Optimizing Manufacturing Efficiency using human-centered design and AI
This study explores the implementation of a new machine, in a ceramic industry’s production process, that detects and categorizes plate defects using artificial vision and machine learning algorithms. Simultaneously, the novel UTAUT-for-Industry framework will be applied to assess worker acceptance of the new machine, aiming to ensure that worker feedback and acceptance are central to the implementation process, while enhancing product quality and production efficiency. This dual approach supports industries in advancing towards Industry 5.0, emphasizing human-centric smart manufacturing systems and promoting human-machine intelligent cooperation
Authors
- Guilherme B. M. Neves
- Nuno Marques (ORCID: https://orcid.org/0009-0003-1714-0763)
- Marco Aurélio de Souza Rodrigues (ORCID: https://orcid.org/0000-0002-9250-4761)
- Diogo Sousa
- Flávia V. Barbosa (ORCID: https://orcid.org/0000-0003-1570-5786)
- Cátia A. Carreira
- Marcelo Cardoso de Sousa (ORCID: https://orcid.org/0009-0006-5870-7828)
- Diana Martins (ORCID: https://orcid.org/0000-0003-4536-2315)
- Teresa Gonçalves (ORCID: https://orcid.org/0000-0002-1323-0249)
- Miguel A. Ferreira (ORCID: https://orcid.org/0000-0003-0537-2703)
Institutions
- Universidade do Porto (PT)
- Atlântica Instituto Universitário (PT)
- Institute of Mechanical Engineering and Industrial Mangement (PT)
Publication Details
- Journal
- Procedia CIRP
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procir.2025.08.024
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00