標題: 考量碳排放量、成本與前置時間於再製造系統之批量決策
Lot Sizing for Recoverable Remanufacturing Decisions with Cost, Lead Time and Carbon Dioxide Emissions
作者: 蘇泰盛
吳靖純
黃立雯
Tai-Sheng Su
Chin-Chun Wu
Li-Wen Huang
關鍵字: 再製造系統;模糊理論;可能性規劃法;前置時間;二氧化碳排放量;Remanufacturing Systems;Fuzzy Theory;Possibilistic Linear Programming;Lead-Time;CO_2 Emissions
公開日期: 1-Oct-2018
出版社: 國立交通大學
National Chiao Tung University
摘要: 本研究考量新料與回收料混合之再製造系統,並建構一個可能性線性規劃模式,提供於可回收再製造系統之模糊環境進行生產決策。模式中考量多零組件、多供應商、多回收商、多料源及多機台等因素。系統中的相關參數是具模糊性,模糊參數可用梯形與三角形可能性分配來表示。本研究應用模糊理論與可能性線性規劃來表示目標函數、需求量及二氧化碳排放量的不確定性。我們也提出一個決策模式於可回收再製造系統,模式中考量新料與回收料的混合、物料供應商的採購、二氧化碳的排放量及機台良率等限制,達到最小總成本、前置時間及二氧化碳排放量的目標。此外,我們提出一個模糊目標函數和目標限制式的求解程序,為驗證模式的正確性,我們以一個實務案例之數值進行測試,研究結果和建議是適合於生產計畫使用。
This work uses new and recoverable materials to mix into the remanufacturing systems. It implements a possibilistic linear programming model to provide aid in making production decisions in recyclable remanufacturing systems subject to a fuzzy environment which includes multi-component, multi-vendor, multi-source and multi-machine factors. When the related parameters are imprecise in the systems, both the trapezoidal and triangular possibility distributions are used. This work applies fuzzy theory and possibility linear programming to set the objective function, demand and CO_2 emission uncertainty. We propose a decision making model to consider the procurement of raw materials, new materials and recycled materials mixed into the remanufacturing systems with reference to the restrictions of supplier/vendor capacity, CO_2 emissions and machine yield in order to minimize total cost, lead-time and CO_2 emissions. In addition, we propose a procedure for solving the fuzzy objective functions and fuzzy constraints. To test the adequacy of model, we use a numerical example from a real case study. The results and suggestions can provide a feasible situation for production planning.
URI: http://hdl.handle.net/11536/152524
ISSN: 1023-9863
期刊: 管理與系統
Journal of Management and System
Volume: 25
Issue: 4
起始頁: 457
結束頁: 491
Appears in Collections:Journal of Management and System


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