Proactive Condition Monitoring for Steel Manufacturing
(Heavy Industry)
THE CHALLENGE
- In steel manufacturing, the sinter plant plays a critical role in converting iron ore into sinter – a key raw material for the blast furnace.
- This process relies on a chain of pallet cars transporting iron ore and sinter along a closed track. The breakdown of pallet cars halts the entire production line, resulting in significant financial losses.
- Since the sinter plant is vital for steel production, any disruption to pallet car operations can severely impact overall production efficiency and profitability.
BUSINESS OBJECTIVE
The primary objective is to implement proactive monitoring of pallet cars to detect and address issues before they lead to production downtime. By adopting a proactive AI-driven condition monitoring solution, steel manufacturers could save up to $750k annually by reducing unplanned downtime and associated losses.
THE SOLUTION
- visionTrack leverages visual AI to detect early signs of wear and tear on pallet cars, including the classification of various types of wear and tear, including missing nuts and bolts, absent side walls, and damage to fire bars.
- The system employs cameras strategically placed to monitor the movement of pallet cars, classifying various types of wear and tear and issuing alerts when maintenance attention is required.
THE RESULT
Thanks to the strategic application of visual AI technology, steel manufacturers can:
- Improve profitability for the plant and business as a whole
- Enhance equipment reliability on sinter car lines
- Strengthen production continuity in sinter plants
- Streamline proactive maintenance processes
TECHNOLOGY USED
- Existing factory cameras
- visionTrack Computer Vision solution
