Application of integrated process and control system model for simulation and improvement of an operating technology
Systematic methods and tools for managing the complexity
Process Simulation & Optimization - II (T4-9b)
Keywords: intergrated model, process simulation, polymerization plant
According to costumers’ expectations and market challenge, chemical industry of the immediate future needs to have the ability to operate complex, highly interconnected plants that are profitable and that meet quality, safety, environmental and other standards. Towards this goal, process modeling, simulation and optimization tools are increasingly being used industrially. Leading chemical product companies, like DuPont and Dow Chemical Co., stand for life-cycle modeling, where an overall model is applied at every level of a plant, i.e. “the model integrates the whole organization”. For all that purpose, it has been shown that models of a process and its control system should be considered as a whole integrated entity. Contrary to the fact that this approach is fulfilled during design phase of a technology, integrated application for simulation is unnoticed during continuous process analysis and improvement, either the process model or its control system model is highly degraded for simplified analysis hence it results in particular solutions.
Our methodology proposes statistical data mining tools based on process data and model-based techniques for optimization of an operating, multi-product polymerization plant. The model-based part of the methodology proposes an integrated process and control system model, which can be applied as a dynamic simulator of the plant. This model was achieved by hybrid modelling technique: where first principle models were not available because of confidentiality or unavailability, black box models were applied, which parameters were identified based on a process data warehouse generated from industrial data. Process model and its advanced process control model are connected by the main control loops, where neural network was also applied to copy control logic.
The dynamic process simulator was realized in MATLAB Simulink environment to get it flexible, expandable and easily restructurable, it communicates through a GUI with the user with purposes of analysis of system performance and process optimization: a product quality sensitivity function was achieved with respect to the main process variables, product changing strategies were analyzed but the simulator has the potential to develop new bias points and products, to adjudicate operators’ work or to make any experiment on the system without being under any obligation of cost. In this sense, our tool is very useful not only for operator training systems (OTS) or decision support systems (DSS), but for product/process development as well because of its structural variability.
The aim of this work is to present the effective usability of such a dynamic simulator of an operating plant and to emphasize how intergrated modeling and simulation can improve system performance. Our case study deals with the application of the simulator as an online product quality estimator.
See the full pdf manuscript of the abstract.
Presented Tuesday 18, 09:45 to 10:05, in session Process Simulation & Optimization - II (T4-9b).
