Pedagogy 4.0: Employability Skills and Computer Aided Design (CAD) Education for Industry 4.0

Abstract

The fourth industrial revolution, termed Industry 4.0, is characterised by an exponential transformation rate. As a result, workforces and companies must adapt to rapid changes, which prompted the development of new approaches to higher education, such as Education 4.0. However, despite its importance in enabling Industry 4.0 and related technologies, such as additive manufacturing and smart manufacturing, computer-aided design (CAD), computer-aided manufacturing (CAM), and computer-aided engineering (CAE) education has not undergone responsive changes to its delivery. Consequently, this study aims to support Industry 4.0 by identifying the necessary employability skills and enhancing CAD, CAM, and CAE education. This paper shows (i) the crucial role of higher education in equipping future engineers with the skills for Industry 4.0; (ii) the current state-of-the-art in computer-aided design; and (iii) proposes a novel adaptive approach to computer-aided design, manufacturing, and engineering. Indeed, the results reveal that the most effective teaching method evolves with the learner's ability. As such, the proposed Pedagogy 4.0 empowers students to adapt their learning experience. These findings provide novel insights into engineering education and may contribute to developing the next generation of engineers for Industry 4.0.

Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > Engineering for Health
College of Engineering & Physical Sciences > Smart and Sustainable Manufacturing
Aston University (General)
Additional Information: © 2023 The Authors
Event Title: 2023 28th International Conference on Automation and Computing (ICAC)
Event Type: Other
Event Dates: 2023-08-30 - 2023-09-01
Last Modified: 29 Oct 2024 16:56
Date Deposited: 13 Sep 2023 12:13
Full Text Link: https://www.res ... for_Industry_40
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PURE Output Type: Conference contribution
Published Date: 2023-08-30
Authors: Boyd, Liam
Lu, Yang
Souppez, Jean-Baptiste R. G. (ORCID Profile 0000-0003-0217-5819)

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