Development of a diagnostic module for industrial robot control systems.

Modern production is largely based on the implementation of automated systems and industrial robots, which ensure high efficiency, precision, and speed in performing tasks. With the increased complexity and multifunctionality of such systems, there arises a need for the development of reliable diagnostic methods that allow for the prompt identification and elimination of faults, as well as maintaining a high degree of equipment operability. In this context, the creation of a diagnostic module for the industrial robot control system becomes especially relevant.

The objective of this course work is to develop a module that will perform diagnostics of the industrial robot control system, identifying potential faults and providing the user with comprehensive information for their resolution. To achieve this goal, it is necessary to solve a number of tasks: analyze existing approaches to diagnostics, develop algorithms for diagnosing various components of the control system, as well as implement a prototype of the module and test it under real operating conditions.

Relevance.

Modern industrial robots play a key role in ensuring the efficiency of production processes. As their application and the complexity of control systems increase, there is a growing need for the development of tools that can promptly identify and eliminate faults. Effective diagnostics not only prevent long downtimes but also reduce maintenance costs, thus increasing productivity and the economic return on investments in robotics. In a rapidly changing technological environment, the relevance of creating diagnostic modules becomes particularly evident: enterprises seek to enhance the reliability and safety of their automated systems.

The main problem of this research is the insufficient effectiveness of existing methods for diagnosing industrial robot control systems, as well as the lack of integrated solutions that allow for the rapid identification of faults. This leads to significant economic losses and reduced productivity due to equipment downtime. The research is aimed at creating a more universal and reliable diagnostic module that meets the modern requirements of the industry.

The subject of the research is the industrial robot control system, which includes both hardware and software components responsible for performing tasks of adjustment, control, and monitoring of the robot's operation.