Optimizing Crack Gas Compressor Loop

Project Overview

Enhancing efficiency and reducing costs for a major petrochemical manufacturer
Client: Large petroleum refinery and petrochemical manufacturer
Challenge: Optimize 5-stage Crack Gas Compressor system for improved efficiency and reduced costs
Approach: Data-driven intelligence leveraging advanced analytics and machine learning

Key Challenges

In the process industries, several key challenges can significantly impact operational efficiency and safety. Here are the main challenges we address:
  • High power consumption due to lower stage efficiencies
  • Excessive wash oil and Boiler Feed Water consumption
  • Fouling issues in inter-stage coolers
  • Need for real-time performance monitoring

Our Solution

Discover how our advanced AI/ML solutions can transform your operations. From data analysis to real-time KPI tracking, we provide comprehensive tools to enhance efficiency and safety.
  • Advanced data analysis of 4 years of operational data
  • Machine learning models (GBT and BART) for efficiency prediction
  • Design of Experiments for 'Golden fingerprint envelope'
  • Real-time dashboard for KPI tracking and optimization

Key Results and Benefits

  • ✓ Optimized Crack Gas Compressor
    Loop parameters
  • ✓ Reduced power consumption across
    all 5 stages
  • ✓ Decreased wash oil and Boiler Feed
    Water usage
  • ✓ Mitigated fouling in inter-stage
    coolers
  • ✓ Implemented real-time performance insights
  • ✓ Established proactive maintenance framework

Conclusion

By leveraging data-driven intelligence, we significantly improved the efficiency and performance of the client’s Crack Gas Compressor system. This optimization led to substantial cost savings, improved operational reliability, and set a new standard for proactive maintenance in the industry.
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