Abstract
Intelligent Information Support for Decision Making in Maintenance and Equipment Repair Management is discussed in this article. The authors propose a solution approach that includes Bayes method, knowledge engineering technologies and fuzzy logic to formalization of revealed and expert knowledge (production rules system) for diagnostics, (fuzzy production system) for classify equipment and components, forecasting and optimization methods for planning the components procurement. Practical realization is performed using analytical MATLAB platform and EXSYS Corvid and software developed in USATU. The proposed approach by authors of this article can be implemented as the local application for information system, or as part of the creation of the digital twin of the production system. The results of experimental studies have shown a significant gain in time in decision-making in the diagnostic task, as well as in the level of timely replacement of components by 12 percent due to the introduction of demand coefficients in planning purchases.
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