
Anodes serve as conductive blocks in the electrolytic process, where their integrity directly impacts electrical energy consumption, carbon purity, and overall plant productivity. Defective anodes—whether caused by surface issues like cracks, segregation, oxidation, or stub holes damage —lead to irregularities in the smelting process, increasing power consumption and reducing the lifespan of the pots.
Traditional manual inspection methods for ABF (Anode Butts Firing) and GAP (Green Anode Plant) anodes have limitations in consistency and accuracy. Human error, fatigue, and subjective judgment make it difficult to ensure uniform quality control, especially in large-scale operations. This is where automation, powered by AI and deep learning, transforms the process.
Insightzz’s Anode Inspection System
Leveraging advanced deep learning and computer vision technologies, Insightzz's system automates the detection of surface defects on anodes, ensuring precision and efficiency at a level far beyond what manual inspections can achieve.