TY - JOUR
T1 - Integration of AI Use Cases in Training to Support Industry 4.0
AU - Nazarenko, Artem A.
AU - Zamiri, Majid
AU - Sarraipa, Joao
AU - Figueiras, Paulo
AU - Jardim-Goncalves, Ricardo
AU - Moalla, Néjib
N1 - info:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F00066%2F2020/PT#
Funding information:
This study was developed in the Center of Technology and Systems (CTS-UNINOVA) with direct funding from the BASE Funding of the Research Unit of CTS, ref. No. UIDB/00066/2020 and by the ERASMUS + programmes from European Commission under the following projects: “ED-EN HUB—Education and Enterprise HUB—Space of Collective Intelligence” under grant agreement No. 20201-FR01-KA202-080231; “ENHANCE—strENgtHening skills and training expertise for TunisiAN and MorroCan transition to industry 4.0 Era”, under grant agreement No. 619130-EPP-1-2020-1-FR-EPPKA2-CBHE-JP. And it was also supported by the project “AIDEAS—AI Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability, and Resilience” funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No. 101057294.
Publisher Copyright:
© 2024 by the authors.
PY - 2024/3/26
Y1 - 2024/3/26
N2 - As the demand for Artificial Intelligence (AI) continues to grow across industries, there is a need for effective training programs that support the successful deployment of AI in various organizational contexts. This study aims to bring attention to the importance of training programs in preparing industry professionals for AI implementation and highlights key considerations for designing effective training initiatives. It identifies the needs of the industry, hands-on learning experiences, and continuous skill development to ensure the optimal utilization of AI technologies in the context of Industry 4.0. In line with the objective of this work and with the support of an EU project and an associated Digital Innovation Hub (DIH), three comprehensive training programs in Maintenance, Production, and Quality are being developed. Industries can benefit from these training programs, which foster a workforce that is equipped with the necessary knowledge, skills, and awareness to enhance the implementation of Industry 4.0-related technologies and concepts, including AI and supportive technologies. The paper is terminated with concluding remarks and briefly looks into possible future work.
AB - As the demand for Artificial Intelligence (AI) continues to grow across industries, there is a need for effective training programs that support the successful deployment of AI in various organizational contexts. This study aims to bring attention to the importance of training programs in preparing industry professionals for AI implementation and highlights key considerations for designing effective training initiatives. It identifies the needs of the industry, hands-on learning experiences, and continuous skill development to ensure the optimal utilization of AI technologies in the context of Industry 4.0. In line with the objective of this work and with the support of an EU project and an associated Digital Innovation Hub (DIH), three comprehensive training programs in Maintenance, Production, and Quality are being developed. Industries can benefit from these training programs, which foster a workforce that is equipped with the necessary knowledge, skills, and awareness to enhance the implementation of Industry 4.0-related technologies and concepts, including AI and supportive technologies. The paper is terminated with concluding remarks and briefly looks into possible future work.
KW - Artificial Intelligence (AI)
KW - Digital Innovation Hub (DIH)
KW - Industry 4.0
KW - machine learning
KW - training program
UR - http://www.scopus.com/inward/record.url?scp=85205267998&partnerID=8YFLogxK
U2 - 10.12720/jait.15.3.397-406
DO - 10.12720/jait.15.3.397-406
M3 - Article
AN - SCOPUS:85205267998
SN - 1798-2340
VL - 15
SP - 397
EP - 406
JO - Journal of Advances in Information Technology
JF - Journal of Advances in Information Technology
IS - 3
M1 - 8
ER -