Overview of Remaining Useful Life Prediction Techniques in Through-life Engineering Services

TLDR

Through‑life Engineering Services use Remaining Useful Life predictions to improve support and reduce catastrophic failures in complex engineering products. This paper aims to identify failure mechanisms and highlight prediction approaches that can reduce uncertainties in RUL estimation. The authors classify RUL prediction techniques and map degradation mechanisms to these methods to guide designers and manufacturers in extending component life‑span.

Abstract

Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components.