| Summary: | Background. Predicting the change in the reliability of an intelligent information-measuring system
is an urgent task in determining the thermophysical properties of heat-insulating, composite, building and other materials
at manufacturing enterprises. The failure of an intelligent measuring system consists in exceeding the measurement
error of the system components, which leads to inaccurate control of the thermophysical properties of materials
and a decrease in the quality of manufactured materials in production. Evaluation of system reliability based on the
created information and mathematical models of reliability prediction will make it possible to maintain the efficiency
of the structural components of the measuring system in a timely manner, improve the accuracy of measuring information
for calculating the parameters of the thermophysical properties of materials and, therefore, improve the quality
of products. Materials and methods. The prediction of the reliability of an intelligent information-measuring system is
based on the classical theory of reliability, mathematical modeling, probability theory and mathematical statistics,
methods of software and hardware self-control, and an algorithm for predicting the reliability of a measuring system.
Results. Information and mathematical models have been developed to predict the reliability of an intelligent information-
measuring system of thermophysical properties of materials, a knowledge base, which helps to increase the
probability of failure-free operation of this system. Conclusions. Forecasting the reliability of an intelligent information-
measuring system makes it possible to exclude a violation of the system's operability, improve the accuracy of
the measurement data obtained from the control object and ensure the reliability of the determined thermophysical
properties of materials to improve the quality of products manufactured at manufacturing enterprises.
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