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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 周雍強(Yon-Chun Chou) | |
dc.contributor.author | Kuo-Chiao Chang Chien | en |
dc.contributor.author | 張簡國喬 | zh_TW |
dc.date.accessioned | 2021-06-15T12:28:42Z | - |
dc.date.available | 2019-08-24 | |
dc.date.copyright | 2016-08-24 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-08-08 | |
dc.identifier.citation | [1] Cavalieri, S., Garetti, M., Macchi, M., & Pinto, R. (2008). A decision-making framework for managing maintenance spare parts. Production Planning & Control :The Management of Operations, 19(4), 379-396.
[2] Díaz, A., & Fu, M. C. (1997). Models for multi-echelon repairable item inventory systems with limited repair capacity. European Journal of Operational Research, 97(3), 480-492. [3] Dekker, R., Pinçe, Ç., Zuidwijk, R., & Jalil, M. N. (2013). On the use of installed base information for spare parts logistics: A review of ideas and industry practice. International Journal of Production Economics, 143(2), 536-545. [4] Flores, B. E., & Whybark, D. C. (1986). Multiple Criteria ABC Analysis. International Journal of Operations & Production Management, 6(3), 38-46. [5] Flores, B. E., & Whybark, D. C. (1987). Implementing Multiple Criteria ABC Analysis. Journal of Operations Management, 7. [6] Gelders, L. F., & Van Looy, P. M. (1978). An Inventory Policy for Slow and Fast Movers in a Petrochemical Plant: A Case Study. J Oper Res Soc, 29(9), 867-874. [7] Liu, Q., & Huang, D. (2006). Classifying ABC inventory with multicriteria using a data envelopment analysis approach. Paper presented at the Intelligent Systems Design and Applications, Six International Conference. [8] Macchi, M., Fumagalli, L., Pinto, R., & Cavalieri, S. (Eds.). (2011). A Decision Making Framework for Managing Maintenance Spare Parts in Case of Lumpy Demand: Action Research in the Avionic Sector. [9] Marmorstein, W. Z. H. (1990). Comparing two alternative methods of determining safety stock levels: The demand and forecast systems. Journal of Business Logistics, 11, 16. [10] Mukhopadhyay, S. K., Pathak, K., & Guddu, K. (2003). Development of decision support system for stock control at area level in mines. Insititution of Engineers (India) Journal - Mining, 84, 11-16. [11] Ng, W. L. (2007). A simple classifier for multiple criteria ABC analysis. European Journal of Operational Research, 177(1), 344-353. [12] Partovi, F. Y., & Burton, J. (1993). Using the Analytic Hierarchy Process for ABC Analysis. International Journal of Operations & Production Management, 13(9), 29-44. [13] Persona, A., Battini, D., Manzini, R., & Pareschi, A. (2007). Optimal safety stock levels of subassemblies and manufacturing components. International Journal of Production Economics, 110(1-2), 147-159. [14] Persona, A., Catena, M., Ferrari, E., & Manzini, R. (2003). Quantitative models for evaluating safety stocks in case of modular products. Paper presented at the 17th International Conference on Production Research (ICPR 17th), Blacksburg, Virginia, USA. [15] Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 33(3), 695-700. [16] Roda, I., Macchi, M., & Fumagalli, L. (2014). A review of multi-criteria classification of spare parts. Journal of Manufacturing Technology Management, 25(4), 528-549. [17] Saaty, T. (1988). What is the Analytic Hierarchy Process? In G. Mitra, H. Greenberg, F. Lootsma, M. Rijkaert, & H. Zimmermann (Eds.), Mathematical Models for Decision Support (Vol. 48, pp. 109-121): Springer Berlin Heidelberg. [18] Sarker, R., & Haque, A. (2000). Optimization of maintenance and spare provisioning policy using simulation. Applied Mathematical Modeling, 24, 751-760. [19] Syntetos, A. A., Keyes, M., & Babai, M. Z. (2009). Demand categorisation in a European spare parts logistics network. International Journal of Operations & Production Management, 29(3), 292-316. [20] Whybark, D. C. W., J.C. (1976). Material requirements planning under uncertainty. Decision Science, 7(4), 595-606. [21] 林俊劭. (2012). 不做代工的緯創 營益率翻六倍. 商業週刊, 1305. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50055 | - |
