New methodology for improving the inspection policies for degradation model selection according to prognostic measures
IEEE Transactions on Reliability
Health monitoring data are vital for failure prognostic and maintenance planning. The continuous monitoring data or frequent inspections can provide a large amount of information on degradation evolution and therefore ensure the quality of deterioration modeling and the lifetime prognostic accuracy. However, they are usually very costly and sometimes impracticable in real engineering applications. Therefore, it is essential to address the issue of the appropriate amount of monitoring data. This paper proposes a new methodology to help the companies improving their actual inspection/monitoring policy to reduce the operation and maintenance costs but also ensure the information quality. We investigate different types of inspection policies including the periodic or nonperiodic ones by considering multiples functions of the system degradation state that are linear, concave, or convex.