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Prognostic modelling options for remaining useful life estimation by industry

Sikorska, Joanna, Hodkiewicz, Melinda, & Ma, Lin (2011) Prognostic modelling options for remaining useful life estimation by industry. Mechanical Systems and Signal Processing, 25(5), pp. 1803-1836.

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Abstract

Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success.

By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs.

This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

Impact and interest:

60 citations in Scopus
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36 citations in Web of Science®

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ID Code: 42332
Item Type: Journal Article
Keywords: Prognostics, Remaining Useful Life (RUL), Maintenance, Reliability
DOI: 10.1016/j.ymssp.2010.11.018
ISSN: 0888 3270
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > INTERDISCIPLINARY ENGINEERING (091500)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Deposited On: 04 Jul 2011 13:56
Last Modified: 01 Mar 2012 00:31

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