Special Session Ⅹ

 

Intelligent Monitoring and Collaborative Optimization for Complex Processes  (Submission Deadline: July 31, 2026)
复杂过程智能监测与协同优化

 

Chair:	Co-chair:
Le Zhou Zhejiang University of Science and Technology, China	Yuan Yao National Tsing Hua University, China
Keywords:
·  Intelligent Process Monitoring (智能过程监测) ·  Collaborative Parameter Optimization (协同参数优化) ·  Complex Process Modeling (复杂过程建模) ·  Data-Knowledge Dual-Driven Modeling  (数据-知识融合建模)
Topics:
·  Data-Knowledge Dual-Driven Complex Process Modeling (数据-知识双驱动的复杂过程建模)  ·  Intelligent Monitoring of Complex Processes (复杂过程的智能监测) ·  Big Data Analytics for Industrial Processes (工业过程大数据分析) ·  Collaborative Parameter Optimization for Complex Processes (复杂过程的参数协同优化) ·  Data-Driven Deep Mining of Industrial Process Information (数据驱动的工业过程信息深度挖掘) ·  Root Cause Analysis for Complex Manufacturing Processes (面向复杂制造过程的异常溯源分析)
Summary:
·  This session focuses on the challenges of intelligent monitoring and collaborative optimization in the operation of complex industrial processes. Given the complexities of process mechanisms, strong multivariable coupling, and dynamically changing operating conditions, integrating mechanistic knowledge with operational data to achieve accurate monitoring and efficient optimization is key to ensuring system safety and improving operational efficiency. The session aims to explore cutting-edge approaches such as data-knowledge fusion modeling, intelligent process monitoring, and collaborative parameter optimization, building an integrated technology system of “perception-analysis-decision-making”. This session will offer new insights into the intellectualization of complex industrial processes and promote the deep integration of theory and practice.
·  本专题聚焦于复杂工业过程运行中的智能监测与协同优化难题。面对过程机理复杂、多变量强耦合及工况动态多变等挑战，如何融合机理知识与运行数据实现精准监测与高效优化，是保障系统安全、提升运行效率与生产质量的关键。专题旨在探讨数据-知识融合建模、智能过程监测及协同参数优化等前沿方法，构建“感知-分析-决策”一体化的技术体系。该专题将为复杂工业过程智能化提供新思路，推动理论与实践的深度融合。