CDUX360
CDUX360 is an AI-powered decision support solution designed for Crude Distillation Units (CDUs). It combines domain expertise with machine learning to benchmark unit performance, identify optimization opportunities, and provide actionable insights across yield, energy efficiency, product quality, asset reliability, and throughput.
Configured to each unit’s operating envelope, CDUX360 analyzes plant data to identify performance gaps and connects each opportunity to its driving parameters. This gives engineering and operations teams clear root-cause insights and quantified recommendations to support more effective operating decisions.
Salient Features
Client Benefits
Increase Distillate Recovery by 0.5–2 wt%
Optimize cut points and maximize distillate recovery using operating data, performance insights, and yield soft sensors.
Reduce Quality Giveaway by 0.5–2%
Use product quality soft sensors for parameters such as diesel FBP, kerosene flash point, and VGO quality to improve visibility and minimize quality giveaway.
Increase Throughput by 1–3%
Improve CDU throughput through pumparound optimization and enhanced column performance.
Accelerate Data-Driven Operator Actions
Translate operating deviations into ranked, quantified actions with the underlying cause, actual versus optimum conditions, and recommended adjustments, helping operators respond to performance opportunities more effectively.
Dashboard & Snapshots
![Solution configuration [Defining the Objective: Maximize Production, Minimize Utility]:](https://ingenerox.ai/wp-content/uploads/2025/05/Picture3-3.png)
![Solution configuration [Defining cases of interest – Multiple cases can also be added]:](https://ingenerox.ai/wp-content/uploads/2025/05/Picture4-3.png)
Case Studies
Development of Soft Sensor to predict the C5 contents in Debutaniser column Overhead:
Background
In modern petrochemical operations, maintaining product specifications within tight limits is critical for both quality assurance and process efficiency. One of the key challenges faced by a leading chemical plant was the need for real-time prediction and monitoring of C5 content in the overhead stream of the debutanizer column — a crucial step to ensure product specification compliance and optimize operations.
Challenge
Traditional laboratory testing methods for measuring C5 content introduced significant time delays, making real-time adjustments difficult. The plant required a fast, accurate, and reliable solution to continuously monitor C5 levels, allowing operators to take timely corrective actions and avoid off-spec products.
Solution with AnalyticX
Using AnalyticX, the engineering team was able to develop a soft sensor — a machine learning-based predictive model — specifically designed to estimate the C5 content in the debutanizer overhead stream in real time.
Key steps included:
- Seamless ingestion of historical operational data into AnalyticX without any coding requirements.
- Applying statistical analysis to identify key process variables influencing C5 concentrations.
- Rapid development and training of a machine learning model tailored to predict C5 content with high accuracy.
- Deployment of the predictive model into live operations for real-time product spec monitoring.
Results
- Enhanced Product Monitoring:
Operators now have a real-time view of the predicted C5 content, significantly reducing reliance on delayed lab measurements. - Improved Process Control:
By closely tracking C5 levels, the plant was able to make timely adjustments to operational parameters, ensuring consistent product quality. - Reduced Off-Spec Production:
Real-time insights helped minimize off-spec batches, leading to material savings and reduced reprocessing costs.
Key Takeaways
- AnalyticX enabled the rapid development of a soft sensor customized for critical KPI monitoring.
