IoT-Based Prognostics and Systems Health Management for Industrial Applications

Citation data:

IEEE Access, ISSN: 2169-3536, Vol: 4, Page: 3659-3670

Publication Year:
2016
Usage 10
Abstract Views 9
Link-outs 1
Captures 140
Readers 140
Citations 15
Citation Indexes 15
Repository URL:
https://research-repository.uwa.edu.au/en/publications/63013f6f-26ba-42c2-8aa0-c7684aec26f7; http://scholarworks.unist.ac.kr/handle/201301/20409
DOI:
10.1109/access.2016.2587754
Author(s):
Kwon, Daeil; Hodkiewicz, Melinda; Fan, Jiajie; Shibutani, Tadahiro; Pecht, Michael G.
Publisher(s):
Institute of Electrical and Electronics Engineers (IEEE); IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Tags:
Computer Science; Materials Science; Engineering; Internet of things; maintenance; prognostics and systems health management; reliability; remaining useful life
article description
© 2013 IEEE.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.