Enhance Material Blend Processing
Real Time AFR Blend Monitoring for Enhanced Efficiency
Reduced inconsistent calorific values, with AFR monitoring for optimal combustion efficiency, minimizes equipment damage, and reduces energy consumption.
One of the global leading Cement Manufacturers
Client Overview
The client is a leading cement and building materials manufacturer in Central Europe. As part of a global construction materials group, it plays a vital role in regional infrastructure development. With a strong emphasis on sustainability and digital innovation, the company delivers high-quality cement, concrete, and aggregates, continually improving efficiency while reducing environmental impact.
Problem Statement
Challenges in Material Handling, Accurate Feedstock Identification, and Maintaining Consistent Blend Ratios
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.
Material Wrongly Tagged before Blending
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.
Ripik AI's AFR Monitoring System enable Real-Time Calorific Value Optimization
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24x7 Alternative fuel Monitoring Real-time monitoring of AFR (Alternative Fuels and Raw materials) enabled the detection and classification of fuels such as plastics, rubber, and biomass used in cement kilns. By leveraging visual and spectral data, the system provided a detailed breakdown of material composition, allowing operators to accurately identify key fuel types and ensure optimal blending and combustion efficiency.
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Real-Time Calorific Value Optimization Real-time calorific value estimation was achieved by analyzing alternative fuel composition trends using AI-driven models, enabling the identification of inefficient fuel utilization patterns to enhance overall kiln performance.
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Get Instant Alerts Operators received instant alerts that identified issues such as inconsistent feed rates and irregular combustion patterns, enabling timely intervention to prevent critical failures and maintain process stability.
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Historical Video Feeds Historical video feed analysis enabled postmortem reviews to identify critical events, operator behavior, and operational patterns. Comprehensive reporting highlighted recurring issues and trends, allowing teams to take proactive measures.
Impact and Validation by End Users
delivered precise alternative fuel optimization solution with computer vision system
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.
10%
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
25kT
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.