Hybrid Digital Twins for Advanced Monitoring and Prescriptive Maintenance
Periodic cleaning is a common and often necessary strategy to maintain the performance of heat exchangers over long operation runs. However, deciding which heat exchanger to clean, when to clean it and how to clean it (e.g. mechanically or chemically) is a non-obvious task which often relies on past experience and simplistic performance indicators rather than being condition-based and driven by economic optimisation and operational constraints.
Hexxcell's Hybrid Digital Twins for Advanced Monitoring and Prescriptive Maintenance are powerful operational excellence tool that support data driven decision making in refinery operations, maintenance, production planning, profitability and environmental sustainability.
Advanced Monitoring of Heat Exchangers
Hexxcell Studio™ Advanced Performance Monitoring Dashboard provides unprecedented insights into Heat Exchangers and Heat Exchanger Networks thermo-hydraulic performance, presenting them in easy to understand Key Performance Indicators (KPIs) which includes:
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Individual heat exchangers:
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Thermal performance (including fouling resistance, heat duty loss vs. clean)
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Hydraulic performance (ΔP vs ΔP clean)
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Key operating variables (e.g. shear stress, velocity, film temperature, wall temperature, Re number etc.) vs. clean conditions
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Heat exchanger contribution to network performance
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Overall network:
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Actual furnace inlet temperature vs. clean conditions (i.e. furnace inlet temperature if all exchangers were clean)
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Predicted pressure drops increase vs. clean conditions (i.e. if all exchangers were clean)
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Assessment and detailed breakdown of economics and other KPIs
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Advanced visualization plots
This keeps operators always aware of current field operations. Hexxcell Studio™ predicts future performance based on production plans and warns ahead of time of possible issues. What-if studies can also be performed to find alternative operating modes that avoid losses in production and optimise plant performance.
Prescriptive Maintenance and Operations Improvements
Periodic cleaning is a common and often necessary strategy to maintain the performance of heat exchangers over long operation runs. However, deciding which heat exchanger to clean, when to clean it and how to clean it (e.g. mechanically or chemically) is a non-obvious task which often relies past experience and simplistic performance indicators rather than economic drivers and specific Key Performance Indicators (KPIs).
Hexxcell Studio's advanced capabilities include:
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Predictive Maintenance:
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Identification of best heat exchanger to clean, when to clean over an extended period of time
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Clean on opportunity: best heat exchanger to clean today or during a short-term unplanned shutdown in order to minimise furnace duty
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Prescriptive Maintenance:
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Evaluation of trade-offs between different cleaning methods (mechanical, chemical, thermal cleaning)
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Condition-based: how long do a cleaning action needs to last, depending on the conditions of the asset (minimise downtime)
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Operations Improvement:
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A detailed analysis of operations and performance of the previous month
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Performance Prediction (thermal and hydraulic) for the overall network over the next few months of operations with Base Case Scenario (current operation plan – e.g. cleaning schedule, flow splits), in particular trends towards hydraulic and thermal limits, and calculation of economics and other KPIs
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Performance Improvement (thermal and hydraulic) for the network over the next few months of operations with an number of Future Scenarios (alternative operation plans – e.g. cleaning schedule, flow splits), in particular trends towards hydraulic and thermal limits, and calculation of economics and other KPIs
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Recommended operation plan for the next months and assessment of the benefits, including optimal operation of flow splits between branches
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Example of Typical Insights and Recommendations
Example of typical recommendations provided to refineries include:
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Clean now E05 to maximise furnace inlet temperature and E09 to minimise pressure drop in the network
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The furnace duty is expected to reach its limit with current operations in two months. Cleaning E06 now would delay it by 1 month. The proposed cleaning schedule will avoid any production losses.
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Year-to-date fouling costs are approaching $1.2 MM and are expected to reach $7.5 MM by the end of the year. They can be reduced by 30% by the proposed cleaning schedule, costing $0.87MM: the estimated ROI is 158% with a payback of 3 months.
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Fouling behaviour in E04 has changed significantly since last week, inorganics carryover from the desalter is possible. Verify the operation of the desalter.
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Pressure drops in E07 are reaching a critical level, vibration issues are possible. A chemical wash on the tube-side could help improving the issue.
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To reduce fouling rates in E03 while maintaining Residuum outlet temperature above 240°C, reduce bypass opening in E05 by 20% if running in turndown next week, change the flow split ratio from 50-50 to 40-60
See also:
Advanced Analytics: Fouling Propensity Analysis™
Advanced analytics to unveil key correlations between operating parameters, crude slates and fouling behaviour
Equipment Design: Dynamic Retrofit Test™
A predictive approach to test performance of a proposed retrofit design