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Probabilistic evaluation of the effect of maintenance parameters on reliability and cost

Preventive maintenance is performed to extend the equipment lifetime or at least the mean time between failures. Cost-effective maintenance scheduling is important due to budget constraints in the current situation where reduction of the operating and capital cost is the focus of the power industry. In order to establish a cost-effective maintenance, quantitative evaluation of maintenance parameters is critical. In this paper, a probabilistic model to achieve cost-effective maintenance strategies is presented. Reliability indices such as mean duration, state probability and visit frequency of each state, are computed using Monte Carlo simulation and demonstrated using a numerical example. Further, cost analysis is performed by computing all associated costs including inspection, maintenance and failure costs based on the reliability indices.