Performance analysis for a degrading system with Markov model

Most mechanical engineering systems experience deterioration due to several practical factors such as aging, usage etc. This results in the degradation of its performance. Although the deterioration is continuous in nature, it is not always practically possible to measure the deterioration especially in the case of subsea systems. In such cases the performance of these systems is represented by multiple finite states in their lifetimes where various levels of degradation are represented by these states. Generally, the degradation process is divided into two stages, i.e., the normal and defective stages. Thus, there are three possible states for the system: normal, defective, and failed. The Markov approach has been utilized heavily for reliability analysis of such systems. However, most of the Markov models rely on an accurately exponentially distributed transition rate, which is unrealistic in certain cases. In reality, there are some uncertainties in the transition rates thanks to the limits of prior knowledge. This paper presents a multi-phase Markov model-based performance evaluation model for a three-state system with uncertainties in transition rates. The transition rates are assumed following Beta distribution with known lower and upper bounds. The average system unavailability in a given life cycle is employed to quantify system performance. © 2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.