Evaluation and Comparison of Mixed Effects Model Based Prognosis for Hard Failure

Abstract

Failure prognosis plays an important role in effective condition-based maintenance. In this paper, we evaluate and compare the hard failure prediction accuracy of three types of prognostic methods that are based on mixed effect models: the degradation-signal based prognostic model with deterministic threshold (DSPM), with random threshold (RDSPM), and the joint prognostic model (JPM). In this work, the failure prediction performance is measured by the mean squared prediction error, and the power of prediction. We have analyzed characteristics of the three methods, and provided insights to the comparison results through both analytical study and extensive simulation. In addition, a case study using real data has been conducted to illustrate the comparison results as well.