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Predictive Maintenance

Artificial intelligence spares the engine block hammers

The production of engine blocks is already almost fully automated. An intelligent system is currently being developed in Passau to also automate the monitoring of these processes.

30 Mar. 2018
Artificial intelligence spares the engine block hammers (Photo: R. Scheuchl GmbH)

The Institute for Software Systems in Technical Applications of Computer Science ( FORWISS ) at the University of Passau focuses on a critical load phase in production: as part of pre-coring - the equipment is provided by project partner R. Scheuchl - two pneumatic hammers hit the component at the same time with centimeter precision in order to loosen the sand in the inner casting cores without damaging the engine block.

This is where the QUAR project (predictive maintenance and quality assurance in raw part machining) comes into play: it uses machine-learning technology to make accurate predictions on the wear state of the machine tools. Specifically: The objective is to train it to predict when, for example, the hammers stop working properly. Sensors and power consumption are used as measured values that help determine the optimal time to replace critical components. The declared aim is to avoid unplanned downtimes in raw parts machining. The Free State of Bavaria is financing the research project with funds from the R & D program: Information and Communication Technology .