TY - GEN
T1 - AI Applications in the Configuration and Calibration of Industrial Machines
AU - Calado, Jorge S.
AU - Ferreira, Jose
AU - Mendonca, Joao Pedro
AU - Jardim-Goncalves, Ricardo
N1 - Funding Information:
The research leading to this paper received funding from the European Union Horizon Europe Program Under Grant Agreement No. 101057294 (AIDEAS AI-Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability and Resilience) and No. 101092043 (Agile- Hand Smart Grading, Handling and Packaging Solutions for Soft and Deformable Products in Agile and Reconfigurable Lines).
Publisher Copyright:
© 2024 IEEE.
PY - 2024/12/18
Y1 - 2024/12/18
N2 - The development and integration of Artificial Intelligence (AI) applications for Industrial Machines (IMs) has been increasing, transforming manual operational processes into semi- or fully automated ones. Time-consuming and specialized tasks can now be assisted by intelligent systems that support or replace machine operators, with the potential of improving efficiency and lowering costs. Establishing a standardized procedure for configuring and calibrating new IMs proves challenging due to the inherent divergences among manufacturers, client-specific requirements and adaptations, and the distinctive characteristics of various application fields. This paper presents an overview of the emerging applications of AI applications for 1M calibration and configuration processes, highlighting the transformative impact of AI on enhancing operational efficiency, reducing downtime, and improving overall performance in industrial settings compared to traditional approaches to machine setup and optimization. This work is being developed in the AIDEAS project, where it will be implemented in a pilot with Computer Numerical Control (CNC) IMs.
AB - The development and integration of Artificial Intelligence (AI) applications for Industrial Machines (IMs) has been increasing, transforming manual operational processes into semi- or fully automated ones. Time-consuming and specialized tasks can now be assisted by intelligent systems that support or replace machine operators, with the potential of improving efficiency and lowering costs. Establishing a standardized procedure for configuring and calibrating new IMs proves challenging due to the inherent divergences among manufacturers, client-specific requirements and adaptations, and the distinctive characteristics of various application fields. This paper presents an overview of the emerging applications of AI applications for 1M calibration and configuration processes, highlighting the transformative impact of AI on enhancing operational efficiency, reducing downtime, and improving overall performance in industrial settings compared to traditional approaches to machine setup and optimization. This work is being developed in the AIDEAS project, where it will be implemented in a pilot with Computer Numerical Control (CNC) IMs.
KW - Artificial Intelligence
KW - Industrial Machines
KW - Industry 5.0
KW - Machine Calibration
KW - Machine Configuration
KW - Smart Manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85216421440&partnerID=8YFLogxK
U2 - 10.1109/ICE/ITMC61926.2024.10794282
DO - 10.1109/ICE/ITMC61926.2024.10794282
M3 - Conference contribution
AN - SCOPUS:85216421440
T3 - Proceedings of the 30th ICE IEEE/ITMC Conference on Engineering, Technology, and Innovation: Digital Transformation on Engineering, Technology and Innovation, ICE 2024
BT - Proceedings of the 30th ICE IEEE/ITMC Conference on Engineering, Technology, and Innovation
PB - Institute of Electrical and Electronics Engineers (IEEE)
T2 - 30th ICE IEEE/ITMC Conference on Engineering, Technology, and Innovation, ICE/ITMC 2024
Y2 - 24 June 2024 through 28 June 2024
ER -