Achieved 70% Reduction in downtime of conveyor failures with Ripik AI conveyor belt monitoring system. This ensured smoother operations, minimized downtime, and delivered significant cost savings.
Manual inspections frequently overlooked early signs of refractory damage, resulting in unplanned downtime. By contrast, AI-driven monitoring enables timely detection of wear, cutting downtime by 50% and enhancing operational reliability.
Reducing inconsistencies in calorific values through AFR monitoring optimizes combustion efficiency, minimizes equipment damage, and lowers energy consumption.
Achieved an 82% reduction in crusher blockages and a 20% decrease in unwanted stoppages in cement crusher operations by detecting oversized rocks in real time. This led to smoother operations, reduced downtime, and substantial cost savings.
Real-time camera intelligence to monitor materials, equipment, and processes, driving efficiency and consistency in industrial operations.
Hosts and manages hundreds of Vision AI Agents, enabling you to customize, deploy, and scale real-time monitoring solutions instantly across operations.
Let us walk you through a tailored demo experience.
Achieved 70% Reduction in downtime of conveyor failures with Ripik AI conveyor belt monitoring system. This ensured smoother operations, minimized downtime, and delivered significant cost savings.
Manual inspections frequently overlooked early signs of refractory damage, resulting in unplanned downtime. By contrast, AI-driven monitoring enables timely detection of wear, cutting downtime by 50% and enhancing operational reliability.
Reducing inconsistencies in calorific values through AFR monitoring optimizes combustion efficiency, minimizes equipment damage, and lowers energy consumption.
Achieved an 82% reduction in crusher blockages and a 20% decrease in unwanted stoppages in cement crusher operations by detecting oversized rocks in real time. This led to smoother operations, reduced downtime, and substantial cost savings.
Real-time camera intelligence to monitor materials, equipment, and processes, driving efficiency and consistency in industrial operations.
Hosts and manages hundreds of Vision AI Agents, enabling you to customize, deploy, and scale real-time monitoring solutions instantly across operations.
Let us walk you through a tailored demo experience.
Reduced inconsistent calorific values, with AFR monitoring for optimal combustion efficiency, minimizes equipment damage, and reduces energy consumption.
The client faced challenges with the existing material monitoring systems, which were inadequate to address the complexities of Alternative Fuels and Raw materials (AFR). The current procedures required constant manual monitoring that often lacked attentiveness and were highly subject to human bias. The traditional blending process had no sampling mechanism in place, resulting in inconsistent fuel quality and monitoring gaps. These issues made it difficult to ensure proper AFR management, impacting overall process efficiency and reliability.
Incorrect raw material being placed on the conveyor, leading to process disruptions.
Operators sometimes load the conveyor with unintended raw material, causing production errors, batch contamination, and potential damage to downstream equipment.
Feeding material from the wrong bunker, causing mix-up in the batch.
Feeding material from the wrong bunker results in incorrect composition, disrupting downstream processes and affecting product quality.
Incorrect labeling or tagging of material, resulting in confusion during blending.
Mislabeling materials causes confusion during blending, increasing the risk of using the wrong input and compromising consistency.
Variability in blend quality, often observed during night shifts due to operational inconsistencies.
Variations in operator practices or reduced supervision during night shifts lead to uneven blending and inconsistent product output.
Ripik AI adds a robust layer of blend compliance by continuously monitoring over 90% of the incoming material. Leveraging advanced AI algorithms, it ensures accurate identification and classification of raw materials, enabling precise blend ratios and reducing variability. This enhanced monitoring improves process consistency, minimizes off-spec production, and supports overall operational efficiency and regulatory compliance.
$1M
Expected value generation annually
The implementation of real-time AFR (Alternative Fuels and Raw materials) monitoring is expected to generate annual savings of up to $1 million. By replacing delayed responses with instant deviation detection, the system enables immediate corrective actions, ensuring consistent and compliant blends while significantly improving operational efficiency.
100+
Increase in consumption of alternative fuel
Consumption of alternative fuel increased by 10% following the elimination of blend ratio variations caused by insufficient continuous monitoring. Implementation of automated monitoring systems ensured consistent and accurate blending, leading to improved fuel efficiency and enhanced process stability
70%
Expected reduction in GHG emissions
Improving material analysis processes, specifically by increasing sample collection and analyzing over 90% of incoming materials, enables better quality control and optimization of feedstock. This enhanced monitoring is projected to reduce greenhouse gas emissions by 25,000 tons, supporting both environmental goals and operational efficiency.
See how leading companies across steel, cement, oil & gas, energy, automotive, chemicals, pharmaceuticals, FMCG, and other industries are transforming their operations with Ripik AI’s Vision AI solutions—driving real-time insights, enhanced safety, and intelligent process optimizations across the industrial landscape
Achieved 70% Reduction in downtime of conveyor failures with Ripik AI conveyor belt monitoring system....
Manual inspections frequently overlooked early signs of refractory damage, resulting in unplanned downtime....
Reducing inconsistencies in calorific values through AFR monitoring optimizes combustion efficiency,...
Achieved an 82% reduction in crusher blockages and a 20% decrease in unwanted stoppages in cement crusher...
The Flare Stack Monitoring System delivered over 90% measurement accuracy, replacing manual judgment...
Ripik AI's Ladle Activity Tracker enhanced ladle operations in steel plants with comprehensive real-time...
Ripik AI's material sizing solution achieved 95% accuracy, significantly enhancing raw material monitoring...
Ripik AI's Volumetric Estimation using LIDAR has transformed stockpile management, achieving over 95%...
In the world of cost-competitive steel market, our client managed to improve fuel rate and throughput...
See how Ripik.AI's real-time asset monitoring solution transformed a leading EPC company's operation...
