Abstract
Planning maintenance activities on tractors can be improved and become more effective when using a mathematical apparatus for modelling the processes of the operation and maintenance of machines and tractors using homogeneous Markov chains. For this purpose, it is necessary to switch from the traditional methods for determining the indicators of their technical state to dynamic methods based on the theory of random processes. The most promising method is the use of homogeneous Markov chains. Based on the accumulated statistical data, it is possible to determine the probabilities of transition from one technical state to another. The values of the transition probabilities are used to construct a probability matrix describing a simple Markov chain. For tractors, taking into account the approaching of their limit state, which is characterized by the full depletion of resources, an absorbing Markov chain is best suited. The algorithms for the decomposition and study of the properties of reducible absorbing Markov chains, which allow obtaining useful information for an efficient operation, maintenance and repair of tractors and complex agricultural machinery, are presented.
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