生產／再製造存貨模型中之最佳回收努力值策略

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：8

、訪客IP：3.143.17.128

姓名

陳逸洋(Yi-Yang Chen) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

生產／再製造存貨模型中之最佳回收努力值策略
(An Optimal Recycling Sales Effort Strategy in a Production/Remanufacturing Inventory Model)

相關論文

★ 應用灰色理論於有機農產品之經營管理— 需求預測及關鍵成功因素探討	★ NAND型Flash價格與交運量預測在風險分析下之決策模式
★ 工業電腦用無鉛晶片組最適存貨政策之研究-以A公司為例	★ 砷化鎵代工廠磊晶之最適存貨管理-以W公司為例
★ 資訊分享&決策制定下產銷協同關係之研究 -以IC設計業為例	★ 應用分析層級法於電子化學品業委外供應商評選準則之研究
★ 應用資料探勘於汽車售服零件庫存滯銷因素分析-以C公司為例	★ 多目標規劃最佳六標準差水準: 以薄膜電晶體液晶顯示器C公司製造流程為例
★ 以資料探勘技術進行消費者返廠定期保養之實證研究	★ 以價值鏈觀點探討品牌公司關鍵組織流程之取決-以S公司為例
★ 應用產銷協同規劃之流程改善於化纖產業-現況改善與效益分析	★ 權力模式與合作關係對於報價策略之影響研究—以半導體產業A公司為例
★ 應用資料探勘於汽車製造業之庫存原因分析	★ 以類神經網路預測代工費報價---以中小面板產業C公司為例
★ 電路板產業存貨改善研究-以N公司為例	★ 運用六標準差改善機台備用零件(Spare parts)存貨管理

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

二十一世紀，隨著環保意識抬頭，製造業為了減少汙染並負起企業責任，逐漸重視再製造技術。另一方面，再製造充分利用淘汰之舊物，開源節流以降低生產成本，是製造業者應具備的關鍵技術。故如何宣導以增加消費者使用後的回收率，並投資相關設備提升再製造技術以增加回收後的使用率，已成製造業相當重要的研究議題。
　　本研究依據Dobos and Richter（2003）所提出的生產／再製造物質流模型作為研究背景，將再製造流程分為生產、成品存貨、市場、回收存貨、再製造、廢棄六部分。假設決策者必需付諸一努力值以提升市場回收率，亦需付諸一努力值以提升回收後之使用率，故這兩個努力值會分別對應出一回收率函數與一使用率函數。
　　另外，就製造商角度而言，由於付諸之努力值本身亦為一種成本，但付諸不同的努力值組合後會對應到不同的總成本，某些策略組合在付諸努力值後之總成本會低於未付諸努力值之總成本，故本研究探討在經濟訂購量型式之逆物流模型中，何種努力值策略下會對應到最低之總成本，當參數給定後，可透過Java求解或Matlab立體成本繪圖，成功找到需要付諸努力值的情境。

摘要(英)

With the rise of environmental awareness in the twenty-first century, manufacturing order to reduce pollution and assume corporate responsibility, remanufacturing has aroused much attention of the company. On the other hand, remanufacturing make the best use of the returned items, open up the source and regulate the flow to reduce manufacturing cost, which is the critical technology that manufacturer should have. So how to encourage the consumer to enhance the return rate and invest related equipment to enhance the use rate has become a very important research topic for the manufacturing business.
　　This research mainly takes Dobos and Richter (2003) “the material flow in the model in a production and recycling cycle” as background, which separated the process of remanufacturing into six parts: production, serviceable stock, market, non-serviceable stock, recycling and disposal. Assume that the decision maker should give a sales effort to improve the return rate and also give a sales effort to improve the use rate, as a result, these two sales effort will correspond to the return rate function and the use rate function respectively.
　　Furthermore, in the view of manufacturing, sales effort are also kinds of cost. But different combinations of sales effort will correspond to different total cost. Some of the sales effort strategies will get a lower total cost after giving the sales effort. Therefore, this research also discuss what kind of sales effort strategies will correspond to the lowest total cost under a deterministic EOQ-type reverse logistic model. When the parameters are determined, we can successfully find out the situation which needs sales effort by Java or Matlab 3D graphics.

關鍵字(中)

★ 逆物流
★ 再製造
★ 努力值

關鍵字(英)

