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系統識別號 U0026-0807201419345500
論文名稱(中文) 考量不完美生產製程與保養政策於生產具保固產品之經濟生產批量模式
論文名稱(英文) Economic Production Quantity Model with Imperfect Process and Preventive Maintenance for Products Sold with Warranty
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 102
學期 2
出版年 103
研究生(中文) 蘇裕淵
研究生(英文) Yu-Yuan Su
學號 R36011076
學位類別 碩士
語文別 英文
論文頁數 51頁
口試委員 指導教授-林清河
口試委員-耿伯文
口試委員-李昇暾
口試委員-林義旭
口試委員-林育德
中文關鍵字 經濟生產批量模型  不完美生產製程  最小維修  預防保養  保固 
英文關鍵字 EPQ model  imperfect production process  minimal repair  preventive maintenance  warranty 
學科別分類
中文摘要   對於現今大多數製造業來說,策略制定的最終目標即為最小化總成本。早期,生產線之存貨管理一直是常用來處理成本與產量的方式,學者發展出經濟生產批量(EPQ)模型來探討生產成本、批量與週期時間以最小化總成本。近年來,學者結合製程情況與產品品質議題來改良EPQ模型,許多研究皆從這兩種構面下手,而本研究另考量產品保固政策,除了能更貼近實際製程上對於成本項的考量,也同時考慮到消費者所感受之產品價值。在考量最小免費維修保固政策的情況下,提出改良後的EPQ模型以最佳化生產週期時間與生產批量,另外,也考慮一不完美生產製程於預防保養政策之中,該製程服從退化且具有遞增失效率的機率分配。
  假設此生產製程一開始於可控制的狀態進行生產,生產出品質良好的產品;運作一段時間後,該生產製程可能於某一生產時間點退化而跳至不可控制的狀態,爾後生產中的某些產品可能為不合格產品,在此將生產不合格產品之機率將納入模型中計算與考量,並於生產週期結束時對於不合格產品進行重製。此外,本研究也探討對於售出產品後給予保固政策,此一概念能涵蓋製程的定期檢驗政策以節省檢驗成本與檢驗時間的支出,並且對於在保固期間內失效的產品能夠給予最小的免費維修,因此,對於不合格產品(重製過後)的保固成本將會比合格產品的保固成本來得高,所以本研究模型透過批量大小來控制生產出不合格品的比例,以降低保固成本的支出。
  整體來說,本研究考量了最小維修、預防保養、產品重製與保固等政策,以及存貨可能會在製程進行預防保養時間過長而有缺貨現象,建立改良後的經濟生產批量模型,希望透過該模型以得到最佳生產週期時間、最小化期望總成本,並利用數值範例代入模型中配適模型的適用情形,再進行敏感度分析以及實驗設計之田口方法分別進行單參數與多參數分析,分別探討各個參數與參數組合對於期望總成本影響的情況。
英文摘要 This paper proposes an integrated economic production quantity (EPQ) model to determine the optimal production run-time and production lot-sizing under a minimal free-repair warranty (FRW) policy. It advocates a strategic preventive maintenance (PM) plan for an imperfect production process following a deterioration distribution with an increasing failure rate (IFR). It is assumed that the production system begins in the in-control state that produces items with high or perfect quality. Over time, the production process may deteriorate to the point to which non-conforming items are fabricated. The probability of non-conforming items being produced is thus taken into account to identify the time at which the process is in the out-of-control state. Furthermore, instead of using an inspection policy which monitors the process, a warranty policy for products sold is considered which includes the concept of the inspection cost in order to reduce the inspection time during the process. This model can be used for products sold within the warranty period, which follows a failure distribution. In this case, the warranty cost to service non-conforming items is much greater than the cost to service conforming items, so the EPQ model controls the proportion of non-conforming items produced through lot sizing, resulting in a reduction in the warranty cost. In brief, minimal repair, PM, rework and warranty policy are considered in the model. An inventory shortage may occur during the PM, which is also considered as the shortage cost. The objective of this paper is to obtain the optimal production run-length which minimizes the expected total cost per cycle. A numerical example is provided to illustrate the effect of changes in the various parameters on the optimal solution. A sensitivity analysis and the Taguchi method are applied to the EPQ model with respect to the key parameters.
論文目次 I. Preface 1
1.1 Research Background and Motivation 1
1.2 Research Objectives 2
1.3 Research Flow and Outline 5
II. Literature Review 7
2.1 Imperfect Production Process 7
2.1.1 Combination with Inspection or Maintenance 8
2.2 Preventive Maintenance 9
2.2.1 Reactive Maintenance 10
2.2.2 Periodical Maintenance 10
2.2.3 Minimal Repair/Maintenance 11
2.3 Contingency Strategy: Production and Preventive Maintenance 11
2.4 Rework 12
2.5 Warranty Policy 13
2.6 Inventory Shortage 14
2.7 Summary of Literature Review 15
III. Model Development 16
3.1 Introduction 16
3.2 Notation 19
3.3 Assumptions and Requirements 20
3.4 Model Structure 21
3.4.1 Setup Cost 22
3.4.2 Holding Cost 22
3.4.3 PM Cost 23
3.4.4 Warranty Cost 23
3.4.5 Minimal Repair and Rework Cost 25
3.4.6 Shortage Cost 26
3.4.7 Total Cost 27
3.5 Model Optimization 28
3.6 Summary of Model Development 31
IV. Numerical Analysis 32
4.1 Numerical Example 32
4.2 Sensitivity Analysis 35
4.3 Design of Experiment ─ Taguchi Method 42
4.4 Summary of Numerical Analysis 46
V. Conclusion 47
5.1 Concluding Remark 47
5.2 Future Extension 48
References 49
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