Exploration of the Industry Demand-Oriented Training Model for Professional Degree Graduate Students in Intelligent Manufacturing
- DOI
- 10.2991/978-2-38476-440-2_156How to use a DOI?
- Keywords
- Intelligent Manufacturing; Professional Degree Graduate Students; Training Model; Teaching Reform
- Abstract
Driven by a new round of industrial revolution, intelligent manufacturing technology and its industry are developing rapidly, which puts forward new requirements for the training mode of professional degree graduate students in manufacturing engineering. This paper constructs a new training mode for professional degree graduate students based on industry demand by analyzing the industry demand and the existing problems in the training mode of professional degree graduate students. It introduces a series of new practices and reform achievements of professional degree graduate student training in mechanical engineering at Wuhan University of Science and Technology, providing a reference for graduate training reform under the background of manufacturing industry upgrading.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xuhui Xia AU - Xiang Liu AU - Lei Wang AU - Zelin Zhang AU - Jianhua Cao AU - Yuyao Guo PY - 2025 DA - 2025/07/10 TI - Exploration of the Industry Demand-Oriented Training Model for Professional Degree Graduate Students in Intelligent Manufacturing BT - Proceedings of the 2025 11th International Conference on Humanities and Social Science Research(ICHSSR 2025) PB - Atlantis Press SP - 1384 EP - 1391 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-440-2_156 DO - 10.2991/978-2-38476-440-2_156 ID - Xia2025 ER -