Continuous Fitness Check Predicts Potential Machine Faults (image) Saarland University Caption It keeps a constant eye on the condition of the machine, it carries out diagnostic analyses and it notifies the operator when a part needs to be replaced. The research team led by Andreas Schuetze at Saarland University has developed an early warning system for industrial assembly, handling and packaging processes. Nikolai Helwig (left) and Tizian Schneider, research assistants in the group, are pictured testing the smart condition monitoring system on an electromechanical cylinder. The research team will be exhibiting their technology at the Saarland Research and Innovation Stand (Hall 2, Stand B46) at Hannover Messe, which runs from April 24th to April 28th. Credit Oliver Dietze Usage Restrictions None Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.