53
4.5本研究模式一與過去研究(N)次配送比較(方案三) 58
4.6本研究模式一與過去研究(N)次配送比較(方案四) 64
4.7本研究模式一與過去研究(N)次配送之總比較 69
第五章 實例驗證與敏感度分析(二) B/D VS NO B/D 70
5.1 本研究與無當機模式之敏感度分析 70
5.2 本研究與無當機模式(卻發生當機)比較 72
5.3 本研究與學者張智凱[50] (N)次配送相比較 77
第六章結論與未來研究方向 81
6.1 本研究結論與貢獻 81
6.2 未來方向 82
參考文獻 83
【附錄A】情況一基本假設與成本推導 1
【附錄B】情況二基本假設與成本推導 1
【附錄C】情況三基本假設與成本推導 1

 
圖目錄
圖3- 1情況一第一次生產過程含當機之良品存貨圖 27
圖3- 2情況一第一次生產過程含當機之不良品存貨圖 29
圖3- 3情況二第二次生產過程含當機之良品存貨圖 31
圖3- 4情況二第二次生產過程含當機之不良品存貨圖 33
圖3- 5情況三第一、第二次生產過程中皆未發生當機之良品存貨圖 35
圖3- 6情況三第一、第二次生產過程中皆未發生當機之不良品存貨圖 37
圖4- 1生產週期時間與期望週期總成本之關係圖 42
圖4- 2平均當機間隔時間(1/Β)與期望週期總成本之關係圖 43
圖4- 3平均當機間隔時間(1/Β)、不良率變動與週期總成本之關係圖 44
圖4- 4不良率變動與期望週期總成本之關係圖 45
圖4- 5不良率變動、當機間隔時間對期望週期總成本之曲面圖 46
圖4- 6生產時間相同、配送次數不同之總運送成本比較圖 50
圖4- 7生產時間相同、配送次數不同之持有成本比較圖 51
圖4- 8生產時間相同、配送次數不同之期望週期總成本比較圖 52
圖4- 9生產時間相同、配送次數相同之總運送成本比較圖 56
圖4- 10生產時間相同、配送次數相同之持有成本比較圖 56
圖4- 11生產時間相同、配送次數相同之期望週期總成本比較圖 57
圖4- 12分別的最佳生產週期時間，配送總次數不同之運送成本比較圖 61
圖4- 13分別的最佳生產週期時間，配送總次數不同之持有成本比較圖 62
圖4- 14分別最佳生產週期時間，配送總次數不同期望週期總成本比較圖63
圖4- 15分別的最佳生產週期時間，配送總次數相同之運送成本比較圖 67
圖4- 16分別的最佳生產週期時間，配送總次數相同之持有成本比較圖 67
圖4- 17分別最佳生產週期時間，配送總次數相同期望週期總成本比較圖68
圖4- 18不同方案之期望週期總成本比較圖 69
圖5- 1本研究與無當機模式之平均當機間隔時間關係圖 70
圖5- 2本研究與無當機模式之不良率變動與期望週期總成本之關係圖 71
圖5- 3本研究與無當機模式(卻發生當機)之期望週期總成本關係圖 72
圖5- 4本研究與無當機模式(發生當機)之維修成本比較圖 74
圖5- 5本研究與無當機模式(卻發生當機)之運送成本比較圖 75
圖5- 6本研究與無當機模式(卻發生當機)之期望週期總成本比較圖 76
圖5- 7本研究與(N)次配送之維修成本比較圖 78
圖5- 8本研究與(N)次配送之持有成本比較圖 79
圖5- 9本研究與(N)次配送之期望週期總成本比較圖 80

 
表目錄
表1- 1基本假設表 2
表3- 1參數符號表 23
表4- 1模式一基本假設數據表 40
表4- 5本研究與過去學者張智凱[50]之比較總表 47
表4- 6本研究之參數表(方案一) 47
表4- 7學者張智凱[50]之參數表(方案一) 49
表4- 8本研究之參數表(方案二) 53
表4- 9研究學者張智凱[50]之參數表(方案二) 54
表4- 10本研究之參數表(方案三) 58
表4- 11研究學者張智凱[50]之參數表(方案三) 59
表4- 12本研究之參數表(方案四) 64
表4- 13研究學者張智凱[50]之參數表(方案四) 65
表5- 1本研究AR當機模式之參數表(設M=5000、Β=4) 73
表5- 2無當機模式(卻發生當機)之參數表(設M=5000、Β=4) 73
表5- 3本研究AR當機模式之參數表(設M=5000、Β=4) 77
表5- 4 (N)次配送之參數表(M=5000、Β=4) 77

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