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Decision support system for predictive maintenance of laser cutting machines

We develop a new data-driven decision support system for predictive maintenance of laser cutting machines, with various modules that are integrated in the IoT system of Bystronic.

A new decision support system for predictive maintenance of laser cutting machines is developed and implemented in the IoT system of Bystronic Laser AG. The system provides a platform for condition monitoring, fault detection and prediction of the remaining useful life of systems and components as well as data-driven decision support and prescriptive recommendations for effective operation and maintenance of the laser cutting machines.

In the research project we focus on several sub-systems of the laser machine and develop fault detection algorithms for each one of them. To this end we process and analyze machine data and identify health indicators that can be then used for early detection of degradation of an upcoming fault.  The chosen use cases offer a clear advantage to Bystronic service staff and customers due to early fault detection and diagnosis and demonstrate the implementation of an IoT-based predictive maintenance toolbox.