Integrated planning of acquisition, disassembly and bulk recycling: a case study on electronic scrap recovery

Spengler, Thomas; Ploog, Martin; Schröter, Marcus

doi:10.1007/978-3-662-05607-3_16

Cited by 21 publications

(14 citation statements)

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“…In the research domain related to recycling, most researchers assume the deterministic environment (AdensoDíaz et al 2007;Ferrão and Amaral 2006;Fröhling et al 2010;Guide 1997;Jayaraman 2006;Jayaraman et al 1999;Lambert 1999;Spengler et al 2003;Wongthatsanekorn 2009), and very few studies try to deal with the uncertainty (Cohen et al 1980;Naeem et al 2013;Reveliotis 2007;van der Laan and Salomon 1997;van der Laan et al 1996). Stochastic models, grouped into theoretical optimal control and dynamic programming categories, take into account the uncertainty and random parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Spengler et al (2003) studied the shredding and separation procedures for returned electronics. Sometimes, shredding is preceded by disassembly for environmental and economical considerations.…”

Section: Introductionmentioning

confidence: 99%

“…Though integrating the two channels seems to be a good idea, it is a complicated issue, and sometimes causes more problems than it's worth. Fleischmann et al (2000) categorize recycling networks into three types: bulk recycling network (Realff et al 2004;Spengler et al 1997;Wongthatsanekorn 2009), assembly product remanufacturing network (Ferrão and Amaral 2006;Golany et al 2001;Jayaraman et al 1999;Li et al 2006;Spengler et al 2003), and re-usable item network. In this study, the term "recycling supply chain" refers to all recycling activities that take place in reverse logistics.…”

Section: Introductionmentioning

confidence: 99%

“…While planning the disassembly sequence, product graphs (e.g., liaison graphs or relational graphs) are usually used to present product configurations (Lee et al 2001). "Shredding" completely destroys the product structure to obtain valuable materials, such as ferrous metals, aluminum, copper, and plastics (Spengler et al 2003).…”

Section: Introductionmentioning

confidence: 99%

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A heuristic master planning algorithm for recycling supply chain management

2015

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This study focuses on solving a multi-objective master planning (MP) problem for a recycling supply chain, including collectors, disassemblers, shredders, reconditioners and garbage handlers. An MP problem for a recycling supply chain is solved to determine the optimal transporting and processing operations, while considering multiple product structures, multiple discrete planning periods, and multiple demands, stocking and garbage handling quantities. To solve the MP problem, we propose a multiple-goal mixed integer programming model with two objectives: minimize the total delay cost and minimize the sum of processing cost, transportation cost, holding cost, setup cost and garbage handling cost. To improve the effectiveness and efficiency of the solution process, we propose a heuristic algorithm, RPMPA, which consists of three phases: preliminary works, demand grouping and sorting algorithm, and the Recycling Process Path Selection Algorithm. We built a prototype based on RPMPA, and constructed a scenario analysis to show the effectiveness and efficiency of RPMPA.Keywords Heuristic · Recycling supply chain · Bill of material · Master planning · Mixed integer programming

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A heuristic master planning algorithm for recycling supply chain management

2015

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“…Besides asset recovery and environmental regulations [6], [8], [25], an important driver for companies to engage in a reverse supply chain is that many used products, especially electronic ones [7], [9], [14], [19], [20], represent a resource for recoverable value. Though direct reuse of used products is infeasible in most cases, remanufacturing and recycling are the major recovery options applied in the reverse supply chain.…”

Section: Introductionmentioning

confidence: 99%

A Multiphase Fuzzy Logic Approach to Strategic Planning of a Reverse Supply Chain Network

Pochampally

Gupta

2008

IEEE Trans. Electron. Packag. Manufact.

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Abstract-Strategic planning (also called designing) is a challenging aspect of a reverse supply chain network. To effectively satisfy drivers such as profitability, environmental regulations, and asset recovery, only the most economical used products must be reprocessed in only the recovery facilities that have the potential to efficiently reprocess them. Due to uncertainties in supply, quality, and reprocessing times of used products, the cost-benefit function in the literature that selects the most economical product to reprocess from a set of used products is not appropriate for direct adoption. Moreover, due to the same uncertainties, any traditional forward supply chain approach to identify potential manufacturing facilities cannot be employed to identify potential recovery facilities. This paper proposes a three-phase fuzzy logic approach, taking the above uncertainties into account, to design a reverse supply chain network. Application of the approach is detailed through an illustrative example in each phase.Index Terms-Analytic hierarchy process (AHP), fuzzy, reverse supply chain, strategic planning.

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