(7c) Understanding Exchanger Practically for Improving Performance

Exchangers are one of the key assets of almost any operating unit and an important aspect of overall process performance improvement. Optimization of exchanger operation is critical and is feasible through application of the right predictive and prescriptive analytical techniques.

A good monitoring process continuously tracks equipment closely to identify deviations in operating parameters and understand issues before they impact performance. Nevertheless with multiple process parameter changes it's not easy. Using advanced analytical tools in combination with machine learning techniques and AI is a valuable and effective way to identify deviations and problems earlier than traditional manual efforts. Taking a pro-active technical approach anticipates the problem before it reaches alarm levels and generally provides time for correction.

This paper will discuss techniques to identify deviation in equipment performance easily and accurately and provide insights quickly. Additionally, the paper will describe how predictive and prescriptive analytics can help determine the impact of deviations, the need for corrective action and assist in reaching innovative solutions.

Exchanger performance troubleshooting can be a tedious process as multiple operating and design factors affect actual performance. Sometimes smart design improvements are needed, but often options are available to restore the desired performance through intelligent process adjustments. Ensuring optimal exchanger operation requires understanding of the design/process complexities and overall functioning of the equipment.

This paper will cover several case studies to demonstrate on how units were able to substantially enhance their Overall Asset Effectiveness by improving the exchanger monitoring and performance.