Analysis and prioritization of quality 4.0 dimensions and companies' readiness to adapt to industry 4.0 evolutions through Bayesian Best - Worst method

dc.contributor.authorJamkhaneh, Hadi Baloueipor
dc.contributor.authorJalali, Rezapor
dc.contributor.authorShahin, Rezapor
dc.contributor.authorLima, Rui M.por
dc.contributor.authorRasouli, Ehsanpor
dc.contributor.authorJamali, Gholamrezapor
dc.date.accessioned2023-02-27T09:44:19Z
dc.date.available2023-02-27T09:44:19Z
dc.date.issued2022-01
dc.date.updated2023-02-24T19:04:30Z
dc.description.abstractIntroduction: The evolutions of the Fourth Industrial Revolution helped many companies and organizations to survive, achieving economic success and ensuring competitiveness, and has put them under pressure to align their goals, policies, strategies, and the nature of their operations with these changes. Therefore, the concept of quality and the nature of its operations to meet customers' needs in the digital era must be changed and updated in accordance with these developments. Quality 4.0 facilitates coordination between quality management and industry 4.0. A review of the literature shows that the concepts and perspectives of quality 4.0 have not yet evolved and matured, and therefore there is little research on the alignment of quality 4.0 management with industry 4.0 technologies. Purpose: The main purpose of this study is to identify and evaluate quality 4.0 indicators to draw a roadmap for organizations to align quality 4.0 management with industry 4.0 technologies. Methodology: To achieve the goal, first the literature of quality 4.0, quality 4.0 management as well as industry 4.0 technologies were studied to gain a broad understanding of the subject. Then the dimensions and quality 4.0 indicators that are potentially affected by the implementation of Industry 4.0 are identified. Next, the importance and prioritization of dimensions and quality 4.0 indicators for alignment with Industry 4.0 using the Bayesian Best-Worst method are determined. Findings: The research findings identify the dimensions and quality 4.0 indicators in different classes and then prioritize each of the indicators according to their importance in aligning quality 4.0 management with industry 4.0 technologies. Conclusion: The results of this study help to facilitate the process of change management towards quality 4.0 in companies and outline a roadmap for companies to prioritize the nature of their operations regarding the changes and developments and the need for revision and provides investment in quality 4.0 management.por
dc.description.sponsorship- (undefined)por
dc.distributioninternationalpor
dc.identifier.isbn9789895491117por
dc.identifier.urihttps://hdl.handle.net/1822/82909
dc.language.isoengpor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://publicacoes.riqual.org/icqem-22-compressed/por
dc.rightsopenAccesspor
dc.subjectBayesian Best-Worst Methodpor
dc.subjectChange managementpor
dc.subjectQuality 4.0por
dc.subjectQuality 4.0 managementpor
dc.subjectQuality 4.0 Organizational Dimensionspor
dc.titleAnalysis and prioritization of quality 4.0 dimensions and companies' readiness to adapt to industry 4.0 evolutions through Bayesian Best - Worst methodpor
dc.typeconferencePaperpor
dspace.entity.typePublicationen
oaire.citationEndPage17por
oaire.citationStartPage1por
sdum.bookTitle5th International Conference on Quality Engineering and Management: proceedings bookpor
sdum.conferencePublicationInternational Conference on Quality Engineering and Managementpor
sdum.export.identifier12568

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