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Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

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Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

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dc.contributor.author Mzougui, Ilyas es_ES
dc.contributor.author Carpitella, Silvia es_ES
dc.contributor.author Certa, Antonella es_ES
dc.contributor.author El Felsoufi, Zoubir es_ES
dc.contributor.author Izquierdo Sebastián, Joaquín es_ES
dc.date.accessioned 2021-03-01T08:08:06Z
dc.date.available 2021-03-01T08:08:06Z
dc.date.issued 2020-05 es_ES
dc.identifier.uri http://hdl.handle.net/10251/162559
dc.description.abstract [EN] Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCRs) is crucial, and is currently a very active field of research. Failure Mode, Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the Risk Priority Number (RPN) is proposed within the FMECA framework by means of an integrated Multi-Criteria Decision-Making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of "dependence" among the risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated with input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: When planning interventions of prevention/mitigation, primary importance should be given to (1) supply chain disruptions due to natural disasters; (2) manufacturing facilities, human resources, policies and breakdown processes; and (3) inefficient transport. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Processes es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Supply chain es_ES
dc.subject Criticality and risk analysis es_ES
dc.subject Systems engineering es_ES
dc.subject FMECA es_ES
dc.subject AHP es_ES
dc.subject Fuzzy DEMATEL es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/pr8050579 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation Mzougui, I.; Carpitella, S.; Certa, A.; El Felsoufi, Z.; Izquierdo Sebastián, J. (2020). Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA. Processes. 8(5):1-22. https://doi.org/10.3390/pr8050579 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/pr8050579 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 22 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 8 es_ES
dc.description.issue 5 es_ES
dc.identifier.eissn 2227-9717 es_ES
dc.relation.pasarela S\412333 es_ES
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dc.subject.ods 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación es_ES
dc.subject.ods 12.- Garantizar las pautas de consumo y de producción sostenibles es_ES


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