Revision and Implementation of Metrics to Evaluate the Performance of Prognostics Models

摘要: Prognostics is used in predictive maintenance to estimate the remaining time to the end of the life of a system or component. Among the many challenges of prognostics is the need for model verification and validation. Over the years, several objective metrics have been utilized by the community. Some of these metrics came from statistics, others from forecasting, and others have been proposed specifically for prognostics. A single``perfect''metric has not yet been put forward. Finding one metric that can excel in all evaluation dimensions and case studies is an open question. In this review, we analyze the most important metrics of prognostics. The metrics are implemented on a public GitHub project. The paper describes each metric properties, advantages, disadvantages, and industrial applicability. Our goal is to raise the level of interest in prognostics metrics and to help establish a common evaluation procedure.