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OptiTwin Data-Driven Machining Process Optimization Platform for SMEs.pdf (1.080Mb)
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Title
OptiTwin: Data-Driven Machining Process Optimization Platform for SMEs
Author
Peralta Abadía, José Joaquín
Larrinaga, Felix
CUESTA ZABALAJAUREGUI, MIKEL
Badiola, Xabier
Duo, Aitor
Olalde Mendia, Gorka
Publication Date
2024
Research Group
Ingeniería del software y sistemas
Mecanizado de alto rendimiento
Version
Postprint
Document type
Conference ObjectConference Object
Language
English
Rights
© 2024 IEEE
Access
Embargoed access
Embargo end date
2026-10-31
URI
https://hdl.handle.net/20.500.11984/6813
Publisher’s version
https://doi.org/10.1109/ETFA61755.2024.10711032
Published at
International Conference on Emerging Technologies and Factory Automation (ETFA)  29. Padova, 10-13 septiembre, 2024
Publisher
IEEE
Keywords
Manufacturing industry
Machining
Machine learning
ODS 8 Trabajo decente y crecimiento económico ... [+]
Manufacturing industry
Machining
Machine learning
ODS 8 Trabajo decente y crecimiento económico
ODS 9 Industria, innovación e infraestructura [-]
Abstract
The manufacturing industry is constantly seeking innovative solutions to optimize machining processes. However, there is a lack of efficient digital platforms that fully meet the flexibility, service ... [+]
The manufacturing industry is constantly seeking innovative solutions to optimize machining processes. However, there is a lack of efficient digital platforms that fully meet the flexibility, service composition, and affordability needs of the manufacturing industry, in particular for small and mediumsized enterprises (SMEs). This paper introduces the OptiTwin platform, a novel data-driven system designed to enhance machining process optimization for SMEs. The OptiTwin platform was developed with a focus on data acquisition, management, and analysis based on data driven models. The functionalities of the platform were validated through a drilling use case at Mondragon University's high-performance machining laboratory, demonstrating its effectiveness in real-time tool condition monitoring. The results showcase the potential of OptiTwin in optimizing machining processes and empowering SMEs with data-driven insights for enhanced productivity and quality assurance. [-]
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  • Conferences - Engineering [435]

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