Quality Management Bibliometric Analysis and Visualization

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dc.contributor.advisorBuri , Zsolt
dc.contributor.authorAljoab , Mohsen Saeed Mohammed
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-06-17T12:47:18Z
dc.date.available2025-06-17T12:47:18Z
dc.date.created2025
dc.description.abstractThis study examines the evolution of Quality Management Systems (QMS) into Quality 4.0, which integrates digital technologies like AI, IoT, and big data analytics. Using bibliometric analysis of research from 2020 to 2025, data from Scopus was analyzed with VOSviewer and CiteSpace to identify key trends and relationships. Results show a strong focus on technology integration within quality management, highlighted by clusters on AI in manufacturing, sustainable TQM, and digital supply chains. Despite the progress, gaps remain such as limited global diversity, few empirical case studies, and incomplete integration of digital tools into existing QMS. The research suggests updating standards like ISO 9001 to better align with digital transformation and emphasizes studying the impact of technology on workers. Overall, Quality 4.0 represents a major shift towards real-time, automated quality systems, combining human and AI collaboration. This analysis provides valuable insights into current trends and future research directions in quality management.
dc.description.courseEngineering Management
dc.description.degreeMSc/MA
dc.format.extent64
dc.identifier.urihttps://hdl.handle.net/2437/393065
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectQuality Management System (QMS)
dc.subjectIndustry 4.0
dc.subjectQuality 4.0
dc.subject.dspaceEngineering Sciences
dc.titleQuality Management Bibliometric Analysis and Visualization
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