• Experiment Science and Technology
  • Vol. 22, Issue 1, 37 (2024)
Cuijuan AN1, Kai ZHANG1, Guoxia WANG1, Min ZHANG1, Dawei DING1、*, and Shanlei WU2
Author Affiliations
  • 1School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  • 2LCS Department, Rockwell Automation (China) Co., Ltd., Beijing 100005, China
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    DOI: 10.12179/1672-4550.20230508 Cite this Article
    Cuijuan AN, Kai ZHANG, Guoxia WANG, Min ZHANG, Dawei DING, Shanlei WU. Design of Simulation Training Platform for Automation Production Line Based on PLCSIM Advanced and Simulink[J]. Experiment Science and Technology, 2024, 22(1): 37 Copy Citation Text show less

    Abstract

    In order to solve the problems of hardware equipment, experimental duration, and limited space in the offline course of “Automated Production Line Training”, and improve the teaching quality and effectiveness, a simulation training platform for automated production lines based on PLCSIM Advanced and Simulink is designed. This platform is based on the physical training equipment in the laboratory, and uses Simulink to build a simulation model of the controlled object. Control algorithms are written in the PLCSIM Advanced simulation controller, through API communication the real-time exchange between object model and controller data is achieved and simulated. Taking the paper tension control system as an example, the construction and implementation process of the simulation training platform are introduced. Practical teaching has shown that this platform has improved the teaching effectiveness, stimulated students’ interest in practical learning, improved their ability to discover and solve complex engineering problems, and made students deeply realize the importance of teamwork and effective communication.
    Cuijuan AN, Kai ZHANG, Guoxia WANG, Min ZHANG, Dawei DING, Shanlei WU. Design of Simulation Training Platform for Automation Production Line Based on PLCSIM Advanced and Simulink[J]. Experiment Science and Technology, 2024, 22(1): 37
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