(347f) Using Dynamic Simulation to Drive Process Design, Control, and Optimization | AIChE

(347f) Using Dynamic Simulation to Drive Process Design, Control, and Optimization

Authors 

Wiley, L. - Presenter, SimSci by Schneider Electric

While most industrial operations are dynamic in nature, many in the process industries fail to see the value in creating such models. Engineering may create a rigorous, but static, engineering model to design, configure, and size (a) unit operation(s), or an entire process. They may even choose to enhance the model by running elementary safety and controllability studies, incorporating costing, and executing performance analyses. Separately, to serve its purpose, Operations may create low to medium fidelity models for controlling and optimizing the plant.

Dynamic simulation fills the gap between the two. It serves as the basis for validating the process designs, testing safety and control systems testing, and optimizing capital expenditure by avoiding costly over design. The use of this dynamic model can extend into other groups within the organization. Once Engineering has validated the designs, they can pass them off to Maintenance to conduct startup commissioning, operator training, and safely operate the facility. The same dynamic models can be used by Production to perform real-time optimization, in conjunction with advanced process control. This allows both operators and management to optimize the operating parameters while adhering to feed, safety, and environmental constraints.

This paper will present new simulation, training, and optimization technologies (based on a common dynamic simulation) that when coupled together are able to easily validate a design, quickly and effectively train operators, as well as, run tightly controlled optimized operations safely, profitably, and in compliance with regulations. Several customer applications will show the value and success of this implementation.

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