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Designing dynamic reverse logistics network for post-sale service

The paper addresses the problem of designing a multi-country production–distribution network that also provides services such as repairs and remanufacturing. The proposed work concentrates primarily on post-sale service provided by the firm under warranty returns. The proposed model assumes that exi...

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Detalles Bibliográficos
Autores principales: Mishra, Shraddha, Singh, Surya Prakash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340781/
https://www.ncbi.nlm.nih.gov/pubmed/32836618
http://dx.doi.org/10.1007/s10479-020-03710-9
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author Mishra, Shraddha
Singh, Surya Prakash
author_facet Mishra, Shraddha
Singh, Surya Prakash
author_sort Mishra, Shraddha
collection PubMed
description The paper addresses the problem of designing a multi-country production–distribution network that also provides services such as repairs and remanufacturing. The proposed work concentrates primarily on post-sale service provided by the firm under warranty returns. The proposed model assumes that existing warehouses can also serve as collection centres or repair centres for reverse logistics. In addition, the model also explores the possibility of establishing a new facility. Hybrid facilities are considered because of their huge cost-cutting potential due to equipment sharing and space sharing. The capacity of hybrid facilities can be expanded to a predefined limit to process returned products without hampering forward logistics operations. However, if a product cannot be repaired at the warehouse, it is transported to the plant for remanufacturing. The model optimizes the overall configuration and operation cost of the production–distribution network. The production–distribution model developed in the paper is a mixed-integer nonlinear program (MINLP) that is later transformed to a mixed-integer linear program to reduce the solution time. The usefulness of the model is illustrated using a randomly generated dataset. The model identifies (a) the optimal locations/allocations of the existing/new facilities, (b) the distribution of returned products for refurbishing and remanufacturing, and (c) the capacity expansion of the existing plants and warehouses to facilitate remanufacturing and repair services.
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spelling pubmed-73407812020-07-08 Designing dynamic reverse logistics network for post-sale service Mishra, Shraddha Singh, Surya Prakash Ann Oper Res S.i. : Mim2019 The paper addresses the problem of designing a multi-country production–distribution network that also provides services such as repairs and remanufacturing. The proposed work concentrates primarily on post-sale service provided by the firm under warranty returns. The proposed model assumes that existing warehouses can also serve as collection centres or repair centres for reverse logistics. In addition, the model also explores the possibility of establishing a new facility. Hybrid facilities are considered because of their huge cost-cutting potential due to equipment sharing and space sharing. The capacity of hybrid facilities can be expanded to a predefined limit to process returned products without hampering forward logistics operations. However, if a product cannot be repaired at the warehouse, it is transported to the plant for remanufacturing. The model optimizes the overall configuration and operation cost of the production–distribution network. The production–distribution model developed in the paper is a mixed-integer nonlinear program (MINLP) that is later transformed to a mixed-integer linear program to reduce the solution time. The usefulness of the model is illustrated using a randomly generated dataset. The model identifies (a) the optimal locations/allocations of the existing/new facilities, (b) the distribution of returned products for refurbishing and remanufacturing, and (c) the capacity expansion of the existing plants and warehouses to facilitate remanufacturing and repair services. Springer US 2020-07-08 2022 /pmc/articles/PMC7340781/ /pubmed/32836618 http://dx.doi.org/10.1007/s10479-020-03710-9 Text en © Springer Science+Business Media, LLC, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle S.i. : Mim2019
Mishra, Shraddha
Singh, Surya Prakash
Designing dynamic reverse logistics network for post-sale service
title Designing dynamic reverse logistics network for post-sale service
title_full Designing dynamic reverse logistics network for post-sale service
title_fullStr Designing dynamic reverse logistics network for post-sale service
title_full_unstemmed Designing dynamic reverse logistics network for post-sale service
title_short Designing dynamic reverse logistics network for post-sale service
title_sort designing dynamic reverse logistics network for post-sale service
topic S.i. : Mim2019
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340781/
https://www.ncbi.nlm.nih.gov/pubmed/32836618
http://dx.doi.org/10.1007/s10479-020-03710-9
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