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Integrated approach for manufacturing-remanufacturing systems and closed-loop supply chain optimization

Integrated approach for manufacturing-remanufacturing systems and closed-loop supply chain optimization
制造-再制造系统和闭环供应链优化的集成方法
批准号:
121863-2009
负责人:
Chen, MingYuan
金额:
$2.04万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2009
资助国家:
加拿大
项目状态:
已结题
起止时间:
2009-01-01 至 2010-12-31

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中文摘要
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英文摘要
The proposed research will follow an integrated system approach to study closed-loop supply chain management (CLSCM) and related issues. A forward supply chain (FSC) is concerned with material and components supply for new products, new product production, product distribution, transportation and delivery to customers. A reverse supply chain (RSC) is concerned with collection of used and reusable materials, transportation, sorting and inspection and remanufacturing to make them "as good as new" products. Extensive research has been done addressing different problems related to FSC and RSC. In recent years, many remanufacturing related problems have also been studied. However, research on CLSCM has been mainly focused on problems related to logistics and transportation. The proposed research will address problems related to CLSCM using an integrated approach for optimal coordination of manufacturing and remanufacturing activities as they may share machines, equipment, labor and other production resources. Current research on such problems is limited and the studied problems are often too simplified to be practical. We plan to follow an integrated approach to develop optimization math models and solution methodology for solving production planning, job scheduling, quality control and improvement and other problems in hybrid manufacturing and remanufacturing systems. Other CLSCM issues including the use of advanced materials such as composite materials, logistics, costs, customer demands and environmental benefits will be incorporated into the extended optimization models. Well-established and advanced modeling tools, optimization methods and computing technology will be utilized to develop effective and efficient solution methods for solving practical CLSCM problems.
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