Mostrar el registro sencillo del ítem
dc.contributor.author | Serrano-Ruiz, Julio C. | es_ES |
dc.contributor.author | Mula, Josefa | es_ES |
dc.contributor.author | Poler, R. | es_ES |
dc.date.accessioned | 2022-07-14T18:04:18Z | |
dc.date.available | 2022-07-14T18:04:18Z | |
dc.date.issued | 2021-12 | es_ES |
dc.identifier.issn | 2073-431X | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/184216 | |
dc.description.abstract | [EN] Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to survive in the long term. On the one hand, the antidisruptive potential and the inherent sustainability implications of the zero-defect manufacturing (ZDM) management model should be highlighted. On the other hand, the digitization and virtualization of processes by Industry 4.0 (I4.0) digital technologies, namely digital twin (DT) technology, enable new simulation and optimization methods, especially in combination with machine learning (ML) procedures. This paper reviews the state of the art and proposes a ZDM strategy-based conceptual framework that models, optimizes and simulates the master production schedule (MPS) problem to maximize service levels in SCs. This conceptual framework will serve as a starting point for developing new MPS optimization models and algorithms in supply chain 4.0 (SC4.0) environments. | es_ES |
dc.description.sponsorship | The research leading to these results received funding from the European Union H2020 Program with grant agreements No. 825631 "Zero-Defect Manufacturing Platform (ZDMP)" and No. 958205 "Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)", and from Grant RTI2018-101344-B-I00 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe". | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Computers | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Supply chain 4.0 | es_ES |
dc.subject | Master production schedule | es_ES |
dc.subject | Zero-defect manufacturing | es_ES |
dc.subject | Digital twin | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
dc.title | Smart Master Production Schedule for the Supply Chain: A Conceptual Framework | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/computers10120156 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-101344-B-I00/ES/OPTIMIZACION DE TECNOLOGIAS DE PRODUCCION CERO-DEFECTOS HABILITADORAS PARA CADENAS DE SUMINISTRO 4.0/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/825631/EU | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/958205/EU | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses | es_ES |
dc.description.bibliographicCitation | Serrano-Ruiz, JC.; Mula, J.; Poler, R. (2021). Smart Master Production Schedule for the Supply Chain: A Conceptual Framework. Computers. 10(12):1-24. https://doi.org/10.3390/computers10120156 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/computers10120156 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 24 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 10 | es_ES |
dc.description.issue | 12 | es_ES |
dc.relation.pasarela | S\453249 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | COMISION DE LAS COMUNIDADES EUROPEA | es_ES |
dc.subject.ods | 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación | es_ES |