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Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making

Circular manufacturing systems (CMS) constitute complex value networks comprising a large and diverse set of stakeholders that collaborate to close the loop of products through multiple lifecycles. Complex systems modelling and simulation play a crucial role in providing quantitative and qualitative...

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Autores principales: Roci, Malvina, Salehi, Niloufar, Amir, Saman, Asif, Farazee.M.A., Shoaib-ul-Hasan, Sayyed, Rashid, Amir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066358/
https://www.ncbi.nlm.nih.gov/pubmed/35518913
http://dx.doi.org/10.1016/j.mex.2022.101709
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author Roci, Malvina
Salehi, Niloufar
Amir, Saman
Asif, Farazee.M.A.
Shoaib-ul-Hasan, Sayyed
Rashid, Amir
author_facet Roci, Malvina
Salehi, Niloufar
Amir, Saman
Asif, Farazee.M.A.
Shoaib-ul-Hasan, Sayyed
Rashid, Amir
author_sort Roci, Malvina
collection PubMed
description Circular manufacturing systems (CMS) constitute complex value networks comprising a large and diverse set of stakeholders that collaborate to close the loop of products through multiple lifecycles. Complex systems modelling and simulation play a crucial role in providing quantitative and qualitative insights into the behaviour of such systems. In particular, multi-method simulation modelling that combines agent-based, discrete-event, and system dynamics simulation methods is considered more suitable to model and simulate CMS as it allows to capture their complex and dynamic nature. This paper provides a step-by-step approach on how to build a CMS multi-method simulation model in order to assess their economic, environmental, and technical performance for enhanced decision-making. To model and simulate CMS three main elements need to be considered: • A multi-method model architecture where the CMS stakeholders with heterogeneous characteristics are modelled individually as autonomous agents using agent-based, discrete-event, and system dynamics. • An agent environment defined by a Geographic Information System (GIS) to establish connections based on agents’ geographic location. • The product journey resulting from the product's interaction with various CMS stakeholders in the circular value network is traced throughout its multiple lifecycles.
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spelling pubmed-90663582022-05-04 Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making Roci, Malvina Salehi, Niloufar Amir, Saman Asif, Farazee.M.A. Shoaib-ul-Hasan, Sayyed Rashid, Amir MethodsX Method Article Circular manufacturing systems (CMS) constitute complex value networks comprising a large and diverse set of stakeholders that collaborate to close the loop of products through multiple lifecycles. Complex systems modelling and simulation play a crucial role in providing quantitative and qualitative insights into the behaviour of such systems. In particular, multi-method simulation modelling that combines agent-based, discrete-event, and system dynamics simulation methods is considered more suitable to model and simulate CMS as it allows to capture their complex and dynamic nature. This paper provides a step-by-step approach on how to build a CMS multi-method simulation model in order to assess their economic, environmental, and technical performance for enhanced decision-making. To model and simulate CMS three main elements need to be considered: • A multi-method model architecture where the CMS stakeholders with heterogeneous characteristics are modelled individually as autonomous agents using agent-based, discrete-event, and system dynamics. • An agent environment defined by a Geographic Information System (GIS) to establish connections based on agents’ geographic location. • The product journey resulting from the product's interaction with various CMS stakeholders in the circular value network is traced throughout its multiple lifecycles. Elsevier 2022-04-22 /pmc/articles/PMC9066358/ /pubmed/35518913 http://dx.doi.org/10.1016/j.mex.2022.101709 Text en © 2022 The Author(s). Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Roci, Malvina
Salehi, Niloufar
Amir, Saman
Asif, Farazee.M.A.
Shoaib-ul-Hasan, Sayyed
Rashid, Amir
Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
title Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
title_full Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
title_fullStr Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
title_full_unstemmed Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
title_short Multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
title_sort multi-method simulation modelling of circular manufacturing systems for enhanced decision-making
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066358/
https://www.ncbi.nlm.nih.gov/pubmed/35518913
http://dx.doi.org/10.1016/j.mex.2022.101709
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