Automatic anomaly detection for gears, tools, and other mechanical components is an advanced technology that leverages artificial intelligence to identify defects, wear, or irregularities on surfaces and geometries of parts. This solution is applicable in various sectors of metalworking, enhancing the quality and reliability of production processes.
Using deep learning algorithms and neural networks of the latest generation, the system analyzes images or videos to automatically detect imperfections that could compromise the functionality of components. This technology enables optimization of quality controls, waste reduction, and failure prevention, which could otherwise cause production downtimes or defective final products.
Thanks to the use of machine learning models trained on specific datasets, the system achieves high accuracy, correctly detecting over 90% of anomalies in the conducted tests.
How it can be used
The entire system can be integrated into existing industrial environments, adapting to fixed devices, quality control cameras, or embedded platforms. Data analysis is performed in real-time, allowing for immediate interventions and improving the traceability of detected anomalies.
Application scenarios
ET MechVision AI finds application in various industrial contexts, including:
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Quality control in production: automated inspection of gears, tools, and components to detect manufacturing defects or early wear.
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Predictive maintenance: analysis of component conditions to prevent failures and reduce maintenance costs.
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Industrial automation: integration with machinery for real-time quality control of manufactured parts.
Are you interested?
Would you like to try our anomaly detection system, or are you interested in a customized quality control solution for your company? Contact us for a free consultation!
