Engineers in Germany have developed an acoustic monitoring system that can tell whether parts have been assembled correctly during automated manufacturing processes.
A number of products are manufactured in large individual components and then glued or fitted together with robotic arms.
“Component tolerances play an important role: if they are too large, they can cause collisions and displacements,” said Danilo Hollosi, Head of Acoustic Event Detection at Fraunhofer IDMT in Oldenburg. The error is often noticed too late, which leads to unscheduled downtime and high costs.
Hollosi and his team have developed smart sensors that can be fitted directly to the machine or equipment and used to identify faults immediately. The sensors are sensitive to airborne sound and recognise faults based on noises.
“When mating connectors join together, it makes a click that the microphone or sensor picks up. If the click doesn’t happen, the acoustic monitoring system displays an error, which is reliably documented. At the same time, the relevant worker is notified,” said Hollosi.
In automated manufacturing, the metadata is used for process documentation and quality assurance. According to Fraunhofer, a unique feature of the solution is that the maintenance system can distinguish between countless types of clicks and mechanical impacts, while also filtering out noise interference in loud production environments.
“Not all clicks are the same. A mechanical connector sounds different to a light switch, a stapler or a biro. You’d be amazed how many different kinds of noise things make when they snap into position,” said Hollosi.
AI-based algorithms for audio analysis detect the interference and the target noises. Processing of the data is performed directly at the sensor.
The complete condition monitoring system – the microphone, audio signal processing technology, software and battery – are currently housed in a casing no larger than a packet of cigarettes.
A miniaturised solution is said to be available in three variants that can be integrated into existing systems. Users also have the option of attaching the scalable intelligent maintenance system to robots or of installing it several meters away from the machinery or equipment and at strategically valuable measuring points.
“In effect, we give machines a sense of hearing for quality assurance,” said Hollosi. “This allows manufacturers to punctually recognise signs of damage at an early stage, to reduce unscheduled downtime, to harmonise shop floor workflows and to increase the effectiveness of the overall plant.”