Ripik.ai has been associated with IMFA since Jan 2023 towards implementation of Industry 4.0 in our Choudwar plant located in Odisha. They are working on two machine learning / data science use related to power and metallurgical coke consumption optimization through real-time alerts. The team has good knowledge in the areas of data science & machine learning, and their problem solving skill set is high
I have known Pinak, Arunabh and Navneet since 2017. They were part of Advanced analytics program in TSK between 2017 and 2020 and placed a crucial role in its delivery. The team worked end to end in conceptualization and delivery of the use cases across Blast Furnace, Sinter Plant and Steel Melt Shop.
Ripik.ai has been the analytics partner of Godrej & Boyce since March 2022. They have been doing projects with the Interio and Aerospace businesses already and we are exploring use cases for other businesses as well. Pinak and his team have worked with us closely on these manufacturing use cases. They have an unparalleled understanding of the process and can bring impact very quickly
I am delighted to write this testimonial about Ripik.ai, one of ESL’s analytics partner since January 2023. The Ripik.ai team is working on three use cases in our Upstream section at the Bokaro plant – Digital Twin of Blast Furnace, Burden Mix optimization in Blast Furnace and Green Mix optimization in Sinter Plant Burden Mix optimization in Blast Furnace and Green Mix …
Meet our elite squad - some of the brightest minds from Google, MIT, and IITs, pioneering the future at Ripik.AI.
Choose Ripik.AI for innovative Computer Vision AI Solution that drive operational excellence in manufacturing industries.
Join Ripik.AI where learning is more impactful, diversity inspires, and work-life harmony thrives.
Explore the latest breakthroughs, partnerships, and global recognitions shaping Ripik.AI's impact on industrial AI
Discover Ripik AI's latest event appearances showcasing cutting-edge AI solutions for manufacturing.
Tackle raw material variability and environmental challenges with accurate, real-time visibility.
Transforming Cement Manufacturing Operations with Our Patented Vision AI SaaS Platform for Process Optimization
Empower operators to precisely control bath temperature and significantly reduce power usage and AIF3 consumption.
Solve high impact use cases and maximize quality by identifying important parameters and sweet spot of operations.
Revolutionizing boiler operations with patented Computer Vision for higher productivity and lower energy costs.
Unlock efficiency and optimize processes across industries with our advanced, and intelligent AI technologies.
Ripik’s Vision AI Agents are your automated pair of eyes — developing intelligent monitoring agents for engineered industrial performance.
Move beyond number crunching and reduce process variability with an automated pair of eyes—our Vision AI platform
Let us walk you through a tailored demo experience.
Tackle raw material variability and environmental challenges with accurate, real-time visibility.
Transforming Cement Manufacturing Operations with Our Patented Vision AI SaaS Platform for Process Optimization
Empower operators to precisely control bath temperature and significantly reduce power usage and AIF3 consumption.
Solve high impact use cases and maximize quality by identifying important parameters and sweet spot of operations.
Revolutionizing boiler operations with patented Computer Vision for higher productivity and lower energy costs.
Unlock efficiency and optimize processes across industries with our advanced, and intelligent AI technologies.
Ripik.ai has been associated with IMFA since Jan 2023 towards implementation of Industry 4.0 in our Choudwar plant located in Odisha. They are working on two machine learning / data science use related to power and metallurgical coke consumption optimization through real-time alerts. The team has good knowledge in the areas of data science & machine learning, and their problem solving skill set is high
I have known Pinak, Arunabh and Navneet since 2017. They were part of Advanced analytics program in TSK between 2017 and 2020 and placed a crucial role in its delivery. The team worked end to end in conceptualization and delivery of the use cases across Blast Furnace, Sinter Plant and Steel Melt Shop.
