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dc.contributor.author | Reyes, John | es_ES |
dc.contributor.author | Mula, Josefa | es_ES |
dc.contributor.author | Díaz-Madroñero Boluda, Francisco Manuel | es_ES |
dc.date.accessioned | 2024-10-03T18:25:06Z | |
dc.date.available | 2024-10-03T18:25:06Z | |
dc.date.issued | 2024-09-01 | es_ES |
dc.identifier.issn | 0020-7543 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/209248 | |
dc.description.abstract | [EN] Validated quantitative models for lean supply chain planning (LSCP) are still scarce in the literature, particularly because conventional push systems have not been widely integrated and tested with pull systems in sustainable and resilient environments in the Industry 4.0 context. Hence the main contribution of this paper is to develop an optimisation model that is able to contribute to the LSCP with the combination of push and pull strategies. Here we present an integrated just-in-time (JIT) production system with material requirement planning (MRP) for a SC that takes a traditional five level structure based on a mixed-integer linear programming model (MILP) dubbed as LSCP 4.0.The model is able to simultaneously plan the production and inventory of materials and finished goods to satisfy demand from forecasts and firm orders. The selection of alternative suppliers as a proactive measure to face disruptive events is also considered. Furthermore, sustainable practices are included in the objective function for profit maximisation by considering CO2 emissions. This proposal is tested in the footwear sector. The results demonstrate that the combined use of JIT and MRP through a quantitative approach improve performance in leanness, sustainability and resilience by decreasing the bullwhip effect at different SC levels. | es_ES |
dc.description.sponsorship | This work was supported by Generalitat Valenciana [grant numbers: PROMETEO/2021/065 and CIGE/2021/159]; Horizon2020 Framework Programme [grant number 958205]; the MCIN/AEI/10.13039/501100011033 and by European Union Next GenerationEU/PRTR [grant number PDC2022-133957-I00]; and Universidad Tecnica de Ambato. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Taylor & Francis | es_ES |
dc.relation.ispartof | International Journal of Production Research | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Lean manufacturing | es_ES |
dc.subject | Sustainability | es_ES |
dc.subject | Supply chain | es_ES |
dc.subject | Resilience | es_ES |
dc.subject | Mixed-integer linear programming | es_ES |
dc.subject | Industry 4.0 | es_ES |
dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
dc.title | Quantitative insights into the integrated push and pull production problem for lean supply chain planning 4.0 | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1080/00207543.2024.2312205 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2022-133957-I00/ES/VALIDACION DE RESULTADOS TRANSFERIBLES DE OPTIMIZACION DE TECNOLOGIAS DE PRODUCCION CERO-DEFECTOS HABILITADORAS PARA CADENAS DE SUMINISTRO 4.0/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/958205/EU/Industrial Data Services for Quality Control in Smart Manufacturing/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO%2F2021%2F065//Industrial Production and Logistics Optimization in Industry 4.0 (i4OPT)/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/CIUCSD//CIGE%2F2021%2F159/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi | es_ES |
dc.description.bibliographicCitation | Reyes, J.; Mula, J.; Díaz-Madroñero Boluda, FM. (2024). Quantitative insights into the integrated push and pull production problem for lean supply chain planning 4.0. International Journal of Production Research. 62(17):6251-6275. https://doi.org/10.1080/00207543.2024.2312205 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1080/00207543.2024.2312205 | es_ES |
dc.description.upvformatpinicio | 6251 | es_ES |
dc.description.upvformatpfin | 6275 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 62 | es_ES |
dc.description.issue | 17 | es_ES |
dc.relation.pasarela | S\508609 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | COMISION DE LAS COMUNIDADES EUROPEA | es_ES |
dc.contributor.funder | Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana | es_ES |
upv.costeAPC | 3170 | es_ES |