Continuous fitness check predicts potential machine faults
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 Schütze at Saarland University has developed an early warning system for industrial assembly, handling and packaging processes. Intelligent sensors continuously collect a wide array of measurement data from inside plant machinery and compare the signal patterns against those for normal operating conditions. If the system detects a difference in the patterns that indicates a potential fault, it immediately notifies the equipment operator about what remedial measures should be taken. This helps engineers to plan maintenance more effectively and protects them from unpleasant surprises and unexpected production losses.