Methodology combining industry 4.0 technologies and KPI’s reliability for supply chain performance
dc.rights.license | open | en_US |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | EL KIHEL, Yousra | |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | ZOUGGAR AMRANI, Anne | |
hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
dc.contributor.author | DUCQ, Yves
ORCID: 0000-0001-5144-5876 IDREF: 119003791 | |
dc.contributor.author | AMEGOUZ, Driss | |
dc.contributor.author | LFAKIR, Ahmed | |
dc.date.accessioned | 2023-10-03T07:18:22Z | |
dc.date.available | 2023-10-03T07:18:22Z | |
dc.date.issued | 2023-01-13 | |
dc.identifier.issn | 0951-192X | en_US |
dc.identifier.uri | oai:crossref.org:10.1080/0951192x.2022.2162605 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/183859 | |
dc.description.abstract | In the context of internationalization, the supply chain is becoming complex with a profusion of decisions to take. The modeling and measurement of supply chain (SC) performance has been widely addressed by researchers, however the arrival of new technologies in the era of industry 4.0 is changing the environment and implicitly impacting the Key Performance Indicators (KPI) for SC management. Although several models exist, none of them is specifically oriented for SC operations management considering the importance of KPI and inclusion of technologies of industry 4.0 concomitantly.This paper presents a research methodology targeting a reference model to grasp SC state with decisions identification called GRAILOG from which a set of KPI is built to support the different decisions. A methodology called PPTechIP is then described and demonstrated to lead and advise the company on the industry 4.0 transformation relevant to build reliable KPI. PPTechIP is based on a set of radars split into different decision levels and functions of the SC based on GRAILOG model. Potential of Progress is calculated and assist the manger in their decision making. PSA (French Car Manufacturer) embracing the era of industry4.0 was chosen to implement the model. The results, using the suggested methodology, provide several interesting insights in the control indicators of PSA. Big Data, Augmented reality and collaborative robots grasp great attentions from PSA and are judged as prior to continue the follow up and Cloud computing is judged as being an alert, carefulness to over investment has to be considered. | |
dc.language.iso | EN | en_US |
dc.source | crossref | |
dc.subject | Supply chain management | |
dc.subject | Key Performance Indicators | |
dc.subject | Industry 4.0 | |
dc.subject | Technologies | |
dc.subject | Automotive industry | |
dc.title | Methodology combining industry 4.0 technologies and KPI’s reliability for supply chain performance | |
dc.type | Article de revue | en_US |
dc.identifier.doi | 10.1080/0951192x.2022.2162605 | en_US |
dc.subject.hal | Sciences de l'ingénieur [physics] | en_US |
bordeaux.journal | International Journal of Computer Integrated Manufacturing | en_US |
bordeaux.page | 1128-1152 | en_US |
bordeaux.volume | 36 | en_US |
bordeaux.issue | 8 | en_US |
bordeaux.institution | Université de Bordeaux | en_US |
bordeaux.institution | Bordeaux INP | en_US |
bordeaux.institution | CNRS | en_US |
bordeaux.team | PRODUCTIQUE-MEI | |
bordeaux.peerReviewed | oui | en_US |
bordeaux.inpress | non | en_US |
bordeaux.import.source | dissemin | |
hal.popular | non | en_US |
hal.audience | Internationale | en_US |
hal.export | false | |
workflow.import.source | dissemin | |
dc.rights.cc | Pas de Licence CC | en_US |
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