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Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model

This paper presents the data set, variables and criteria for the development of a multi-objective and multi-period Mixed Integer Linear Programming (MILP) model for the deployment and design of an aerospace CFRP (Carbon Fibre Reinforced Polymer) waste supply chain. It involves ε-constraint, lexicogr...

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Detalles Bibliográficos
Autores principales: Dong, Anh Vo, Azzaro-Pantel, Catherine, Boix, Marianne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909135/
https://www.ncbi.nlm.nih.gov/pubmed/31871965
http://dx.doi.org/10.1016/j.dib.2019.104766
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author Dong, Anh Vo
Azzaro-Pantel, Catherine
Boix, Marianne
author_facet Dong, Anh Vo
Azzaro-Pantel, Catherine
Boix, Marianne
author_sort Dong, Anh Vo
collection PubMed
description This paper presents the data set, variables and criteria for the development of a multi-objective and multi-period Mixed Integer Linear Programming (MILP) model for the deployment and design of an aerospace CFRP (Carbon Fibre Reinforced Polymer) waste supply chain. It involves ε-constraint, lexicographic techniques and Multiple Criteria Decision Making (MCDM) tools. In this model, the deployment of new recycling sites (Grinding, Pyrolysis, Supercritical Water, Microwave) is established. The system is optimised by bi-criteria optimisation including an economic objective based on cost minimisation or Net Present Value (NPV) maximisation and an environmental one (minimisation of Global Warming Potential). The presentation of the global strategy, the results and their discussion have been presented in a companion paper (Vo Dong, P.A., Azzaro-Pantel, C., Boix, A multi-period optimisation approach for deployment and optimal design of an aerospace CFRP waste management supply chain, Waste Management, Volume 95, 2019, Pages 201–216 [1]). The data were acquired by literature analysis, by use of Simapro v7.3 software tool and EcoInvent database, by use of institutional sources (Eurostat for energy prices) or from Airbus and Boeing websites for aircraft deliveries and calculation of CFRP content. The model was created by the authors within the framework of SEARRCH (Sustainability Engineering Assessment Research for Recycling Composite with High value) project supported by ANR (Agence Nationale de la Recherche Scientifique). The case study of CFRP waste supply chain in France has supported the deployment analysis.
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spelling pubmed-69091352019-12-23 Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model Dong, Anh Vo Azzaro-Pantel, Catherine Boix, Marianne Data Brief Engineering This paper presents the data set, variables and criteria for the development of a multi-objective and multi-period Mixed Integer Linear Programming (MILP) model for the deployment and design of an aerospace CFRP (Carbon Fibre Reinforced Polymer) waste supply chain. It involves ε-constraint, lexicographic techniques and Multiple Criteria Decision Making (MCDM) tools. In this model, the deployment of new recycling sites (Grinding, Pyrolysis, Supercritical Water, Microwave) is established. The system is optimised by bi-criteria optimisation including an economic objective based on cost minimisation or Net Present Value (NPV) maximisation and an environmental one (minimisation of Global Warming Potential). The presentation of the global strategy, the results and their discussion have been presented in a companion paper (Vo Dong, P.A., Azzaro-Pantel, C., Boix, A multi-period optimisation approach for deployment and optimal design of an aerospace CFRP waste management supply chain, Waste Management, Volume 95, 2019, Pages 201–216 [1]). The data were acquired by literature analysis, by use of Simapro v7.3 software tool and EcoInvent database, by use of institutional sources (Eurostat for energy prices) or from Airbus and Boeing websites for aircraft deliveries and calculation of CFRP content. The model was created by the authors within the framework of SEARRCH (Sustainability Engineering Assessment Research for Recycling Composite with High value) project supported by ANR (Agence Nationale de la Recherche Scientifique). The case study of CFRP waste supply chain in France has supported the deployment analysis. Elsevier 2019-11-09 /pmc/articles/PMC6909135/ /pubmed/31871965 http://dx.doi.org/10.1016/j.dib.2019.104766 Text en © 2019 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Engineering
Dong, Anh Vo
Azzaro-Pantel, Catherine
Boix, Marianne
Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model
title Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model
title_full Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model
title_fullStr Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model
title_full_unstemmed Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model
title_short Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model
title_sort multi-period optimal design of an aerospace cfrp waste management supply chain: data set, variables and criteria for the development of a multi-objective milp model
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909135/
https://www.ncbi.nlm.nih.gov/pubmed/31871965
http://dx.doi.org/10.1016/j.dib.2019.104766
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