availability analysis of mechanical systems with condition-based maintenance using semi-markov and evaluation of optimal condition monitoring interval

Maintenance helps to extend equipment life by improving its condition and avoiding catastrophic failures. appropriate model or mechanism is, thus, needed to quantify system availability vis-a-vis a given maintenance strategy, which will assist in decision-making for optimal utilization of maintenance resources. this paper deals with semi-markov process (smp) modeling for steady state availability analysis of mechanical systems that follow condition-based maintenance (cbm) and evaluation of optimal condition monitoring interval. the developed smp model is solved using two-stage analytical approach for steady-state availability analysis of the system. also, cbm interval is decided for maximizing system availability using genetic algorithm approach. the main contribution of the paper is in the form of a predictive tool for system availability that will help in deciding the optimum cbm policy. the proposed methodology is demonstrated for a centrifugal pump.