Features of modeling failures of recoverable complex technical objects with a hierarchical constructive structure
DOI:
https://doi.org/10.15587/1729-4061.2017.108395Keywords:
complex technical object, hierarchical constructive structure, mean time between failures, unit operating costs, statistical simulation modelingAbstract
We developed a methodology and algorithms of forming the optimal sets of elements, which take part in the failure-recovery modeling process of complex technical objects. The methodology is based on the hierarchical constructive structure of the object, takes into account the redundancy of failing elements, as well as the maintainability of the product elements and their cost, which distinguishes this methodology from the known ones. Structurally, the methodology is implemented as a set of three algorithms. The generated optimal sets of elements are used to calculate the predictive reliability characteristics and operating costs of the object. The constructive structure of the object in the model is represented by a graph (tree). The optimality of the sets is understood in the sense of their correspondence to the object maintainability parameters.
With the improvement of maintainability properties, the forecasted values of the mean time between failures and the recovery time are correspondingly improved. Improvement of the operating cost index is not mandatory; provided different input data, there may not be such an improvement. Each variant of the values of object maintainability parameters is conformed to its optimal sets of failing and recoverable elements, under which adequate predictive estimates of reliability indicators and the object operating cost are provided.
The paper provides some examples of modeling, which demonstrate how the optimal sets of failing and recoverable elements are determined, and how the predictive estimates of reliability and object operating cost depend on the choice of these setsReferences
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Copyright (c) 2017 Sergey Lenkov, Genadiy Zhyrov, Dmytro Zaitsev, Evgen Lenkov, Igor Tolok, Tetiana Bondarenko, Viktor Zagrebnyuk, Yurii Gunchenko, Oleksandr Antonenko
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