We planted our patented Cognitive and Vision AI based technology – Ripik Vision for 90% + accuracy in burden mix optimization for reducing energy consumption. The technology is equipped to provide real-time predictions on coal size distribution, moisture, and colour mix, offering timely alerts for any significant variations. This involves optimization of burden mix components such as Lump, Chips, FRBL, and Briquette percentages and burden chemistry factors like basicity, MgO-by-Al2O3 ratio, and total Cr, among others. The technology extends its optimization to the mix of metallurgical coke and anthracite coal, resistance set point optimization, and the identification of maximum resistance for different burden mixes, all contributing to enhanced efficiency. With the Resistance Set Point Recommender in place, the suite ensures an overarching strategy for operational excellence and resource optimization.
The SaaS deployment has led to notable improvements in production and reductions in specific power and reductant consumption, with an annualized benefit of INR 230 (in lacs) observed over the last 6 months. Automated burden mix preparation optimizes efficiency, resulting in a 1% reduction in SPC and specific reductant consumption, translating to an annualized impact on the power industry. Additionally, our comprehensive approach with the development of a Burden Charging Recommender and Resistance Set Point Recommender, aimed at optimizing power and reductant consumption. The solution’s impact is evident in a 1.1% reduction in unburnt carbon in boilers, attributed to proactive actions by the CHP team based on software alerts, highlighting its effectiveness.