Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors

Modelling the time that the system remains in a given state using classical distributions is not always possible. In many cases, empirical distributions are multimodal due to the influence of external, hidden factors and the selection of the best classical distributions may lead to erroneous results. In the article the method of diagnosis of influence of hidden factors into sojourn time of semi-Markov models was presented. In order to capture hidden factors, the authors proposed to model the distributions of the sojourn time with a mixture of distributions, which is a significant novelty in relation to the studies presented in the literature. Hidden factors directly affect the reliability of technical systems. Detecting the existence of these factors enables more accurate modeling of system readiness. Paying attention to irregularities caused by hidden factors makes it possible to reduce system maintenance costs. Such a system model provides complete information and enables a reliable assessment of the system readiness and maintenance.

Automated summary

This article introduces a method for diagnosing the influence of hidden factors on the sojourn time of semi-Markov models. By modeling the sojourn time with a mixture of distributions, the authors are able to accurately assess and maintain the readiness of the system.