Research On Simulation And Optimization Of Process For Value-added Chemicals Recovery From Waste Photoresist Stripper Based On Dividing-Wall Column

Photoresist stripper is an indispensable kind of functional electronic wet chemicals in manufacturing the traditional TFT-LCDs or those new electronic products.Unfortunately,large quantities of waste organic solvents such as waste photoresist stripper increase sharply with development of technologies.From the viewpoint of the cost-control and environmental issues,value-added component recycling from waste solvents such as waste photoresist stripper is urgent necessary and of great significance by means of some efficient technologies.This paper presents systematic design of a novel separation process for recycling value-added materials from waste photoresist stripper.The contributions are summarized as follows:Firstly,the traditional separation process is simulated in ASPEN PLUS as a base case.In addition,the intensified divided wall column(DWC)separation process is proposed and simulated.The influence of six parameters on the product quality and the energy consumption of the DWC process is briefly analyzed on the basis of steady-state process simulation and the results of sensitivity analysis.Then,the optimal results of these important parameters are determined by the response surface method(RSM).120 groups of tests with 8 factors and 3 levels are designed.Combined with analysis of variance,the significant items of responses are identified.The total annual cost is taken as the objective function,and the optimal value of each parameter is obtained.The comparison of cost and profits is conducted between the traditional separation process and the DWC process.The results indicate that the DWC process is more attractive due to excellent economic index and lower environmental impact.Finally,different control schemes of the DWC process are investigated by singular value decomposition(SVD)method.Besides,4 control schemes for DWC are compared and the best scheme is the cascade control scheme of the composition combining the temperature difference control loop.In this scheme,the measurement of composition is realized by a soft sensor using BP neural network(BPNN).