Abstract
Complex technical objects in modern society are extremely important. Such objects belong to the class of recoverable objects of long-term repeated use. They tend to be expensive and costly to operate. To ensure the required level of reliability during their operation, maintenance is usually carried out, the essence of which is the timely preventive replacement of elements that are in a pre-failure state. A characteristic feature of complex technical objects for special purposes is the presence in their composition of a large number (tens, hundreds of thousands) of different types of component parts that have different levels of reliability, different patterns of their wear and tear processes. This feature requires a more subtle approach to the organization and planning of maintenance during their operation. The problem is that during the development of such facilities, all issues related to maintainability and maintenance should be addressed already at the early stages of facility design. If you do not provide in advance the necessary hardware and software for the built-in monitoring of technical condition (TC) of the object, do not develop and “build” the maintenance technology into the object, then it will not be possible to realize in the future a possible gain in the reliability of object due to maintenance. Since all these issues must be resolved at the stage of object creation (when the object does not yet exist), mathematical models of the maintenance process are needed, with the help of which it would be possible to calculate the possible gain in the level of reliability of facility due to maintenance, to estimate the cost costs required for this. Then, based on such calculations, make a decision on the need for maintenance for this type of objects and, if such a decision is made, develop structure of the maintenance system, choose the most acceptable maintenance strategy, and determine its optimal parameters. In this paper, we study the influence of the coefficient variation on value of the optimal level of maintenance. The work also confirms the general idea that the smaller value of the coefficient variation of random operating time to failure of the serviced elements, greater optimal value of maintenance level should be.
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