化工学报 ›› 2018, Vol. 69 ›› Issue (11): 4505-4517.DOI: 10.11949/j.issn.0438-1157.20180983

• 综述与专论 • 上一篇    下一篇

面向智能制造的工业结晶研究进展

龚俊波1,2, 孙杰1,2, 王静康1,2   

  1. 1. 化学工程联合国家重点实验室, 天津大学化工学院, 天津 300072;
    2. 天津化学化工协同创新中心, 天津 300072
  • 收稿日期:2018-09-04 修回日期:2018-10-16 出版日期:2018-11-05 发布日期:2018-11-05
  • 通讯作者: 龚俊波
  • 基金资助:

    国家自然科学基金项目(91634117)。

Research progress of industrial crystallization towards intelligent manufacturing

GONG Junbo1,2, SUN Jie1,2, WANG Jingkang1,2   

  1. 1. State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;
    2. Collaborative Innovation Center of Chemical Science and Engineering(Tianjin), Tianjin 300072, China
  • Received:2018-09-04 Revised:2018-10-16 Online:2018-11-05 Published:2018-11-05
  • Supported by:

    supported by the National Natural Science Foundation of China (91634117).

摘要:

工业结晶是一门“半艺术的科学”,具有多目标、非线性和强耦合的特点,在国际上被公认是最难设计的化工单元操作之一。面向智能制造发展的重大战略需求和历史机遇,基于国内外对工业结晶和智能制造的研究现状,拟构建基于智能制造的工业结晶多尺度研究框架。结合相关案例,总结了国内外人工智能、云计算、物联网等核心智能制造技术在工业结晶中的应用,重点分析讨论在溶解度预测、晶型预测、晶习预测、共晶预测与智能制造的发展现状和潜在结合点;总结了结晶过程中的感知、分析、决策的智能控制技术。

关键词: 工业结晶, 溶解性, 晶型, 晶习, 共晶, 预测, 过程控制

Abstract:

Industrial crystallization is a “semi-artistic science” and its process has the characteristics of multi-objective, non-linear and strong coupling. It is well-known by international scholars as one of the most difficult unit operations of chemical engineering to design. On the basis of the domestic and international research progresses on the topic of industrial crystallization and intelligent manufacturing, this review intends to construct a multi-scale research framework of industrial crystallization with intelligent manufacturing technologies to confront with the major strategic demands and historical opportunities of intelligent manufacturing development. The review summarizes the application of core intelligent manufacturing technologies including AI, cloud computing, and internet of things in industrial crystallization with some relevant cases. It will mainly focus on the analysis and discussion of development status and potential integration point of prediction of solubility, polymorphs, crystal habit, and co-crystals with intelligent manufacturing. Some methods for predicting the crystallization conditions of proteins is introduced. Finally, the intelligent control technologies of perception, analysis and decision in crystallization process were reviewed.

Key words: industrial crystallization, solubility, crystal form, crystal habit, co-crystal, prediction, process control

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