Ripik.ai has been the analytics partner of Godrej & Boyce since March 2022. They have been doing projects with the Interio and Aerospace businesses already and we are exploring use cases for other businesses as well. Pinak and his team have worked with us closely on these manufacturing use cases. They have an unparalleled understanding of the process and can bring impact very quickly
I am delighted to write this testimonial about Ripik.ai, one of ESL’s analytics partner since January 2023. The Ripik.ai team is working on three use cases in our Upstream section at the Bokaro plant – Digital Twin of Blast Furnace, Burden Mix optimization in Blast Furnace and Green Mix optimization in Sinter Plant Burden Mix optimization in Blast Furnace and Green Mix …
Meet our elite squad - some of the brightest minds from Google, MIT, and IITs, pioneering the future at Ripik.AI.
Choose Ripik.AI for innovative Computer Vision AI Solution that drive operational excellence in manufacturing industries.
Join Ripik.AI where learning is more impactful, diversity inspires, and work-life harmony thrives.
Explore the latest breakthroughs, partnerships, and global recognitions shaping Ripik.AI's impact on industrial AI
Discover Ripik AI's latest event appearances showcasing cutting-edge AI solutions for manufacturing.
Ripik’s Vision AI Agents are your automated pair of eyes — developing intelligent monitoring agents for engineered industrial performance.
Move beyond number crunching and reduce process variability with an automated pair of eyes—our Vision AI platform
Let us walk you through a tailored demo experience.
The world is growing hotter, leading to escalating crises such as rising temperatures, sudden floods, droughts, and other severe environmental issues. Extreme heatwaves, erratic storms, and unprecedented weather events are becoming increasingly common. In response to these pressing issues, there is a growing global movement toward sustainable living, aiming to mitigate the damage and create a more resilient future.
However, a major contributor to these problems is the heavy metal and manufacturing industry, particularly steel and cement production, which significantly exacerbates these environmental challenges with its substantial carbon emissions. To make a meaningful difference, we must focus on making these industries more sustainable for a better future.
AI is revolutionizing sustainable manufacturing by enhancing efficiency and reducing environmental impact. In industries like the heavy metal sector, AI for sustainable manufacturing optimizes energy consumption by adjusting operations in real-time, ensuring machinery operates at peak efficiency. This optimization leads to lower energy use and reduced carbon emissions, contributing to a smaller carbon footprint. Additionally, AI improves waste management by analyzing production data to minimize waste, recycle materials, and handle hazardous by-products more effectively.
Computer vision AI platforms are instrumental in these advancements, offering precise monitoring and management of production processes. AI for sustainability extends its benefits to resource efficiency by enabling better use of raw materials, water, and chemicals through predictive analytics and digital twins—virtual models of the manufacturing process. These tools simulate various scenarios to recommend the most resource-efficient methods, reducing both waste and the environmental impact of material extraction. In industries dealing with hazardous chemicals, AI for environmental sustainability ensures safer practices by tracking substances, predicting potential hazards, and providing early warnings to prevent accidents. As AI technology continues to advance, its role in AI for sustainable development will become increasingly crucial, paving the way for a greener future.
Reducing carbon emissions is a critical component of achieving sustainability in manufacturing, and AI is playing a transformative role in this area. AI for sustainable development, particularly through advanced computer vision platforms, enables real-time monitoring and optimization of energy-intensive processes. In the cement industry, for example, computer vision AI platform assesses the health of cement kilns, identifying whether they are dusty, healthy, or hot. By providing precise recommendations, this technology helps control fuel rates, prevent kiln jamming, and significantly reduce energy consumption. As a result, manufacturers can lower their carbon footprint and produce greener cement, making their operations more environmentally sustainable and contributing to global efforts to combat climate change.
Effluent treatment is a critical area where AI is driving sustainability in manufacturing, particularly in industries like steel production. AI models play a pivotal role in reducing the toxicity of industrial discharges, which is essential for minimizing environmental impact. For instance, in steel plants, AI solutions such as AiFe are instrumental in controlling cyanide levels in effluents, ensuring they meet stringent environmental standards. By optimizing these parameters, AI significantly improves the quality of effluents discharged into the environment, enhancing plant sustainability and contributing to a safer and cleaner ecosystem. This alignment with broader environmental goals underscores the transformative impact of AI on sustainable manufacturing practices.
