This article describes in more detail the issue of using predictive models of NAR neural networks to predict the course of certain quantities, which may indicate a problem with the industrial machines or their major failures. It is very important to find sufficient size of the structure and values of parameters that directly affect the output accuracy of the model. This article presents the way in which it is possible to automatically find the settings of these NAR models so that the required final accuracy metric is achieved. This presented algorithm was tested on simulation data samples collected by using the M5StickC microcontroller device. This collected dataset presented in this article contains accelerometer and gyroscopic data only, but there is a possibility to expand and add some other sensors to this microcontroller, to collect some other relevant data. This M5-StickC microcontroller device can be used for gathering data in the first phase of the machine state analysis without interfering with the mechanical construction and electrical connections of the machine. Testing of proposed algorithm was carried out in MATLAB environment. The article also describes the way in which these predictive NAR neural network models can be implemented directly in control systems, specifically PLCs from the manufacturer SIEMENS without the use of 3rd party analytical platforms. This application can be helpful in the area of predictive maintenance tasks, especially in avoiding critical failures of industrial machines and devices, or some of their specific parts.

Development of the territories with specific climatic conditions requires the selection of effective materials. Multilayer composite materials are suitable for these purposes in road construction in the Arctic. The article presents a design scheme for a multilayer road surface, which is used to determine the collection of traffic loads. The method of solving the inverse Cauchy problem and the empirical formula to determine the value of the temperature arising from deformation at the contact point of the surface of a multilayer road surface and transport are determined. The experimental studies conducted were aimed to determine the heat transfer through a three-layer road surface made of structural foam concrete of the D1200 brand. The processing of experimental data on temperature values made it possible to derive the formula to determine the change in the layers' temperature depending on their number.