中文

Journal of Shanghai University（Natural Science Edition） ›› 2019, Vol. 25 ›› Issue (1): 95-100.doi: 10.12066/j.issn.1007-2861.2088

• Research Articles • Previous Articles     Next Articles

Process optimization of fluorinated ethylene propylene product based on the optimal projection recognition method

XU Xiao1, LU Kailiang2, JIANG Ruoning3, ZHAO Hongtao4, LI Junwei4, LU Wencong1,2()   

  1. 1. College of Sciences, Shanghai University, Shanghai 200444, China
    2. Materials Genome Institute of Shanghai University, Shanghai 200444, China
    3. Shanghai Huayi Information Technology Co., Ltd., Shanghai 200025, China
    4. Shanghai 3F New Materials Co., Ltd., Shanghai 200025, China
  • Received:2018-06-28 Online:2019-02-28 Published:2019-02-26
  • Contact: LU Wencong E-mail:wclu@shu.edu.cn

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Abstract:

The process data of production can be utilized to investigate the regularity of production quality by using data mining, which is an effective method in industrial optimization. Furthermore, it is expected that the optimal model can be constructed in a fast and automatic way. In this project, the optimal projection recognition technique was proposed to construct the pattern recognition model for classifying different qualities of fluorinated ethylene propylene (FEP) concerning melt index. It was found that the qualified accuracy of production increased remarkably after the application of the optimal model available.

Key words: fluorinated ethylene propylene, melt index, optimal projection recognition method, process optimization

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