Research on Talent Cultivating Pattern of Industrial Engineering Considering Smart Manufacturing

Author:

Zhang Xugang12ORCID,Li Cui12,Jiang Zhigang12ORCID

Affiliation:

1. Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China

2. 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.

Funder

Hubei Provincial Teaching Research Project

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference32 articles.

1. Industrial Engineering and Lean Management for Smart Manufacturing;Qi;J. China Mech. Eng.,2022

2. Research on the Innovation of Chinese Industrial Engineering in the New Development Stage;Li;J. Mechatron. Eng. Technol.,2021

3. Industrial Engineering and Lean Management for Intelligent Manufacturing;Liu;J. Eng. Adv.,2023

4. Augmented reality in support of intelligent manufacturing—A systematic literature review;Egger;Comput. Ind. Eng.,2019

5. Xu, J., Kovatsch, M., Mattern, D., Mazza, F., Harasic, M., Paschke, A., and Lucia, S. (2022). A Review on AI for Smart Manufacturing: Deep Learning Challenges and Solutions. Appl. Sci., 12.

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