Prognostics and Health Management: A Review on Data Driven Approaches

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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.
Funding Information
  • Hong Kong Research Grant Council General Research Fund (11216014, 11471275, 71420107023, 71231001, 2013M530531, FRF-TP-13-026A, 20120006110025, FRF-MP-13-009A)