首页    期刊浏览 2024年09月15日 星期日
登录注册

文章基本信息

  • 标题:The quality management ecosystem for predictive maintenance in the Industry 4.0 era
  • 本地全文:下载
  • 作者:Sang M. Lee ; DonHee Lee ; Youn Sung Kim
  • 期刊名称:International Journal of Quality Innovation
  • 电子版ISSN:2363-7021
  • 出版年度:2019
  • 卷号:5
  • 期号:1
  • 页码:1-11
  • DOI:10.1186/s40887-019-0029-5
  • 出版社:Springer Verlag
  • 摘要: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.
  • 关键词:Predictive maintenance; Quality management; Big data analytics; Artificial intelligence (AI); Platform construction; Information and communication technology (ICT); Real-time
国家哲学社会科学文献中心版权所有