Managing hazardous chemicals effectively is essential for sustainable manufacturing, and AI-driven solutions are making significant strides in this area. AI for sustainable development includes the use of digital twin models in processes like pulp manufacturing. For example, a computer vision AI platform has been utilized in the bleaching stage to reduce the use of harmful chemicals and minimize effluent generation. This not only improves the sustainability of the manufacturing process but also ensures a safer and more environmentally responsible operation.
In a prominent steel company, the implementation of Ripik AI Intellifurnace has significantly advanced sustainability efforts in the manufacturing sector. By integrating advanced AI-driven solutions, including computer vision AI, the steel manufacturer has optimized its furnace operations, leading to remarkable improvements in energy efficiency, process stability, and emission reductions. This innovative approach is a key step towards producing greener steel, setting a new standard for environmentally responsible manufacturing practices.
The steel manufacturer has leveraged Ripik Intellifurnace’s computer vision AI platform to achieve over 90% accuracy in sizing raw materials such as coke, sinter, pellet, and lump ore. This system provides real-time material non-compliance alerts every minute, detecting issues like higher fines percentages and visual anomalies, including high moisture content. By ensuring raw materials are consistently within the optimal size range, the company has enhanced the efficiency of its furnace operations, reduced energy consumption, and minimized waste—contributing to its sustainability goals.
To further its commitment to sustainable practices, the steel industry adopted Ripik’s AI-powered Burden Mix Optimizer. This production line monitoring solution calculates the most cost-effective and chemically balanced burden mix, considering input chemistry and the cost of components. The integration of a data warehouse helps identify the most optimal operating parameters for this composition. By reducing the need for excessive raw material consumption, this AI-driven optimization has significantly lowered the overall environmental footprint of the steel production process.
Maintaining stability in furnace operations is crucial for achieving energy efficiency and reducing emissions. The steel manufacturer implemented Ripik Intellifurnace’s blast furnace monitoring system, which provides real-time stability indicators based on pressure and thermal profiles within the furnace. The system generates automated alerts when stability is low and offers actionable recommendations for burden distribution adjustments. By stabilizing furnace conditions, the company has reduced operational inefficiencies, leading to lower energy usage and emissions, thus supporting its AI for sustainable manufacturing initiatives.
In its quest to lower carbon emissions, the steel industry has utilized Ripik’s AI model to maintain high carbon monoxide utilization efficiency (etaCO). The AI system provides real-time root cause analysis and corrective recommendations whenever there is a drop in etaCO. This proactive approach has enabled the manufacturer to maintain high etaCO levels, resulting in lower coke rates and reduced carbon emissions. Additionally, the company has utilized vision AI platforms dashboards for quality of steel cast, ensuring that the final product meets stringent quality standards while minimizing environmental impact.
The manufacturer has also adopted Ripik’s AI-ML model to predict the silicon content in upcoming casts based on real-time data from raw material and process parameters. This AI system offers recommendations for adjustments in pulverized coal injection (PCI) or RAFT (Reactor and Furnace Technology) to stabilize the silicon content. These optimizations have led to reduced energy consumption and minimized the environmental impact of the steel production process. Furthermore, the use of AI has contributed to reducing cloud compute costs associated with managing large datasets and complex simulations, making the entire process more sustainable.
As the world is heating up with the escalating challenges of climate change and environmental degradation, the manufacturing industry, especially heavy sectors like steel and cement, must evolve to become more sustainable. Integrating AI in sustainable manufacturing is more than a technological advancement—it is a crucial step towards building a resilient, eco-friendly future. By optimizing processes, reducing waste, and minimizing carbon emissions, AI-driven solutions such as computer vision systems and real-time monitoring tools are helping manufacturers not only meet environmental regulations but also improve operational efficiency and profitability.
The journey towards sustainable manufacturing is ongoing, and with AI at the forefront, it holds the promise of a greener, more sustainable world.
Insights and perspectives from Ripik.ai's thought leaders
AI-Driven Productivity Tracking involves real-time monitoring of workflows, resources, machine performance,...
