Lummus-staging

Salt Deposition Prediction
and Advisor

Prevent fouling, extend lifespan, ensure reliability!

Product Introduction:

The advanced REAC Monitoring Solution for Hydrocracking units is designed to enhance operational reliability and safety. This model integrates a powerful hybrid approach, combining first-principles engineering with data-driven machine learning algorithms. By utilizing real-time sensor data and advanced analytics, it predicts and prevents fouling and corrosion risks, such as ammonium bisulfide and ammonium chloride salt deposition, in the Reactor Effluent Air Cooler (REAC) system.

The hybrid approach not only delivers precise diagnostics but also optimizes maintenance schedules, boosting operational efficiency and minimizing downtime. By extending the lifespan of critical equipment, it drives substantial cost savings while ensuring a safer, more reliable operation.

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Hybrid Model

Our hybrid model seamlessly integrates first-principles methodologies with advanced machine learning techniques to optimize wash water management and prevent salt deposition in reactor effluent systems. The first-principles component leverages precise equations and correlations to calculate sublimation temperatures and deposition conditions for ammonium bi-sulfide and ammonium chloride. Simultaneously, the machine learning model analyzes historical data and real-time measurements to accurately predict the necessary wash water volume based on deposition percentages and sublimation temperatures. This powerful combination enhances predictive capabilities, enabling dynamic adjustments to wash water injection rates and maintaining optimal operating conditions. By implementing this hybrid model, we effectively mitigate corrosion risks, enhance system reliability, and ensure operational efficiency in managing salt deposition—transforming your operations for improved performance and longevity.

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Transform your Challenges into Opportunities

The Salt Deposition Prediction and Advisor addresses critical issues related to salt deposition, providing a robust hybrid model that predicts and mitigates corrosion risks. By combining first-principles methodologies with machine learning, our solution optimizes wash water management, enhances operational reliability, and improves equipment longevity. This proactive approach not only ensures optimal conditions but also drives cost savings across your operations.

Pain Point

Benefit

Effectively predicts and manages corrosion risks from ammonium bi-sulphide and ammonium chloride while mitigating salt deposition, enabling companies to enhance equipment longevity by up to 20% and reduce annual maintenance costs by approximately 15%.

Pain Point

Benefit

Continuous monitoring and predictive analytics help maintain optimal conditions minimizing unplanned downtime and enhancing system performance.

Pain Point

Benefit

Optimize energy usage and enhance the equipment lifespan with actionable recommendations based on AI-driven insights and hybrid model approaches.

Pain Point

Benefit

Enables early detection of potential issues, facilitating timely interventions that reduce maintenance costs and prevent unscheduled shutdowns, saving up to $500,000 per incident and over $2.5 million in five years, while significantly boosting profitability and operational efficiency.

Performance Deviation Prediction

Calculate the concentration of salts present, determine the sublimation temperature under the given conditions, and predict the optimal flow rate of wash water required for the process.

Complete monitoring of the all parameters including properties of Feed, Product, Gas streams, Wash water, Sour water, Sublimation temperatures and concentration of the salts.

Trend plots for

  1. Inlet & Outlet Velocities
  2. Outlet temperature
  3. Concentration of salts
  4. Sour water pH, Fe content
  5. Wash water flow

Comparison plots
1. Sublimation Temperature & Operating Temperature
2.Actual & Recommended wash water flow
3. Actual & Recommended Free water flow

Actionable recommendation (comparing with current values) on controllable parameters like Wash water flow

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