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Bi-objective optimization for low-carbon product family design

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Bi-objective optimization for low-carbon product family design

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dc.contributor.author Wang, Qi es_ES
dc.contributor.author Dunbing, Tang es_ES
dc.contributor.author Yin, Leilei es_ES
dc.contributor.author Salido, Miguel A. es_ES
dc.contributor.author Giret Boggino, Adriana Susana es_ES
dc.contributor.author Xu, Yuchun es_ES
dc.date.accessioned 2018-03-23T13:08:40Z
dc.date.available 2018-03-23T13:08:40Z
dc.date.issued 2016 es_ES
dc.identifier.issn 0736-5845 es_ES
dc.identifier.uri http://hdl.handle.net/10251/99650
dc.description.abstract [EN] Consumers, industry, and government entities are becoming increasingly concerned about the issue of global warming. With this in mind, manufacturers have begun to develop products with consideration of low-carbon. In recent years, many companies are utilizing product families to satisfy various customer needs with lower costs. However, little research has been conducted on the development of a product family that considers environmental factors. In this paper, a low-carbon product family design that integrates environmental concerns is proposed. To this end, a new method of platform planning is investigated with considerations of cost and greenhouse gas (GHG) emission of a product family simultaneously. In this research, a lowcarbon product family design problem is described at first, and then a GHG emission model of product family is established. Furthermore, to support lowcarbon product family design, an optimization method is applied to make a significant trade-off between cost and GHG emission to implement a feasible platform planning. Finally, the effectiveness of the proposed method is illustrated through a case study. (C) 2016 Elsevier Ltd. All rights reserved. es_ES
dc.description.sponsorship This research was carried out as a part of the CASES project which is supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme under the Grant agreement no. 294931. This research was also supported by National Natural Science Foundation of China (Nos. 51175262, 51575264); and Jiangsu Province Science Foundation for Excellent Youths under Grant BK2012032.
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Robotics and Computer-Integrated Manufacturing es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Multiple objective programming es_ES
dc.subject Low carbon design es_ES
dc.subject Platform planning es_ES
dc.subject Product family design es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Bi-objective optimization for low-carbon product family design es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.rcim.2016.02.001 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/294931/EU/Customised Advisory Services for Energy-efficient Manufacturing Systems/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//51175262/
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//51575264/
dc.relation.projectID info:eu-repo/grantAgreement/Jiangsu Province Science Foundation for Excellent Youths//BK2012032/
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2018-10-31 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Wang, Q.; Dunbing, T.; Yin, L.; Salido, MA.; Giret Boggino, AS.; Xu, Y. (2016). Bi-objective optimization for low-carbon product family design. Robotics and Computer-Integrated Manufacturing. 41:53-65. https://doi.org/10.1016/j.rcim.2016.02.001 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1016/j.rcim.2016.02.001 es_ES
dc.description.upvformatpinicio 53 es_ES
dc.description.upvformatpfin 65 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 41 es_ES
dc.relation.pasarela S\309645 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder National Natural Science Foundation of China
dc.contributor.funder Jiangsu Province Science Foundation for Excellent Youths, China


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