Live Challenges

Open Industrial Problem Statements

Explore details and align your solution with Tata Steel’s priority thrust areas.

Details: One of the primary challenges in the steel scrap industry is the precise identification of various types of scrap materials during the unloading of raw materials from trucks. This includes categorizing materials such as steel, rusted components, coated materials, hazardous substances, rubber, plastic, and soil.

Expected solution: Solutions are invited for Vision Analytics (VA) and Artificial Intelligence (AI) based systems that can accurately classify incoming materials and generate detailed reports, including the percentage of ferrous components in the raw material.

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Problem overview: Non-uniform shrinkage during continuous casting of steel slabs leads to longitudinal and transverse corner cracks. These defects need to be removed before further processing. Current selective scarfing based on casting speed and grade is still inadequate, causing internal rejection.

Inspection challenges:

  • Detect longitudinal cracks and transverse corner cracks
  • Inspect while slab moves at about 6 m/min
  • Surface temperature above 600 °C
  • Cracks masked by scale and oscillation marks
  • Preferred sensitivity for cracks ~20–30 mm length and ~3 mm depth

Desired solution: An NDT system for online inspection of slabs for surface defects at hot condition in the slab caster—enabling selective/condition-based scarfing to improve productivity and reduce rejection.

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