4.6 Article

IoT-Based Prognostics and Systems Health Management for Industrial Applications

期刊

IEEE ACCESS
卷 4, 期 -, 页码 3659-3670

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2016.2587754

关键词

Internet of things; maintenance; prognostics and systems health management; reliability; remaining useful life

资金

  1. Basic Science Research Program within the Ministry of Science, ICT and Future Planning through the National Research Foundation of Korea [NRF-2014R1A1A1003653]
  2. Ulsan National Institute of Science and Technology [1.160046.01]
  3. Australian ARC Industrial Transformation Research Hub for Offshore Floating Facilities [IH140100012]
  4. BHP Billiton
  5. Natural Science Foundation of Jiangsu Province [BK20150249]
  6. Changzhou Science and Technology Program [CJ20159053]
  7. Japan Society for the Promotion of Science [15K12459]
  8. CALCE Consortium

向作者/读者索取更多资源

Prognostics and systems health management (PHM) is an enabling discipline that uses sensors to assess the health of systems, diagnoses anomalous behavior, and predicts the remaining useful performance over the life of the asset. The advent of the Internet of Things (IoT) enables PHM to be applied to all types of assets across all sectors, thereby creating a paradigm shift that is opening up significant new business opportunities. This paper introduces the concepts of PHM and discusses the opportunities provided by the IoT. Developments are illustrated with examples of innovations from manufacturing, consumer products, and infrastructure. From this review, a number of challenges that result from the rapid adoption of IoT-based PHM are identified. These include appropriate analytics, security, IoT platforms, sensor energy harvesting, IoT business models, and licensing approaches.

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