IEEE Computational Intelligence Society
Technical Committee on Intelligent Systems and Applications


Task Force on Computational Intelligence for Industrial Process

Purpose

Computational intelligence (CI) can perform jobs human-likely by learning from human experience. In recent years, there are many successful applications of CI technologies, for example, using deep learning to train computers to accomplish specific complicated tasks like Alpha Go. CI technologies such as machine learning, reasoning, computer vision, speech recognition and autonomous operations would have significant impacts for industries. They may make the industrial operations much more efficient and improve resource (including human and material resources) and energy utility, even help economic, environmental, and social sustainability.

Scopes
  1. General CI theory and methods for industrial process.
    1. Symbolic methods for industrial process. The topic aims at on modeling and control of industrial processes with symbolic CI technologies such as decision trees, random forests fuzzy logic , and fuzzy systems logic, etc.
    2. Connection structures for industrial process. The topic consists of studies on supervised, unsupervised, and semi-supervised machine learning methods for industry processes, modifications of deep learning, reinforcement learning, meta-learning and transfer learning for industry.
    3. Probabilistic methods for industrial process. The topic covers Bayesian method and Bayesian networks in process control, Markov chains, stochastic neural networks for process modeling and control.
  2. Particular CI technologies for industrial processes
    1. Process control
    2. Performance monitoring
    3. Robotics
    4. Manufacturing
    5. Human-computer interactions and systems

Activities

We organized the following international conferences:

  1. 1st International Conference on Industrial Computational intelligence on July 23-25, 2019, Shenyang, China.
  2. 2nd International Conference on Industrial Computational intelligence, October 23-25, 2020, Shenyang
  3. 17th International Conference on Electrical Engineering, Computing Science and Automatic Control, November 11-13, 2020, Mexico City, Mexico

We will organize the following international conferences:

  1. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexico City, Mexico
  2. 18th International Conference on Electrical Engineering, Computing Science and Automatic Control, 2021, Mexico City, Mexico
  3. 3rd International Conference on Industrial Computational intelligence, 2021, Shenyang
  4. 1st Workshop on Industrial Artificial Intelligence in Sao Paulo, Brazil, 2021

Chairs

Wen Yu
Departamento de Control Automatico
CINVESTAV-IPN (National Polytechnic Institute)
Mexico City, 07360, Mexico
yuw@ctrl.cinvestav.mx

Jinliang Ding
State Key Laboratory of Synthetical Automation for Process Industry
Northeastern University
Shenyang, China
jlding@mail.neu.edu.cn

Members

Erick de la Rosa
GE Aviation
Queretaro
Mexico
edelarosa@ge.com.mx

Edgar Nelson Sánchez
CINVESTAV
Guadalajala
México

Zhao Liang
University of Sao Paulo
Brazil
zhao@usp.brindong

Xiangjie Liu
North China Electric Power University
China
liuxj@ncepu.edu.cn

Shoulie Xie
Institute for Infocomm Research
Singapore
slxie@i2r.a-star.edu.sg

Kang Li
University of Leeds
UK
K.LI1@leeds.ac.uk

Wen-Fang Xie
Concordia University
Canada
wenfang.xie@concordia.ca

YangQuan Chen
University of California
Merced, USA
ychen53@ucmerced.edu