Ripik.AI focuses on reducing operational variability through optimal process control. We implemented our patented Cognitive and Vision AI based solution Ripik Vision, capable of particle differentiation based on color, moisture and size. With the plant team interaction and first-hand process control, we swiftly delved into comprehending their requirements.
Implementation of Blast Furnace (BF) Fuel Rate Control helped operators with the tools to pinpoint the key factors contributing to the increased fuel rate in the furnace. The extended applications of computer vision also predicted slag chemistry and hot metal silicon, optimizing operational efficiency. The application also forecasted scrap quality in Electric Arc Furnaces (EAF), contributing to enhanced performance and steelmaking precision.
This approach empowered operators to optimize fuel efficiency, enhance furnace performance, and contribute to more efficient and sustainable operations.
In the first few weeks of deployment, our client saw a significant 3% reduction in fuel use, which was ascribed to precise Coal and Sinter size control and uniformity. The integration of smart alerts, leveraging video feeds, and the capability for post-mortem analytics through the retrieval of historical images/videos, enhanced their operational efficiency and productivity.