Quantification of the value of condition monitoring system with time-varying monitoring performance in the context of risk-based inspection

Condition monitoring systems (CMSs) can be used to further reduce the expected value of life-cycle cost in the context of risk-based inspection (RBI) planning. However, the degradation of CMS monitoring performance and the utilization of historical data lead to the time-varying property of CMS monitoring performance, which would significantly affect the contributions of CMS. To facilitate risk analysis, a stochastic degradation model and Bayesian theorem are utilized to model the time-varying monitoring performance. Furthermore, a selection method of the CMS identification threshold is proposed to improve the CMS contributions to RBI planning further. To quantify the CMS contributions from a cost-effective perspective, this paper proposes an analytical framework on the value of CMS information analysis, which integrates condition-based maintenance action into RBI planning. In this framework, the importance of considering the time-varying performance of CMS can also be quantified by value of information (VoI) analysis. A case study of fatigue-induced degradation of a welded connection is used to clarify the proposed framework, in which the value of CMS information is quantified and the importance of considering time-varying monitoring performance is highlighted. Finally, the optimal implementation strategy regarding the CMS operation period is identified based on the VoI metric.