Failure modes based censored data analysis for repairable systems and its industrial perspective

Abstract

Reliability analysis of repairable systems (RS) has always been a challenging task for the industries especially when the collected data is censored. In real-world situation, the industries, generally preserve all the system’s related information such as the number of failures, time between failures and their respective failure modes (FMs) for future reliability analysis. The problem arises when FM wise analysis is required to be done for RS along with other censoring criteria such as test termination, removing the operating system from the study etc. The literature provides various models to deal with different types of censored data but lacks in providing FM based censored data analysis technique for RS, when both preventive and corrective maintenances (PM and CM) are treated as imperfect. To bridge this gap, the paper develops a technique and virtual age models for RS which can simultaneously address FM wise analysis with right and multiply censoring data considering both the PM and CM as imperfect. The paper also develops likelihood function using proposed models for parameter estimation. The proposed technique and models are demonstrated with the help of a case study selected from aviation industry. The paper then highlights the applicability of proposed models to industries dealing with complex and critical RS in conducting failure modes and effects analysis (FMEA) and remaining useful life (RUL) estimation. The paper also brings out as to how the proposed models can be converted to the existing models with some modifications.