IR monitoring combined with vision systems are trained to identify complex patterns and subtle thermal...
Effective manufacturing process monitoring ensures operational excellence, product consistency, and proactive...
Machine health monitoring empowers maintenance teams to transition from reactive maintenance to condition-based...
As businesses scale and diversify, the demand for greater efficiency, minimal downtime, and enhanced...
AI in the mining industry is not merely a trend; it’s a necessity. With vast operations often spread...
Discover how AI is transforming plant uptime in manufacturing by enabling predictive maintenance, real-time...
Agentic AI in manufacturing operations are designed, executed, and optimized. These systems act autonomously,...
Root Mean Square Error (RMSE) is a widely used metric that measures the average magnitude of prediction...
The blast furnaces steelmaking process is a complex and requires precise control over various parameters....
AI platforms for anomaly detection are transforming a wide range of industries by leveraging advanced...
The role of AI in enhancing energy efficiency in cement plants particularly in fuel Consumption is significant...
Vision AI agent operate through a structured pipeline involving perception, analysis, decision-making,...
Particle size analysis plays a critical role in heavy industries such as cement, mining, steel, and power...
Conveyor volume scanners are revolutionizing stockpile management by providing precise, real-time data...
AI agents are revolutionizing businesses by automating processes, improving decision-making, and optimizing...
Vision AI is an advanced artificial intelligence-powered system that uses computer vision to interpret...
Automating stockpile volume measurement with Vision AI and LiDAR for industries such as mining, cement,...
Agentic AI applications in manufacturing can optimize production lines, predict equipment failures, and...
As industries continue to evolve and demand higher levels of productivity, the adoption of computer vision...
Accurate raw material moisture analysis plays a pivotal role in industrial operations, directly influencing...
Eliminating downtime in cement plants is no longer a distant goal but a tangible reality with the adoption...
Optimizing cloud architectures for cost-effectiveness is the major goal of such an architecture. The...
Computer vision technology is a replica of human vision by enabling machines to "see" and analyze images...
AI is nowadays playing a pivotal role in contributing towards the reduction of the carbon footprint in...
Incorporating computer vision into factory operations will unlock several new opportunities for efficiency,...
Alternative fuels, such as Refuse-Derived Fuel (RDF), a type of solid waste, are increasingly being considered...
Discover how Vision AI, a cutting-edge technology, surpasses traditional ML models to optimize manufacturing...
Integrating AI in the cement industry is a much-needed breath of fresh air. We’re on the brink of a new...
Research by Nature claims that artificial intelligence can contribute to fulfilling 79% of the target...
The powerful combination of artificial intelligence and cutting-edge vision AI systems presents a breakthrough...
Learn how AI-driven preventive maintenance minimizes equipment downtime in heavy manufacturing. Boost...
Computer Vision AI is changing Asset Performance Management (APM) by enabling real-time monitoring and...
Coal moisture detection ensures that coal is at the right moisture level for optimal burning to enable...
Enhance Electric Arc Furnace efficiency with real-time monitoring and advanced visual analytics. Track...
The integration of Vision AI into cement kiln operations presents a transformative opportunity for manufacturers...
Real-time, automated refractory monitoring is a game-changer for high-temperature industries, providing...
Computer vision is revolutionizing machine monitoring system as it is crucial for optimal performance...
With the boom of AI in the manufacturing sectors, predictive maintenance with AI has arrived as a game-changing...
Computer vision AI platforms are instrumental in these advancements, offering precise 24/7 monitoring,...
For more information on how Ripik.ai can help your organization reduce cloud compute costs and optimize...
Computer Vision AI is a transformative technology poised to redefine production monitoring systems, contributing...
Anomaly detection in manufacturing is a critical component of maintaining product quality, ensuring operational...
Computer Vision AI Platforms have emerged as a game-changer in the manufacturing sector, revolutionizing...
AI-Driven Productivity Tracking involves real-time monitoring of workflows, resources, machine performance,...
