Design of a Data Collection Layer for Complementary Diagnostic and Condition Monitoring System of a Robotic Workplace

The core of this contribution is the design of a system for the identification of parameters and preliminary diagnostics of a robotic workplace based on the collected data from additive sensors. As the physical device for testing is a robotic workplace on the Festo AFB Factory automated production line is used. The goal of the proposed solution is to provide a complementary image of the state of the industrial workplace, through the additional sensory layer created. The first part of the publication is focused on data collection, considering the suitability of the data and the evaluation of the parameters necessary for the operability of the device. In addition, the key parameters for the predictive maintenance process are identified, and a method of further processing and evaluation of values is suggested. The proposed data collection layer is part of the planned predictive maintenance system that significantly improves the reliability of the designated workplace. The final solution offers the ability to react to device malfunctions in real time and correct/improve its condition with timely intervention.