Result of Digitalization in the Automotive Industry: Total Equipment Effectiveness and Bayesian Analysis

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dc.authorscopusid56007981300en_US
dc.authorscopusid58193037900en_US
dc.contributor.authorArgun, Irem Duzdar
dc.contributor.authorKilic, Sedef Akyol
dc.date.accessioned2024-08-23T16:04:16Z
dc.date.available2024-08-23T16:04:16Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractBusinesses today try to accommodate the fast-developing world through prioritizing high productivity, low cost, customer satisfaction, and most time-saving with the help of digitalization. The automotive industry as one of the greatest in global markets also finds its place in digitalization studies. The company analyzed in this article is producing automotive parts and investing in machines and software to enable digitalization. The aim of the firm is to raise the facilities' productivity in the digitalization process. The overall equipment efficiency study carried out in practice was carried out in order to observe the productivity change in the unit where the application was made with are proposed the digitalization transformation in the company. This article considers the total equipment effectiveness and Kaizen is applied for the interruptions with negative impacts on productivity. The productivity of the company is significantly increased after the Kaizen application. In order to digitalize the manufacturing processes successfully, more expert opinions are required. The Bayesian network (BN) is used to achieve higher increase at productivity. It has a powerful probability theory eliminating the inconsistent probability. During the implementation phase, the most important part of this article is the employment of components of the total equipment effectiveness as the variable for BN. The utilizing the expert opinions resulted to advance productivity. At the end of the Kaizen study, the productivity is raised from 83% to 85%. According to the results of the studied BN, the required suggestions to the company.en_US
dc.identifier.doi10.1109/TEM.2023.3254435
dc.identifier.issn0018-9391
dc.identifier.issn1558-0040
dc.identifier.scopus2-s2.0-85153331171en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1109/TEM.2023.3254435
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14138
dc.identifier.wosWOS:000972155100001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Engineering Managementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectManufacturingen_US
dc.subjectProductionen_US
dc.subjectFourth Industrial Revolutionen_US
dc.subjectProductivityen_US
dc.subjectContinuous improvementen_US
dc.subjectCompaniesen_US
dc.subjectUncertaintyen_US
dc.subjectAutomotive industryen_US
dc.subjectBayesian networken_US
dc.subjectdigitalizationen_US
dc.subjectkaizenen_US
dc.subjecttotal equipment effectivenessen_US
dc.subjectImprovementen_US
dc.subjectNetworken_US
dc.subjectOeeen_US
dc.titleResult of Digitalization in the Automotive Industry: Total Equipment Effectiveness and Bayesian Analysisen_US
dc.typeArticleen_US

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