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Entry-Exit Criteria for the Mechanical Engineering AI Talent Granary Model in the Intelligent Digital Age

Author(s)

Tianjian Liu1, Yawen Fan2, Fang Liu1, Jingfeng Shen1,*

Affiliation(s)

1School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China 2School of Engineering and Computing, The Sino-British College, University of Shanghai for Science and Technology, Shanghai, China *Corresponding Author

Abstract

Addressing the challenges of precision and adaptability in cultivating AI talent for mechanical engineering professionals, this paper utilizes the “AI Talent Granary” model, focusing on its core dynamic mechanism: the “Warehouse Entry and Exit Criteria.” The study innovatively applies the team role model from *Journey to the West* to talent classification, constructing vivid portraits of four distinct AI talent archetypes: the Sun Wukong-type, the Zhu Bajie-type, the Sha Wujing-type, and the Tang Monk-type. Based on these profiles, the system establishes a corresponding criteria framework spanning three phases: For the Warehouse Entry phase, a precision selection model based on role potential is proposed; for the In-Warehouse Development phase, a role-empowered PBL-OKR integrated training model is designed; and for the Warehouse Exit phase, role-value-based multi-certification and intelligent matching criteria are established. Ultimately, this research offers a vivid, profound, and effective strategic framework to address the critical challenges of “inaccurate selection, inadequate development, and ineffective utilization” of AI talent in mechanical engineering disciplines.

Keywords

AI Talent Granary; Warehouse Entry and Exit Criteria; Mechanical Engineering Major; Journey to the West Team Model; Character Profile; PBL; OKR

References

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