IR monitoring combined with vision systems are trained to identify complex patterns and subtle thermal...
Effective manufacturing process monitoring ensures operational excellence, product consistency, and proactive...
Machine health monitoring empowers maintenance teams to transition from reactive maintenance to condition-based...
As businesses scale and diversify, the demand for greater efficiency, minimal downtime, and enhanced...
AI in the mining industry is not merely a trend; it’s a necessity. With vast operations often spread...
Discover how AI is transforming plant uptime in manufacturing by enabling predictive maintenance, real-time...
Agentic AI in manufacturing operations are designed, executed, and optimized. These systems act autonomously,...
Root Mean Square Error (RMSE) is a widely used metric that measures the average magnitude of prediction...
The blast furnaces steelmaking process is a complex and requires precise control over various parameters....
AI platforms for anomaly detection are transforming a wide range of industries by leveraging advanced...
The role of AI in enhancing energy efficiency in cement plants particularly in fuel Consumption is significant...
Vision AI agent operate through a structured pipeline involving perception, analysis, decision-making,...
Particle size analysis plays a critical role in heavy industries such as cement, mining, steel, and power...
Conveyor volume scanners are revolutionizing stockpile management by providing precise, real-time data...
AI agents are revolutionizing businesses by automating processes, improving decision-making, and optimizing...
Vision AI is an advanced artificial intelligence-powered system that uses computer vision to interpret...
Automating stockpile volume measurement with Vision AI and LiDAR for industries such as mining, cement,...
Agentic AI applications in manufacturing can optimize production lines, predict equipment failures, and...
As industries continue to evolve and demand higher levels of productivity, the adoption of computer vision...
Accurate raw material moisture analysis plays a pivotal role in industrial operations, directly influencing...
Eliminating downtime in cement plants is no longer a distant goal but a tangible reality with the adoption...
Optimizing cloud architectures for cost-effectiveness is the major goal of such an architecture. The...
Computer vision technology is a replica of human vision by enabling machines to "see" and analyze images...
AI is nowadays playing a pivotal role in contributing towards the reduction of the carbon footprint in...
Incorporating computer vision into factory operations will unlock several new opportunities for efficiency,...
Alternative fuels, such as Refuse-Derived Fuel (RDF), a type of solid waste, are increasingly being considered...
Discover how Vision AI, a cutting-edge technology, surpasses traditional ML models to optimize manufacturing...
Integrating AI in the cement industry is a much-needed breath of fresh air. We’re on the brink of a new...
Research by Nature claims that artificial intelligence can contribute to fulfilling 79% of the target...
The powerful combination of artificial intelligence and cutting-edge vision AI systems presents a breakthrough...
Learn how AI-driven preventive maintenance minimizes equipment downtime in heavy manufacturing. Boost...
Computer Vision AI is changing Asset Performance Management (APM) by enabling real-time monitoring and...
Coal moisture detection ensures that coal is at the right moisture level for optimal burning to enable...
Enhance Electric Arc Furnace efficiency with real-time monitoring and advanced visual analytics. Track...
The integration of Vision AI into cement kiln operations presents a transformative opportunity for manufacturers...
Real-time, automated refractory monitoring is a game-changer for high-temperature industries, providing...
Computer vision is revolutionizing machine monitoring system as it is crucial for optimal performance...
With the boom of AI in the manufacturing sectors, predictive maintenance with AI has arrived as a game-changing...
Computer vision AI platforms are instrumental in these advancements, offering precise 24/7 monitoring,...
For more information on how Ripik.ai can help your organization reduce cloud compute costs and optimize...
Computer Vision AI is a transformative technology poised to redefine production monitoring systems, contributing...
Anomaly detection in manufacturing is a critical component of maintaining product quality, ensuring operational...
Computer Vision AI Platforms have emerged as a game-changer in the manufacturing sector, revolutionizing...
A powerful suite of intelligent agents working in sync to transform manufacturing with speed, precision, and autonomy.
Industries
Products
Support
Client Stories
Resources