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Research on Talent Cultivating Pattern of Industrial Engineering Considering Smart Manufacturing

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  • Xugang Zhang

    (Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
    Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Cui Li

    (Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
    Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Zhigang Jiang

    (Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
    Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

Abstract

In-depth exploration of the theory and technological applications of smart manufacturing (SM) is lacking in the current talent training model for industrial engineering (IE) majors, and there is a lack of practical education for SM environments. This makes it difficult for students of traditional IE majors to adapt to the modern trend of industrial intelligence and meet the needs of market demand and enterprise development. Therefore, how to cultivate IE talents for SM has become an urgent problem for IE majors to solve. To this end, this paper proposes a new “SM+IE” talent training model, aiming to cultivate more high-quality composite application talents. This model is based on the Lean Manufacturing course and analyzes the effect of the training mode of SM. Secondly, we used the topic of “Sorting Efficiency Improvement” to verify the effectiveness of the new talent training model. The materials were divided into three types: large, medium, and small, and the materials were sorted using traditional IE practices and smart manufacturing-oriented practices. Finally, interviews were conducted with the participants, and both teachers and students indicated that the learning effect of this teaching reform practice was significantly better than that of the traditional IE teaching mode. The results show that the new talent training model improved not only the application and practical skills of the IE students, but also their teamwork and leadership skills.

Suggested Citation

  • Xugang Zhang & Cui Li & Zhigang Jiang, 2023. "Research on Talent Cultivating Pattern of Industrial Engineering Considering Smart Manufacturing," Sustainability, MDPI, vol. 15(14), pages 1-28, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11213-:d:1196926
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    References listed on IDEAS

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    1. Xianyin Duan & Kunpeng Zhu & Xingdong Wang & Min Zhou, 2023. "Reform of the Training Program of Intelligent Manufacturing Engineering of Universities in the Steel Industry," Sustainability, MDPI, vol. 15(5), pages 1-12, February.
    2. Shujaat Ali & Wan Seon Shin & Hojun Song, 2022. "Blockchain-Enabled Open Quality System for Smart Manufacturing: Applications and Challenges," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    3. Marek Kliment & Miriam Pekarcikova & Peter Trebuna & Martin Trebuna, 2021. "Application of TestBed 4.0 Technology within the Implementation of Industry 4.0 in Teaching Methods of Industrial Engineering as Well as Industrial Practice," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
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    Cited by:

    1. Feng Xiang & Junjie Cao & Ying Zuo & Xianyin Duan & Liangxi Xie & Min Zhou, 2023. "A Novel Training Path to Promote the Ability of Mechanical Engineering Graduates to Practice and Innovate Using New Information Technologies," Sustainability, MDPI, vol. 16(1), pages 1-20, December.

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