System Optimization
System Optimization
Lummus Digital helps its clients to optimize their target objectives (like profit, yield, production, energy consumption, and product sequencing of a unit/system); while maintaining the utmost controllability of the plant with new set points of optimum variables.
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Real Time Optimizer (RTO)
Advance Process Control (APC)/ AI based MPC
Real Time Optimizer (RTO)
Solution Capability
To maximize profit, yield, and production; or minimize energy consumption by using the first principle and artificial intelligence optimizer.
Value Proposition
- Increases profit
- Improves production and yield
- Reduces energy consumption
- Identifies bottlenecks and lower CAPEX for expansion
Advance Process Control (APC)/ AI based MPC
Solution Capability
To manage complex variable interactions within a process to reduce process variability. The solution allows the plant to run closer to the operating constraints. This helps the plant achieve the optimum objective by implementing small step changes in set points – MPC (focus) on our own/ APC with a partner.
Value Proposition
- Optimizes plant stability
- Increases profit
- Improves production and yield
- Reduces energy consumption
Digitalization Success Story
Optimization to Increase Profit of a Hydrocracker Plant at a Major Refiner in Saudi Arabia
Business Objective
To increase profit of a Hydrocracker at a major, Saudi Arabia refiner.
A major, Saudi Arabia refiner contacted Lummus Digital to explore increasing its hydrocracker profits. The business objectives included:
- Running the plant at optimum profitability
- Expediting the response to changing market conditions by adjusting the unit to produce the optimal product mix. Thus, the yield of the most valuable product is increased
- Enhancing value from the plant, i.e., increasing yields, reducing energy / utilities consumption
Key Solution
- Building a Digital Twin whereby the Hybrid plant model mimics the physical plant behavior with an accuracy of ~98%
- Implementing supervised machine learning, which utilized 1 year of historical operating processes and labdata
- Instituting the Kinetics model for various conversion levels in the data improved the performance of the AI model
- Feeding the AI optimizer with configurable objective functions; required constraints of parameters to perform equipment duties, like increasing diesel yield or increasing unit margin
Business Impacts & Outcomes
Increased profit due to increase in diesel yield: Average = $6 mil/yr
Saved energy/utilities consumption: Average = $1 Mil/yr
Enabled the hydrocracker to respond promptly
Derived more value from the plant, i.e., increased yields and reduced energy/utility consumption
Improved the life of equipment; it also reduced labor and spare parts OPEX
Process Upset/ Shutdown/ Off-spec prediction & detection
Real Time Optimizer (RTO)
Maximize the profit, yield, production or minimize energy consumption using first principle and artificial intelligence optimizer.
Value Proposition
- Increase profit - more from existing
- Improve production and yield
- Reduce energy consumption
- Identify bottleneck – lower CAPEX for expansion
