Analysis and Application of Energy Management in Industry 4.0 with TRIZ Methodology

Yuan Chih Yang, Ming Tien Tsai

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

The advent of Industry 4.0 takes our understanding of technology to a whole new level. The pursuit of profitability is gradually being replaced by business strategies that focus on comprehensive and sustainable operations. As a consequence, the looming energy crisis has become the center of attention, making smart energy management solutions an indispensable cornerstone of industry transformation. For intelligent factories, in addition to upgrading manufacturing equipment, businesses can improve upon traditional models of energy management by collecting and analyzing big data generated by the equipment. Smart energy management, in sum, is a system that effectively coordinates, monitors, integrates, manages, and predicts the operation of multiple sets of equipment, creating a customized energy management platform for every business based on data analytics. The present study is a case study on the facility management system adopted by semiconductor manufacturers. The author discusses the developmental trends in smart energy management within the context of Industry 4.0 based on “failure modes and effects analysis (FMEA)” and the “theory of inventive problem solving (TRIZ).” Building on the results, the author summarizes the potential technologies that meet practical needs and the development of intelligent electrical components that address potential failure modes. Finally, through the application of Internet of Things (IoT) and big data collection and transmission, businesses can conduct predictive maintenance on their in-service equipment to prevent system downtime, realizing the true benefits of intelligent management. The author hopes that the findings of this study can offer useful insights for relevant industries seeking to transform their businesses intelligently.

原文English
頁(從 - 到)30-45
頁數16
期刊International Journal of Systematic Innovation
6
發行號3
DOIs
出版狀態Published - 2021

All Science Journal Classification (ASJC) codes

  • 策略與管理
  • 組織行為與人力資源管理
  • 資訊系統與管理
  • 技術與創新管理
  • 人工智慧

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