Implement AI for end-of-line testing and manufacturing process monitoring
Every quality control project is specific, producing unique sets of sounds. Although we do our best to satisfy the demands for standardized, easy-to-implement solutions, your project may require an offer from the Acoustic Academy offering. Let us discuss and evaluate your use case.
End-of-line testing solutions
EOL testing is usually performed by human operators or sound recording systems combined with human supervision. That often leads to error and consequent unpredictable costs. The AI-driven method enhances the accuracy of these checks and automates them.
Examples of EOL testing based on sound features:
- Fuel/oil pumps
- Door systems
- Home appliances
- Air-conditioning systems
Process monitoring solutions
Processes do not always run as designed. Sometimes workers or robots cannot make quality checks of each manufacturing step on the fly. Our solution hears those steps and evaluates whether they have been completed successfully.
Examples of process quality monitoring based on sound features:
- Sealing plugs recognition
- Popp clamp closing
- Fan imbalance
- Cavitation indication
Neuron soundware reshaped our end-of-line testing practices of mechanical units. The initial precision and consistency of detection of faulty units, with only thee full days of audio data available, were surprising. We closed the trial project with the amount of manual testing reduced by a staggering 95%. We are now rolling out the solution to our other three production lines.