Stochastic Approach in Performance Modelling of a Repairable Industrial System

Abstract

This paper aims to present a quantitative investigation of a case study based on a live industrial refrigeration system exhibiting complex and dynamic behaviour such as randomness, concurrency, and time dependency. The study employs a state-space stochastic Markovian process to model the interactions among the key functional elements of the system. Furthermore, the scientific approach pursued in this study would help improve the availability of the considered plant by establishing a trade-off between investment, economy and quality. Based on the analysis of results, a framework for Decision Support Priorities (DSP) is proposed, emphasizing the criticality of various functional units. This framework could also help set and prioritize maintenance, spare parts, and human resource requirements accordingly.