Stream image analysis software is designed to improve the efficiency of nonmetallic inclusion analysis for steel manufacturers.

Process metallurgists (like me) use math, physics and chemistry to describe what happens during metal manufacturing. Other researchers use math, statistics and computer science to study and optimize manufacturing at a larger scale.

Researchers at Carnegie Mellon University’s (CMU) Center for Iron and Steelmaking Research are bringing computer-vision and machine-learning techniques to the study of inclusions, hoping to increase the efficiency of inclusion analysis and gain new insights.

Improvements in steel manufacturing processes have yielded advancements in the purity of steel that, in turn, yield higher-quality end-use products.

Checking our incoming raw-material quality often involves rating nonmetallic inclusions, particularly when heat treating to high hardnesses.