Advanced AI-Based Defect Detection and Pit Mapping

This leading metals and mining enterprise is a global force in aluminium and copper manufacturing, with operations spanning multiple continents. It delivers high-quality, value-added products that serve critical industries such as automotive, aerospace, construction, packaging, and electrical infrastructure. Backed by integrated operations, the organization maintains strong control over its supply chain—from raw materials to finished solutions. A strong focus on sustainability, innovation, and circular economy practices drives long-term responsible growth.

The inspection process faces major challenges due to its slow, manual, and labor-intensive nature, involving over 3,400 inspection points across deep pits, firewalls, and peepholes. Inspectors must work in extreme high-temperature furnace environments, with pits extending up to 5 meters, creating serious safety risks. The reliance on manual inspection increases the likelihood of missing subtle yet critical defects such as cracks, gaps, and surface bulges. These undetected issues often result in costly repairs, unplanned downtime, and heightened operational risk.

The solution began with installing heat-resistant, high-resolution cameras with infrared illumination to reliably capture furnace data in extreme conditions. Advanced AI models were developed and trained on custom-labeled imagery to detect and classify cracks, bulges, gas leaks, and surface deformities. A real-time monitoring system was deployed to trigger instant alerts and feed predictive maintenance dashboards for early intervention. Cloud-based data management and analytics enabled trend analysis, model retraining, and continuous performance improvement through version-controlled updates. Integrated safety and compliance modules further enhanced worker protection by detecting gas leaks and overheating risks in real time.