The paper presents results of the analysis of the developed models for complex technical objects preventive maintenance scheduling. Models based on two different sets of assumptions were developed. The general problem solved was to determine the joint time of preventive renewal for a group of parts or subassemblies. The purpose of the first model (the model of scheduled preventive maintenance strategy) is to determine the profitability of constant application of a previously developed preventive maintenance schedule for a part undergoing post-failure renewal. The second model (the model of adaptive strategy of a system’s preventive maintenance) allows one to determine a new joint time of preventive renewal for a group of parts each time when one of them is undergoing a post-failure renewal. The initial preventive maintenance strategy for each part or subassembly was obtained using typical tools for maintenance planning (decision-random models based on dynamic programming and Bellman’s principle of optimality). Exemplary simulation calculations with the use of both models were made and their results presented as the total maintenance costs estimated for the renewal strategies developed. The object of the analysis were the chosen geometrical features of a rail vehicle wheel changing due to its wear during operation. Based on this kind of analysis, one can choose a better preventive maintenance model for a specific application area.
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Młynarski et al. (2019) studied this question.
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