Research progress of industrial crystallization towards intelligent manufacturing

GONG Junbo; SUN Jie; WANG Jingkang

doi:10.11949/j.issn.0438-1157.20180983

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Research progress of industrial crystallization towards intelligent manufacturing

更新时间：2025-12-10

- Research progress of industrial crystallization towards intelligent manufacturing
- CIESC Journal Issue 11, Pages: 4505-4517(2018)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20180983
  CLC： 799
- Online First：05 November 2018，
  
  Published：05 November 2018
- 稿件说明：
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GONG Junbo, SUN Jie, WANG Jingkang. Research progress of industrial crystallization towards intelligent manufacturing[J]. CIESC Journal, 2018, (11): 4505-4517.
DOI：

GONG Junbo, SUN Jie, WANG Jingkang. Research progress of industrial crystallization towards intelligent manufacturing[J]. CIESC Journal, 2018, (11): 4505-4517. DOI： 10.11949/j.issn.0438-1157.20180983.

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。

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.

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