INFERENCE AND RELIABILITY IN THE MOST DEMANDING OPERATIONS

CONVEYOR BELT FAULT DETECTION

Real-time diagnostics using neural networks to detect wear, tears, and splice failures in conveyor belts. This continuous, non-invasive monitoring system optimizes availability and extends belt service life, providing reliable information for decision-making without interrupting the process..

Technical Documentation

ANOMALOUS OBJECT DETECTION IN BUCKET-WHEEL EXCAVATORS

Intelligent monitoring of bucket-wheel excavator discharge using artificial vision, millimeter-wave radar, and artificial intelligence. The solution detects and classifies anomalous objects and metallic elements in real time to support operational decision-making and reduce risks during the extraction process

Technical Documentation

FOREIGN OBJECT DETECTION ON THE PRODUCTION LINE

Automated detection and classification of foreign objects on iodine packaging lines using artificial vision. The solution identifies process-extraneous elements in real time, generates alerts, and provides traceability to reduce operational risks and prevent unplanned downtime.

Technical Documentation

MILL CHARGE LEVEL METER

Advanced inference to optimize mill efficiency by measuring stress on liner bolts. This easy-to-deploy system provides critical real-time data to estimate mill charge level and optimize mill operation, reducing unplanned downtime caused by critical failures.

Technical Documentation

ROPING DETECTION AND PREDICTION

Advanced AI-based monitoring to predict roping in hydrocyclones. The system integrates high-definition imagery from self-cleaning cameras with vibration data collected by wireless sensors installed at various points on the housing. This information makes it possible to measure the underflow discharge angle and detect conditions associated with roping at an early stage, ensuring flow stability and maximizing asset availability.

Technical Documentation

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