Author(s)

Guifa Yao ¹

Affiliation(s)

¹ Lingnan Institute of Technology, Guangzhou, 510663, China

Corresponding Author

Guifa Yao

ABSTRACT

The multi‑machine collaborative operation of intelligent manufacturing production lines has put forward new requirements for higher vocational PLC training teaching, requiring a leap from single‑machine control to system integration. At present, higher vocational PLC training platforms are mostly limited to the programming and debugging of a single PLC, lacking training functions for multi‑station collaboration and fault response mechanisms. Oriented to the practical teaching needs of majors such as higher vocational electrical automation technology, this paper proposes a multi‑machine collaborative fault perception and dynamic scheduling response method for intelligent production lines based on a PLC training platform. This method takes a multi‑station PLC network as the hardware foundation and constructs a closed‑loop control logic of "perception—decision—scheduling": it collects status signals of each workstation through distributed I/O and bus networks, uses fault identification logic to determine equipment anomalies and generate scheduling priorities; the master PLC performs task migration and path replanning for faulty workstations based on priority rules, realizing dynamic adjustment of multi‑machine collaborative operations. Verification of this method on a training platform shows that it can effectively support comprehensive training projects such as multi‑machine collaborative scheduling and fault response, and helps improve students' engineering practical ability at the system integration level.

KEYWORDS

PLC training platform; Multi‑machine collaboration; Fault perception; Dynamic scheduling; Higher vocational training

CITE THIS PAPER

Guifa Yao. Research on Multi‑Machine Collaborative Fault Perception and Dynamic Scheduling Response Method for Intelligent Production Lines on Higher Vocational PLC Training Platforms. Advances in Vocational and Technical Education (2026). Vol. 8, No. 2, 101-106. DOI: http://dx.doi.org/10.23977/avte.2026.080213.

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Sponsors, Associates, and Links

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• Advances in Educational Technology and Psychology
  
  
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• Transactions on Comparative Education
  
  
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