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.
Enhance blast furnace stability, efficiency, and productivity with AI-driven insights and recommendations. Tackle the inherent complexity of blast furnace operations to optimize performance, reduce downtime, and improve overall output.
Blast furnace steelmaking faces challenges like raw material variability, inconsistent fuel rates, uneven burden distribution, and disrupted efficiency. Refractory wear and downtime increase maintenance costs. Computer vision solutions optimize furnace stability, reduce costs, and improve productivity.
Inconsistencies in steel raw materials, such as oversize particles, & moisture content, disrupts steel process, increases fuel consumption and impacts product's quality.
Burden mix calculations are mostly done manually or in excel format to achieve the right burden mix for target variables like basicity, alumina%, etc.
It is crucial to continuously analyze the factors that impact the fuel rate to ensure uninterrupted efficiency as fuel rate has a direct impact on productivity and quality.
Continuous wear and tear on furnace lining increase unexpected downtime and maintenance needs compromising overall productivity
Accurate Particle Size Analysis: Computer vision systems enable over 90% accuracy in measuring raw material size across coke (BF and Nut coke), sinter, pellet, and lump ore, ensuring optimal burden distribution in blast furnace operations.
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Real-Time Alerts: Get real-time data with automated alerts for higher fines percentage and visual anomalies such as high moisture content, enabling swift corrective actions.
Burden Mix Optimization:Â The Burden Mix Tool optimizes blast furnace operations by analyzing chemistry and costs to determine the best sinter, pellet, ore, and flux mix. Integrated with LIMS and genetic algorithms, it provides real-time adjustments & recommendations.
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Data warehouse integration:Â By analysing historical and real-time data, the data warehouse identifies optimal operating parameters, improving efficiency, and furnace stability.
AI Stability Monitoring:Â Vision AI models continuously monitors thermal, pressure profiles, and raw materials to provide early alerts and AI-driven recommendations, optimizing burden distribution and furnace performance.
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Optimized Furnace Operations:Â In-depth analysis of furnace production and permeability, along with effective SOPs, improved productivity by 3% through optimized gas flow and efficiency.
Root Cause Analysis: Ripik’s AI model delivers real-time root cause analysis (RCA) and corrective recommendations to maintain high etaCO and reduce coke rate in the furnace. The tool identifies variables that positively and negatively impact etaCO, providing actionable insights for optimization.
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Operational Recommendations: Vision AI tool provides recommendations for setting operational variables to optimize performance and efficiency in the furnace.
AI-ML Based Hot Metal Silicon Prediction: Ripik’s AI model predicts the hot metal silicon (Si) in the upcoming cast based on raw material and process parameters. It offers recommendations for adjusting PCI/RAFT to stabilize silicon levels. The model achieves a 40% reduction in standard deviation, improving prediction accuracy.
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Instant Alerts :The tool performs continuous RCA on Si values, with WhatsApp alerts for timely notifications when key variables change.
Real-time Monitoring:Â Vision AI agents enables real-time tuyere monitoring, detecting issues like tuyere sticking, lance off-centering, and choking with high accuracy.
Historical Video Feed : Real-time alerts notify operators of anomalies, to remove manual inspections, enhances safety, and improves furnace performance. Timely intervention minimizes unplanned shutdowns and extending tuyere lifespan.
360-Degree Monitoring with IR Cameras: Multiple IR cameras offer full furnace shell coverage, detecting temperature variations and identifying hotspots in real-time, ensuring comprehensive monitoring to eliminate steel downtime.
Real-Time Alerts:Â Receive instant alerts for hotspot regions and track recurring issues, enabling timely intervention to reduce refractory failure risks and extend refractory life.
Early Detection of Belt & Chute Damage:Â Bunker level monitoring provides real-time data to detect material flow abnormalities that may cause belt and chute damage in blast furnace operations. By tracking bunker levels, it identifies fluctuations or blockages, enabling early intervention to prevent equipment wear and reduce downtime in steel plants. This proactive approach prevents failures, and extends the lifespan of critical components, ensuring stable furnace performance.
Vision AI in the blast furnace steel making process enable real-time monitoring, early detection of equipment issues, improved efficiency, reduced downtime, and extended component lifespan for stable, cost-effective furnace performance.
Real-time blast furnace monitoring and predictive maintenance ensure smoother operations, leading to higher throughput, better quality, and more consistent output in the steelmaking process.
Advanced monitoring and predictive maintenance reduce costly repairs, while optimizing fuel usage and process efficiency lowers material waste and energy consumption, leading to significant savings in steelmaking.
Blast furnace operations extend equipment life by optimizing performance and enabling early issue detection in refractory linings, reducing wear and preventing costly breakdowns.
Blast furnace operations reduce carbon emissions by optimizing fuel usage and enhancing combustion efficiency. Precise monitoring minimizes fuel consumption improving steelmaking process.
A powerful suite of intelligent agents working in sync to transform manufacturing with speed, precision, and autonomy.
