CASE STUDY
How a Leading
Manufacturer Improved
Raw Material
Accuracy by
22%
Using USM’s AI-Driven Variance
Intelligence Solution
Client Overview
The client is a leading industrial manufacturer specializing in chemical-based production, operating a large-scale manufacturing ecosystem with over 250 chemical raw materials managed across 400 dedicated storage tanks. The organization supports multiple production lines and maintains a highly integrated supply chain to ensure consistent product quality and manufacturing efficiency.
Challenges
Managing raw material storage, transfer, and consumption at this scale introduced significant operational and measurement complexities. They faced growing complexity in monitoring raw material movements, ensuring measurement accuracy, and maintaining visibility across production cycles. Key challenges included:
Inaccurate Raw Material Measurement
Raw materials had varying chemical and physical properties, making it difficult to measure exact quantities due to environmental conditions such as evaporation, atmospheric pressure, and temperature fluctuations.
High-Volume Sensor Data
Each storage tank generated continuous data from Level Indication Transmitters (LIT), pressure sensors, and temperature sensors, creating large volumes of operational data that were difficult to structure and analyze.
Material Variance During Transfers
Raw materials moved through long-distance pipelines to production units. Faulty measuring devices, leakages, and process interruptions often created weight variances, impacting production ratios and final product quality.
Data Integrity and Visibility Gaps
Manual postings, duplicate invoicing, inter-tank transfers, and reverse material flows created fragmented records, limiting end-to-end traceability and delaying root cause identification.
Solution
The client needed greater precision in material tracking, stronger process visibility, and faster identification of variances to maintain production consistency and operational control.
USM implemented an Agentic AI-powered raw material intelligence system designed to analyze material behavior, detect anomalies, and predict variance causes in real time. The solution included:
AI-Powered Data Engineering
Structured and streamlined large-scale sensor and SAP data from 400 storage tanks to build a reliable foundation for model training.
Deep Learning-Based Variance Detection
Built AI models using Agentic AI frameworks and deep learning algorithms to analyze raw material properties and detect deviations caused by environmental or operational factors.
Root Cause Analysis Engine
Developed an intelligent root cause identification system capable of tracing variances back to:Environmental changes, Faulty measuring devices, Pipeline leakages, Vendor-level discrepancies or fraud
Predictive Intelligence Reporting
Enabled predictive analysis reports to proactively identify potential risks before they impacted production quality or inventory accuracy.
Results
Our impactful AI solution delivered measurable operational improvements across the plant. By leveraging Agentic AI and deep learning, USM transformed a highly complex raw material tracking environment into an intelligent, predictive manufacturing ecosystem. The client gained better control over inventory, reduced operational losses, and improved product quality through data-driven decision-making.
22%
Reduction in Raw Material Losses
AI-powered variance detection and improved material visibility helped reduce wastage across storage and transfer operations, driving a 22% reduction in raw material losses.
30%
Faster Fault Detection
Real-time anomaly detection enabled faster identification of faulty sensors and measuring equipment, minimizing process disruptions and improving operational continuity.
18%
Reduction in Maintenance Costs
Predictive maintenance insights reduced unplanned device failures and lowered overall maintenance expenses across critical measuring devices.
15%
Improvement in Quality
Accurate measurement and optimized raw material ratios improved formulation consistency and enhanced the quality of finished products.
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50% less manual effort · 92% auto-adjudication · 90% accuracy lift
OUR LOCATIONS
ASHBURN(HQ) | FRISCO