dc.description.abstract | 對於生產耐久財(durable goods)的企業來說,很重要的一塊業務便是提供購買商品的顧客售後維修的服務,因為良好的售後維修服務不僅可以為企業帶來豐厚的利潤,對於顧客知識的累積也有幫助,因此零組件的存貨管理在這其中便顯得格外重要。存貨管理都會遇到的一個問題就是該如何決定其安全存量(safety stock),過去研究安全存量設定的研究往往都是以單一存貨作為研究重點,考量缺貨成本與存貨成本加總最小下的最佳安全存量水準,不過實務上缺貨成本是難以估計且往往需要同時考慮所有的存貨,更不用說種類眾多的零組件。
因此身為售後服務(after-sales service)的提供者,如何在企業給定的經費下決定各零件的服務水準,以使得整體系統的服務水準可以達到最佳,便是一個棘手的問題。本研究根據此問題建構了一個數學模型來求解各零件最佳的服務水準,因為數學模型的使用不具效率且沒有帶來相關管理知識,所以透過汽車零件的數值範例以及KKT條件法的推導,試圖找出零件在不同的需求特性、存貨成本與重要性下服務水準設立的準則,並利用這個準則發展一種分類法來提供企業一個有效率設立服務水準的方式。 汽車案例的結果得知利潤率越高,需求波動越小的零組件應給予較高的服務水準以獲取利益,而KKT研究的結果也可以發現重要性相對於成本比值越大的零件,須給予越高的服務水準,以提升整體系統的服務品質。將以上的準則轉換成指標便可以對所有零組件進行排序,並以比例分配的方式分成ABC三類,給予高、中、低三種程度的服務水準。 | zh_TW |
dc.description.abstract | After-sales service is a core business to the corporations manufacturing durable goods, not only lots of profit could be gained but accumulating customers’ information by providing solid service to customers. One key factor in providing good service is an efficient service parts management, and one key decision in service parts management, like all kinds of inventory management, is deciding an appropriate safety stock level (service level) for each spare part. Previous studies on safety stock level usually focus on one single item, while taking inventory cost and shortage cost into consideration. They suggested the optimal level should achieve its minimum total cost. Unfortunately, it is impractical to deal with only one item, and most of time, the shortage cost is just too difficult to assess accurately.
To a provider of after-sales service, a desired problem is how to set all parts’ service level so that the average service level would reach its maximum. In order to solve the optimal service level for each part, this thesis constructs a mathematic model based on the problem, taking parts’ demand characteristics, inventory cost and criticality into account. By examining the numerical examples and deriving the KKT conditions, we are able to searching patterns of optimal service levels. Once we confirm the patterns, we could use it as some kind of criteria to classify all service parts into three categories: “High service level”, “Moderate service level” and “Low service level”, then by giving these categories respective service level, it is an effective way of setting service levels. As the result shows, the one with high criticality, low cost and demand variability should be classified into category “High service level” and set at high service level. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T12:28:42Z (GMT). No. of bitstreams: 1 ntu-105-R03546026-1.pdf: 1982490 bytes, checksum: 34234955dea1a9574d256f65dec7acbf (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 誌謝 i
摘要 ii Abstract iii 圖目錄 viii 表目錄 ix 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究問題分析 5 1.3 研究範疇、方法與目的 8 1.4 論文架構 10 第二章 文獻回顧 11 2.1 備品零組件的管理 11 2.2 零組件的分類 13 第三章 基礎模型建構與零組件分類 22 3.1 問題定義與假設 22 3.2 符號定義 24 3.3 模型建構 25 3.4 汽車代理商案例 31 3.5 數值範例一 33 3.6 數值範例二 40 3.7 綜合分類指標 55 3.8 零組件指標分類法 60 3.9 CI二維矩陣 61 3.10 小結 63 第四章 KKT條件之應用 64 4.1 拉格朗日乘數(Lagrange Multiplier) 64 4.2 KKT必要條件 66 4.3 敏感度分析 68 第五章 結論及未來研究方向 73 5.1 結論與貢獻 73 5.2 未來研究方向 74 參考文獻 76 附錄 79 | |
dc.language.iso | zh-TW | |
dc.title | 維修零組件的存貨分類法分析 | zh_TW |
dc.title | An analysis of inventory classification for service parts. | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 黃奎隆(Kwei-Long Huang),陳文智(Wen-Chih Chen) | |
dc.subject.keyword | 服務水準,零組件,售後服務,安全存量,存貨分類,KKT條件法, | zh_TW |
dc.subject.keyword | Service level,service parts,after-sales service,safety stock,inventory classification,KKT conditions, | en |
dc.relation.page | 84 | |
dc.identifier.doi | 10.6342/NTU201602068 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2016-08-08 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
顯示於系所單位: | 工業工程學研究所 |
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