★ Reverse Logistics
★ Remanufacturing
★ Sales effort

論文目次

中文摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 vii
第一章緒論 1
1-1 研究動機 1
1-2 研究背景 2
1-3 研究目的 3
1-4 研究架構 3
第二章　文獻回顧 5
2-1 生產／再製造物質流模型 5
2-2 再製造 8
2-3 逆物流 9
2-4 努力值 10
第三章　模型建立 11
3-1 情境描述 11
3-2 模型假設 16
3-2-1 基本假設 16
3-2-2 符號說明 16
3-3 模型建構 18
3-3-1 成本計算-先不考慮努力值 18
3-3-2 成本計算-考慮努力值 20
第四章　模型分析 28
4-1 努力值分析演算法 28
4-2 各項成本變動關係 31
4-2-1 區分參數情境 31
4-2-2 各項成本變動關係 33
4-3 符合情境一之參數設定 35
4-4 決策變數與參數間的關係 38
4-4-1有限制決策變數 38
4-4-2 無限制決策變數 40
4-5 敏感度分析 43
第五章　結論與未來研究方向 49
5-1 結論 49
5-2 研究貢獻 50
5-3 未來研究方向 50
參考文獻 51
附錄一：方程式推導 54
附錄二：模型具有最佳解之證明 56
附錄三：決策變數與參數關係驗證─有限制決策變數 57
附錄四：決策變數與參數關係驗證─無限制決策變數 61
附錄五：目標式與參數關係驗證 68

參考文獻

[1] Agrawal, S., Singh, R. K., & Murtaza, Q., “A literature review and perspectives in reverse logistics.” Resources, Conservation and Recycling, 97, pp.76-92, 2015.
[2] Atasu, A., Sarvary, M., & Wassenhove, L. N. V., “Remanufacturing as a marketing strategy.” Management Science, 54(10), pp.1731-1746, 2008.
[3] Dobos, I. & Richter, K., “A production/recycling model with stationary demand and return rates.” Central European Journal of Operations Research, 11(1), pp.35-46, 2003.
[4] Dobos, I. & Richter, K., “An extended production/recycling model with stationary demand and return rates.” International Journal of Production Economics, 90(3), pp.311-323, 2004.
[5] Dobos, I. & Richter, K., “A production/recycling model with quality consideration.” International Journal of Production Economics, 104(2), pp.571-579, 2006.
[6] Fleischmann, M., Ruwaard, M. B., Dekker, R., Laan, E. v. d., Nunen, J. A.E.E. v., & Wassenhove , L. N. V., “Quantitative models for reverse logistics：A review.” European Journal of Operational Research, 103(1), pp.1-17, 1997.
[7] Govindan, K., Soleimani, H., & Kannan, D., “Reverse logistics and closed-loop supply chain：A comprehensive review to explore the future.” European Journal of Operational Research, 240(3), pp.603-626, 2015.
[8] Kafuku, J. M., Saman, M. Z. M., Yusof, S. M., Sharif, S., & Zakuan, N., “Investment decision issues from remanufacturing system perspective: Literature review and further research.” Procedia CIRP, 26, pp.589-594, 2015.
[9] Krishnan, H., Kapuscinski R., & Butz, D. A., “Quick response and retailer effort.” Management Science, 56(6), pp.962-977, June 2010.
[10] Maity, A.K., Maity, K., & Maiti, M., “A production-recycling-inventory system with imprecise holding costs.” Applied Mathematical Modelling, 32(11), pp.2241-2253, 2008.
[11] Mondal, M., Maity, A. K., Maiti, M. K., & Maiti, M., “A production-repairing inventory model with fuzzy rough coefficients under inflation and time value of money.” Applied Mathematical Modelling, 37(5), pp.3200-3215, 2013.
[12] Mondal, M., Maiti, M. K., & Maiti, M., “A production-recycling model with variable demand, demand-dependent fuzzy return rate：A fuzzy differential equation approach.” Computer & Industrial Engineering, 64(1), pp.318-332, 2013.
[13] Östlin, J., Sundin, E., & Björkman, M., “Importance of closed-loop supply chain relationships for product remanufacturing.” International Journal of Production Economics, 115(2), pp.336-348, 2008.
[14] Rajagopal, P., Sundram, V. P. K., & Naidu, B. M., “Future directions of reverse logistics in gaining competitive advantages：a review of literature.” International Journal of Supply Chain Management, 4(1), pp.39-48, 2015.
[15] Roy, A., Maity, K., kar, S., & Maiti, M., “A production-inventory model for defective and usable items in fuzzy-environment.” Computers & Industrial Engineering, 56(1), pp.87-96, 2009.
[16] Saadany, A. M.A. E., & Jaber, M. Y., “A production/remanufacturing inventory model with price and quality dependant return rate.” Computers & Industrial Engineering, 58(3), pp.352-362, 2010.
[17] Savaskan, R. C., & Wassenhove, L. N. V., “Reverse channel design：The case of competing retailers.” Management Science, 52(1), pp.1-14, January 2006.
[18] Souza, G. C., “Closed-loop supply chains：A critical review, and future research.” Decision Science, 44(1), pp.7-38, February 2013.
[19] Taylar, T. A., “Supply Chain Coordination Under Channel Rebates with Sales Effort Effects.” Institute for Operations Research and the Management Sciences, 48(8), pp.992-1007, 2002.
[20] Teunter, R. H., & Flapper, S. D. P., “Optimal core acquisition and remanufacturing policies under uncertain core quality fractions.” European Journal of Operational Research, 210, pp.241-248, 2011.

指導教授

陳振明(Jen-Ming Chen)

審核日期

2016-6-30

推文