With accurate real-time monitoring of Pusher Car Turnaround Time (TAT) and human geo-fencing, the system delivered a 1–2% productivity increase while improving resource utilization and reducing operational wastage.​
The AI-powered Level Monitoring System uses infrared and optical analytics to continuously measure molten metal levels with high precision, delivering real-time visibility, automated alerts, and programmable closed-loop control to stabilize furnace operations.
Reduce Downtime in Steel Plants Predictive Furnace Monitoring to Extend Equipment Life Achieved 95% accuracy in hotspot detection
Achieved a 70% reduction in temperature-related failures with AI-powered monitoring of switchyard assets, ensuring early detection of thermal anomalies and potential equipment faults for enhanced reliability and predictive maintenance.
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.
With accurate real-time monitoring of Pusher Car Turnaround Time (TAT) and human geo-fencing, the system delivered a 1–2% productivity increase while improving resource utilization and reducing operational wastage.​
The AI-powered Level Monitoring System uses infrared and optical analytics to continuously measure molten metal levels with high precision, delivering real-time visibility, automated alerts, and programmable closed-loop control to stabilize furnace operations.
Reduce Downtime in Steel Plants Predictive Furnace Monitoring to Extend Equipment Life Achieved 95% accuracy in hotspot detection
Achieved a 70% reduction in temperature-related failures with AI-powered monitoring of switchyard assets, ensuring early detection of thermal anomalies and potential equipment faults for enhanced reliability and predictive maintenance.
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.
Steelmaking process has fundamentally changed over the years. Earlier, steel was mainly produced through the blast furnace–oxygen furnace route using iron ore and coke. Now days, a large portion of global steel is produced through Electric Arc Furnace and Induction Furnace technologies, where melting recycled metal scrap from scrap yards, automobiles, appliances, scrap recycling industries and industrial waste streams.
Inconsistent metal scrap composition: Variation metal scrap, such as scrap size, shape, density, and chemical composition, makes furnace behavior unpredictable and difficult to control during melting.
Foreign non Metallic Objects Contamination: Scrap piles often contain non-metallic and hazardous items like batteries, gas cylinders, rubber, plastics, wood, and sealed containers. These pose serious safety risks and can disrupt downstream processes.
Equipment Damage and Downtime: Oversized or improperly processed scrap stresses shredders, conveyors, magnets, and EAF electrodes, causing mechanical failures and unplanned shutdowns.
Ripik AI enables real-time steel scrap monitoring of incoming and processed metal from sources such as scrap yards, automobiles, appliances, metal recycling industry and industrial waste streams used in the steelmaking process. The scrap metal inspection automatically inspects scrap for size, shape, density, and contamination to identify dangerous materials and oversized pieces before they reach critical operations. Hazardous items like batteries, gas cylinders, and pressurized canisters are detected early, and instant alerts are sent to the concerned teams. This proactive approach helps prevent accidents, protects vital assets including furnace components and conveyors, and ensures smooth, stable, and consistent steel production.
Specialized industrial-grade high-resolution cameras, rugged edge processors, and engineered vision systems are deployed on scrap receiving, conveyors, shredders, and furnace charging zones to enable real-time inspection and early detection of hazardous, oversized, and non-compliant scrap.
Real-time monitoring and analysis of scrap materials as they enter and move through the plant using live camera feeds. The system provides instant detection of dangerous materials, oversized scrap, and foreign or combustible contaminants, enabling safer handling and more reliable steelmaking operations.
The platform detects large particles and foreign objects in real-time, such as batteries, cylinders, and canisters that can harm shredders or electrodes, as well as foreign, combustible, and non-compliant contaminants within scrap streams, helping to prevent safety hazards and ensure the quality of the scrap.
Instant Alerts are sent whenever hazardous, oversized, or contaminated scrap is detected through live camera feeds. The platform delivers notifications instantly on WhatsApp, email, or hooters. It also has a feature of a closed-loop mechanism that enables immediate corrective action.
Comprehensive dashboards and automated reports provide scrap trend analysis, quality insights, and anomaly patterns, enabling data-driven decisions that improve safety, equipment reliability, melt consistency, and long-term efficiency in scrap handling operations.
Historical video feed allows reviewing past scrap inspection footage to detect hazardous objects, oversized pieces, contamination, recurring anomaly patterns, and missed non-compliant items, providing actionable insights to improve safety, traceability, and operational reliability in scrap handling processes.
