基于数据挖掘和因子试验设计的聚丙烯装置生产优化

A polypropylene unit production optimization based on data mining and full factorial design

在将工艺参数优化技术用于优化某聚丙烯装置的温度、压力和反应时间等过程参数,使装置生产运行趋于平稳的基础上,采用23全因子试验设计对装置生产中的催化剂TiCl4、活化剂(C2H5)3Al和助催化剂CMMS的用量开展设计实验,通过对实验结果分析得出优化的催化剂、活化剂及助催化剂配料方案为TiCl4:(C2H5)3Al:CMMS=95g:0.9L:200g。以此配料方案进行生产试验,试验结果聚丙烯釜产量均值为3119.50kg,较试验对照期釜产量均值3033.75kg增加85.75kg,增幅达2.83%。

After optimizing a production process of polypropylene device parameters by data mining technology, the unit has operated stabilization. Then the 23 full factorial design is used to choice the amount of catalyst and auxiliaries such as TiCh, （C2Hs）3AI and CMMS. Through analyzing the experimental results, the best catalyst and auxiliaries ingredients scheme is 95 g TiCh：0.9 L （C2Hs）3Al： 200g CMMS. To verify the optimization of the ingredients scheme, the experimental results show that the average of the polypropylene reactor yield has reached 3119.5 kg per reactor higher than the test period 263 reactors average production（3033.75 kg/reactor） 85.75 kg, the growth of about 2.83%.