Slag pots used in blast furnace operations are prone to crack formation due to extreme temperatures, thermal cycling, and mechanical stresses. Current manual inspection methods are subjective and may miss critical defects. The challenge is to develop an automated, non-contact solution to accurately detect, classify, and report cracks on slag pots in a high-temperature steel plant environment, enabling safer and more reliable operations.

Torpedo ladles used for hot metal transportation are currently secured using manually placed wooden scotch blocks, exposing operators to significant safety risks from moving equipment, high temperatures, and pinch points. The plant operates 51 torpedo ladles of varying sizes, with scotching requirements differing based on wheel position and track gradient.The challenge is to develop an automated, remotely operated scotching system integrated onto the torpedo ladle itself, capable of deploying and retracting scotch blocks without manual intervention. The solution must be self-powered, operate reliably in harsh steel plant conditions (up to ~250°C), withstand heat, dust, and sparks, be fail-safe during emergencies, and either use existing wooden scotch blocks or a suitable alternative material with equal or better performance. Modifications to existing equipment or infrastructure may be considered.

Hot metal samples are manually collected from blast furnace runners three times per cast, exposing operators to molten metal, extreme heat, fumes, glare, and splash hazards. We seek autonomous or remote-operated solutions that can safely and reliably collect representative samples with equal or better consistency while operating in harsh runner conditions and eliminating human exposure.