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.
A Globally acknowledged Pulp and Paper manufacturer achieved a remarkable 2% improvement in yield by implementing Vision AI based wood chip and log sizing and process control.
One of the prominent players in the pulp and paper industry is a conglomerate with a substantial presence in the market. With a strong commitment to excellence and sustainability, this conglomerate has become a significant force in the pulp and paper sector. In a cost-competitive market, pulp and paper unit’s 50% of production expenses are accounted by wood costs. Manual and infrequent sampling leads to imbalance in cooking, resulting in lower yields. These findings underscore the importance of automated raw-material sizing decisions for improved process outcomes for economic production.
The pulp and paper unit confronted several challenges. Manual and infrequent sampling practices have contributed to reduced yields. Additionally, the unit faces issues related to undetected thin-sized logs and the presence of under-sized or over-sized chips, leading to imbalances in the cooking process within digesters. These challenges underscore the need for more advanced and automated technologies, such as improved sampling methods and real-time monitoring systems, to optimize wood utilization and enhance overall operational efficiency in the production process.
The implementation of Ripik Vision proved as a transformative move for the facility. As a Vision AI based material sizing solution designed to assess the average particle size of wood chips, the technology provided real-time alerts for any anomalies detected. Additionally, the technology offers distinctive data insights and recommendations for optimal operational parameters, including H factor, Sulphate, and White liquor dosage in the digestor. These recommendations are tailored to the specific characteristics of input wood chips and log sizes, enhancing efficiency and performance in wood processing operations.
Ripik Vision enabled real-time identification of wood chip sizes and outgoing brightness, facilitating precise determination of cooking time and optimal white liquor dosage in the digester. This technology leads to improved yield, with a potential enhancement of 2%, and a notable 10% increase in throughput. Additionally, there is a significant 15% reduction in chemical consumption, resulting in a more efficient and sustainable wood processing operation.
“Our collaboration with Ripik.AI has been seamless, and their team has demonstrated an exceptional level of professionalism, expertise, and dedication to our project. We are excited to continue our partnership with Ripik.AI and are confident that their contributions will be invaluable to our continued growth and success. I highly recommend Ripik.AI to any organization looking for a reliable and expert analytics partner. ”
Assistant Vice President
