Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/241975
Authors: 
Lee, Sang M.
Lee, Donhee
Kim, Youn Sung
Year of Publication: 
2019
Citation: 
[Journal:] International Journal of Quality Innovation [ISSN:] 2363-7021 [Volume:] 5 [Year:] 2019 [Issue:] 1 [Pages:] 1-11
Abstract: 
The Industry 4.0 era requires new quality management systems due to the ever increasing complexity of the global business environment and the advent of advanced digital technologies. This study presents new ideas for predictive quality management based on an extensive review of the literature on quality management and five real-world cases of predictive quality management based on new technologies. The results of the study indicate that advanced technology enabled predictive maintenance can be applied in various industries by leveraging big data analytics, smart sensors, artificial intelligence (AI), and platform construction. Such predictive quality management systems can become living ecosystems that can perform cause-effect analysis, big data monitoring and analytics, and effective decision-making in real time. This study proposes several practical implications for actual design and implementation of effective predictive quality management systems in the Industry 4.0 era. However, the living predictive quality management ecosystem should be the product of the organizational culture that nurtures collaborative efforts of all stakeholders, sharing of information, and co-creation of shared goals.
Subjects: 
Predictive maintenance
Quality management
Big data analytics
Artificial intelligence (AI)
Platform construction
Information and communication technology (ICT)
Real-time
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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