Abstract
Preventive replacement is applied to improve the device availability or increase the profit per unit time of the maintenance system. In this paper, we study age-replacement model of technical object for n-state system model. The criteria function applied in this paper describe profit per unit time or coefficient of availability. The probability distribution of a unit‘s failure time is assumed to be known, and preventive replacement strategy will be used over very long period of time. We investigate the problem of maximization of profit per unit time and coefficient availability for increasing the failure rate function of the lifetime and for a wider class of lifetime. The purpose of this paper is to obtain conditions under which the profit per unit time approaches a maximum. In this paper we shows that the criteria function (profit per unit time or coefficient availability) can be expressed using the matrix calculation method. Finally, a numerical example to evaluate an optimal replacement age is presented.
Highlights
Industrial system management requires implementation of various operational activities
This paper examines operation systems in which the technical object may at a given moment appear in one of the n states
For such systems optimal preventive replacements basing on the criteria function expressing the profit per time unit or availability coefficient
Summary
Industrial system management requires implementation of various operational activities. This paper examines operation systems in which the technical object may at a given moment appear in one of the n states. For such systems optimal preventive replacements basing on the criteria function expressing the profit per time unit or availability coefficient. Values of criteria function depend on the lifetime distribution, the mean value of preventive replacement time, mean repair time value, mean values of remaining at other states, profits per time unit, transition probability matrixes embedded in the semi-Markov process of Markov chain. Data for this example were obtained from an existing municipal bus operation process
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