臺灣博碩士論文加值系統

在許多製造系統中，生產技術的選擇會支配產能大小而使得生產批量有上限，因此技術成本與生產批量大小有直接關係。本研究主要擴展了Khouja (2005)所提出的含技術選擇之存貨模式，建立一個由技術選擇來決定生產批量大小的模式，加入考慮不完美品質項目的影響，並且假設在進行全檢後將不良品以單一批量折扣的方式賣出。本研究之目的是在以上考慮之下，決定有最大利潤之最佳生產批量，共提出三個存貨模式，第一為確定性模式，第二為具有模糊不良率的模式，第三為具有隨機不良率的模式。新產品的不良品形成原因與不良率估計往往有賴專家的經驗判斷，故使用模糊數來表達專家口語上之意見，對管理者而言較為實用。當有足夠的生產資料時，便能夠利用統計方法來估計不良率的大小，以機率分配來描述不良率的不確定性。因此本文除了討論確定性模式之外，更進一步探討不良率為模糊數與不良率為隨機變數兩種不確定性模式。
產品的不良率會受到原料性質、系統條件設定或產品設計等因素的影響，因此不良率具有不確定性存在。當沒有足夠歷史資料來推論不良率的機率分配時，可以利用模糊理論來描述不良率的不確定性。在本研究的模糊模式中，利用Yager排序法來估計每單位時間的利潤，由總利潤函數推導出最佳的生產批量，以提供決策者選擇合適的生產技術與產能大小。

For manufacturing systems, the production technology usually has an influence on the production lot size and therefore delimits the capacity. The technology cost is closely related with the production lot size. This research extends the inventory model, proposed by Khouja (2005), to formulate the models by treating the lot size as the decision variable at the technology selection stage and considering products with imperfect quality. It is assumed that poor-quality items will be sold as a single batch after the 100% screening process. The objective of this research is to determine the optimal production lot size to maximize the total profit. Three inventory models are presented for considering the fixed defective rate, the fuzzy defective rate, and the stochastic defective rate, respectively. For new products, the determination of the defective rate is usually based on the judgment of experts, practically using fuzzy numbers to express experts’ linguistic descriptions. We can use statistical techniques to estimate the defective rate, and use probability distribution to describe the uncertainty of the defective rate, once production data are sufficient. Considering the above scenarios, we not only formulate the deterministic model, but investigate two kinds of uncertain models.
The defective rate of a lot size is affected by the quality of raw material, the system’s configurations, the product design, etc. We can use the fuzzy theory to describe the uncertainty of the defective rate when historical production data are insufficient. In the fuzzy model, we employ the Yager’s ranking method to estimate the total profit per unit time, and then derive the optimal production lot size by the total profit function. The decision-makers can use the solutions to select appropriate production technology and production lot size.

摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
符號表 viii
第一章 緒論 1
1.1 研究動機與目的 1
1.2 研究範圍與界定 2
1.3 研究方法 3
1.4 研究架構與流程 4
1.5 論文概要 6
第二章 文獻探討 7
2.1 具不完美品質之存貨模式 7
2.2 考慮技術選擇之存貨模式 8
2.3 模糊理論在存貨模式的應用 9
2.4 模糊集合理論 11
2.4.1 模糊集合 11
2.4.2 模糊數 14
2.4.3 模糊數的基本運算 16
2.4.4 Yager排序法 16
第三章 考慮不完美品質與技術選擇之存貨數學模式 20
3.1 模式基本假設與參數定義 20
3.2 確定性模式 22
3.2.1 考慮技術選擇之存貨模式 (Khouja, 2005) 22
3.2.2 確定性模式之建立 25
3.3 不確定性模式 29
3.3.1 模糊模式之建立 30
3.3.2 隨機模式之建立 33
3.4 小結 35
第四章 例題演算與分析 36
4.1 例題演算 36
4.1.1 確定性模式 37
4.1.2 模糊模式 38
4.1.3 隨機模式 39
4.2 參數分析 41
4.2.1 確定性模式與技術選擇存貨模式之比較 41
4.2.2 確定性模式與模糊模式之比較 45
4.3 小結 47
第五章 結論與未來研究方向 49
5.1 研究成果 49
5.2 未來研究方向 50
參考文獻 52
附錄 55

張永彥，塑膠模具設計學，全華圖書，民國九十四年。

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