Business challenge

Unlike conventional fuels, AFR sourcing is challenging in India and material varies widely in particle size, composition, and calorific value. This variability leads to combustion instability, CO fluctuations and temperature spikes. Traditional controls —manual AFR feeding and periodic sampling—are often too slow to respond to real‑time changes, limiting AFR usage despite availability. UltraTech’s challenge was to increase AFR utilization without compromising kiln stability, throughput, or clinker quality.

Solution overview

UltraTech addressed the challenge through a group of integrated, closed‑loop solutions across AFR feeding, measurement, and control:

• Robotic feeding: A robotic feeding system was conceptualized and developed to ensure consistent, controlled AFR charging from the material piles, reducing feed variability and manual processing.
• Computer vision–based monitoring: AI vision systems analyze AFR on the conveyors, assessing size distribution and material composition. Through real-time classification, the system provides signals for fuel mix and energy potential, enabling timely corrective action.
• Kiln process optimization: Advanced self-training AI models monitor and manage complex relationships among kiln operating parameters (100+ variables), identify next-best action and operate the equipment autonomously, safely consuming higher AFR levels while maintaining optimal operating conditions.

Together, these interconnected systems convert AFR from a variable, reactive input into a measured and actively controlled fuel stream.

Realized impact

UltraTech’s integrated approach has enabled higher and stable AFR substitution. Plants have observed improved process stability, higher throughput and higher waste heat generation while increasing use of AFR. The solution supports UltraTech’s progress toward long‑term sustainability goals and demonstrates how AI and Robotics enable large‑scale fuel substitution.