Application case of advanced control optimization system for fine chemical equipment in a factory
Category:
Cooperation Case
Case introduction
Zhejiang Bangye Technology adopts multivariable model predictive control technology to design and develop advanced control system for fine chemical equipment. After APC is applied, the automation rate of the device is over 95%, the fluctuation of key process parameters is reduced by more than 50%, the product quality is obviously stable, and the device consumption is Lowering, the labor intensity of the operator is greatly reduced.
Figure 1 shows the effect of the feed control. Since the unit has multiple sets of recovery systems and reactors, it is necessary to ensure a certain ratio of fresh and recycled feed and stable feed pressure. There is a huge safety hazard in the feed pressure out of range, and the deviation of the feed ratio leads to difficulties in subsequent system production. When the operator manually operates, the feed pressure fluctuates greatly, and the feed ratio is difficult to maintain. For this multivariate, the chemical equipment APC with strong coupling correlation will automatically predict the key parameters according to the model, so that the control variables can be adjusted in advance to ensure that the feed pressure and feed ratio remain within the process requirements. In the figure, the red line is the feed pressure, the blue line is the feed ratio, and the dashed line represents the respective process ranges. It can be seen from the figure that after the APC is applied, the feed pressure and the feed ratio are significantly improved.
Figure 2 shows the control effect of APC on the key process parameters of the device during production adjustment. When the output set value (red) changes, the advanced control system automatically adjusts the feed amount (black), keeping the temperature inside the unit (blue) and the pressure (green) basically unchanged in the case of a large change in production. . It shows that in the process of production adjustment, APC can effectively ensure the stability of key process parameters in the device and reduce the defect rate caused by the change of process parameters.
Figure 3 VOA online predictive control process The device APC achieves product quality card edge control based on stable key process parameters, introduces virtual online analyzer (VOA) to predict product quality, VOA provides real-time product quality estimation, combined with model prediction Controller for quality control. VOA uses a credible laboratory test to correct the effects of model deviation and unmeasured interference. Figure 3 shows the flow structure of VOA to achieve online predictive control.
Figure 4 shows the product quality control effect of APC after VOA is put into operation. The factory sets the control target according to the product specifications, and APC will automatically adjust each key process parameter index according to the VOA estimate to ensure product quality. After the application of APC, the actual product quality fluctuations are reduced, the product is over-purified, and the device energy consumption is significantly reduced.
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