Bayesian degradation assessment of CNC machine tools considering unit non-homogeneity

Abstract

Field reliability assessment and prediction is critical for the estimation, operation and health management of CNC machine tools. The classical methods for field reliability of CNC Machine Tools assessment and prediction are challenged with the issues of expensive reliability tests, small sample size and unit non-homogeneity. In order to solve these problems, this paper introduces a degradation analysis based reliability assessment method for CNC machine tools under performance testing. Since the degradation is an independent increment process, the gamma process is employed to characterize the degradation process of CNC machine tools. The random effects are introduced to accommodate performance degradation model with unit non-homogeneity. The parameters of model are updated by Bayesian estimation approach. As a case study, the CNC Machine Tools is studied to illustrate the approach. And the proposed method is demonstrated precise for practical use.