Condition Monitoring of Pick-and-Place Robots Using IIoT-Based Data Acquisition Systems

Abstract

Modern industry challenges companies to ensure high reliability of machinery and equipment and continuity of production processes. An important role in this is played by condition monitoring of machines, during which the operating parameters of the equipment are analyzed, assessing its condition and the degree of wear of components. As part of the ongoing research, an IIoT (Industrial Internet of Things) - based solution was developed to monitor the condition of the joints of a FANUC M-1iA/1H industrial robot. The project involved the integration of sensors on the axes of the robot performing the pick and place process. A set of condition monitoring tools - CMTK - and sensors enabling diagnostics were used to collect and visualize data. The monitoring system is based on the analysis of such parameters as the speed of vibration of the joints, their temperature, the number of cycles performed by the robot. The data sent to the CMTK unit is processed and visualized in the Grafana environment, making it possible to track the state of the machine in real time. Tests conducted showed the cyclicity of vibrations during the robot's operation. A clear correlation was observed between the speed of the manipulator's movement and the vibration level - the highest values were recorded at 4000 mm/s, especially during the braking phase. Deviations from the established pattern can indicate potential failures. The test results confirm the effectiveness of the applied solution as a diagnostic tool ready for industrial deployment. Despite the initial cost, the implemented solution increases production efficiency by reducing downtime and enabling preventive component replacement.