Prognostics and Health Management: A Review on Data Driven Approaches

Author:

Tsui Kwok L.1,Chen Nan2,Zhou Qiang1ORCID,Hai Yizhen1,Wang Wenbin34ORCID

Affiliation:

1. Department of System Engineering and Engineering Management, City University of Hong Kong, Hong Kong

2. Department of Industrial & Systems Engineering, National University of Singapore, Singapore 117576

3. Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China

4. Faculty of Business and Law, Manchester Metropolitan University, Manchester M15 6BH, UK

Abstract

Prognostics and health management (PHM) is a framework that offers comprehensive yet individualized solutions for managing system health. In recent years, PHM has emerged as an essential approach for achieving competitive advantages in the global market by improving reliability, maintainability, safety, and affordability. Concepts and components in PHM have been developed separately in many areas such as mechanical engineering, electrical engineering, and statistical science, under varied names. In this paper, we provide a concise review of mainstream methods in major aspects of the PHM framework, including the updated research from both statistical science and engineering, with a focus on data-driven approaches. Real world examples have been provided to illustrate the implementation of PHM in practice.

Funder

Hong Kong Research Grant Council General Research Fund

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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