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面向家电产品的逆向物流关键技术研究

Research on Key Technologies of Reverse Logistics for Household Appliances

【作者】 宋守许

【导师】 刘光复;

【作者基本信息】 合肥工业大学 , 机械制造及其自动化, 2007, 博士

【摘要】 随着循环经济的兴起、环境法规的压力、经济利益的驱动以及生产者责任的延伸,逆向物流得到了迅速的发展。逆向物流是循环经济发展的重要手段,是闭环供应链的重要组成部分。本文在分析国内外逆向物流主要研究内容、方法及现状的基础上,针对废旧家电产品的回收特点,深入研究了逆向物流的体系结构,重点对废旧家电产品逆向物流的网络规划、库存管理和再制造生产系统进行研究。论文的主要研究工作体现在以下几方面:(1)对逆向物流的概念、产生及发展进行了系统分析,深入探讨了逆向物流的内涵,并对逆向物流的研究内容和现状进行了分析和总结,建立了逆向物流系统体系结构。通过对逆向物流系统的研究对象、组成角色、功能和特点进行研究,建立了基于物流、工作流、信息流和资金流的逆向物流总体框架模型和废旧家电产品逆向物流系统过程模型、信息模型,提出了逆向物流系统的若干关键技术。(2)建立了废旧家电产品逆向物流网络规划模型。分析了逆向物流网络设计的影响因素和逆向物流网络选址基本理论,构建了废旧家电产品再制造集成物流网络和独立逆向物流网络,利用混合整数线性规划法对两种网络分别建立数学模型,并利用遗传算法对模型进行求解。(3)研究了逆向物流的库存管理,构建了允许缺货与退货的销售库存模型,对其最佳订货周期和最佳订货批量进行了深入研究;同时建立了返回和需求相互独立的再制造随机库存模型,研究了其最低成本控制策略。(4)在分析再制造系统各种成本的基础上,提出逆向物流再制造生产系统成本结构。对于生产两种产品且具有不同优先级的再制造生产系统,根据两种产品返回速度和处理速度的不同以及库存容量有限的情况,建立了一个面向再制造系统的随机生产成本模型。(5)对所建立的模型进行了数值分析和验证。以江苏、安徽、浙江和上海三省一市的废旧电冰箱回收为例,规划了冰箱回收网络;系统分析了各参数对库存模型和随机生产成本模型成本的影响,为废旧家电的库存管理和再制造生产提供了有益指导。

【Abstract】 Reverse logistics has been developed quickly due to the arising of recycling economy, pressure of environmental rules, drive of economic interest and extension of producer responsibility. The system structure of reverse logistics on waste household appliances is researched deeply based on the survey of contents, methods and present situation of both Chinese and international research works. This dissertation focuses on the network planning, inventory management and remanufacturing production system, and the detailed works are as follows:(1) The contents and connotations of reverse logistics is deeply discussed, and both Chinese and international research achievements are analyzed and summarized. Through the research on the objectives, roles, functions and features of reverse logistics, the framework integrating the material flow, work flow, information flow and capital flow is established. Concretely, the process model and information model of reverse logistics on waste household appliances is presented. Based on the framework, key technologies of reverse logistics are presented.(2) Network planning model of reverse logistics on waste household appliances is built. Factors having impact on network design of reverse logistics are analyzed. The method of network place selection is presented. And the remanufacturing integrated logistics network for waste household appliances and independent reverse logistics network are established respectively. Mixed integer linear programming (MILP) is adopted to analyze these two networks, and optimization algorithm based on genetic algorithm (GA) is given.(3) Marketing model of reverse logistics and remanufacturing inventory management model are established. Based on the Vendor Inventory Management (VIM) with concurrence of return and stock out, the optimum order cycle (OOC) and optimum order quantity (OOQ) are researched within the cost optimization. And remanufacturing inventory management model and least cost control strategy are presented when product return and demand are both random and mutually independent.(4) Cost model of stochastic remanufacturing production system of reverse logistics is built. With the analysis of all kinds of costs in remanufacturing system, cost structure of remanufacturing production system of reverse logistics is given. With different return rates and disposal rates of two products and the limitation of inventory capacity, a stochastic production cost model is established for the remanufacturing production system with different priorities to produce two kinds of products.(5) These models are numerically analyzed and validated. With a case study of waste refrigerator recycling in Jiangsu Province, Anhui Province, Zhejiang Province and Shanghai, recycle network of refrigerator is built. The impact of return rate, lead time, hold cost and stock out cost on the costs of the two inventory model is analyzed. Additionally, the impact of return rate, production mass, production rate, and inventory space on the cost of remanufacturing produce system is discussed.

  • 【分类号】F426.61;F252
  • 【被引频次】23
  • 【下载频次】2580
  • 攻读期成果
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