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

Yuan Chih Yang, Ming Tien Tsai

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)30-45
Number of pages16
JournalInternational Journal of Systematic Innovation
Volume6
Issue number3
DOIs
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Organizational Behavior and Human Resource Management
  • Information Systems and Management
  • Management of Technology and Innovation
  • Artificial Intelligence

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