The goal of the provided service is to keep the manufacturing process for recognized European automotive manufacturer running smoothly and detect failures that often arise with the automatic feeding system moving baskets around.
Production operators are not always present, as they have to supervise the rest of the production line. Incidents happen unexpectedly, on average twice a day. Due to the takt time of production, the response time must be very short (120 s). If the operators do not react within the limit, the baskets are damaged, which means downtime for the entire production line, which can subsequently jeopardize JIT deliveries to customers.
Neuron Soundware monitors the robots instead of human supervision. It consists of sound sensors collecting data, the industrial IoT devices to process them, and Artificial intelligence for continual evaluation of the sound data. When an incident occurs, the solution provides visual and audible warnings on-site to prevent further damages to the baskets and the long-term failure of the entire working cell.
“In order to provide the customer with information for instant decisions, we opted for neuron networks, which learn from acoustic data to recognize the noise made by a falling pallet. The longer the neural network continues learning, and the more times it captures this noise, the more data will be available for improving the learning process and error detection accuracy”, explains Petr Ivančák, Head of Technical Implementations in Neuron Soundware.