This article describes the results of the anomalies automated detection algorithm development in the operation of industrial robots. The development of robotic systems, in particular, industrial robots, and software for them is ahead of the tracking and managing technologies development. The operation of the digital production system involves the generation of a large amount of various data characterizing the state of both the specific equipment and the industrial system as a whole. Such a system produces a sufficient amount of data to develop machine learning models to analyse this data to solve problems such as forecasting and modelling. As part of the study, an experiment was conducted based on the equipment of the laboratory of industrial robots of Tomsk Polytechnic University. In the course of the research, the industrial manipulator moved loads belonging to different classes by weight. An algorithm was developed for the automated analysis of the values of the parameters of the consumed current and the position of the manipulator.

No abstract

No abstract

The article is devoted to the problem of load agreement of solid-phase components into the fluorination and capture apparatus of two technological of uranium hexafluoride production lines. The article describes the process of developing a model of the horizontal part of the combined type apparatus which was included in the dynamic mathematical model of uranium hexafluoride production. The developed algorithm of load agreement was studied on dynamic mathematical model of uranium hexafluoride production.

No abstract