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Towards a hybrid twin model to obtain the formability of a car body part in real time
Title: | Towards a hybrid twin model to obtain the formability of a car body part in real time |
Authors : | Peinado Asensi, Iván Montés Sánchez, Nicolás García Magraner, Eduardo Andrés Falcó Montesinos, Antonio |
Keywords: | Industria del automóvil - Producción.; Automóviles - Fabricación - Teledetección.; Automóviles - Producción.; Automobiles - Production.; Automobile industry and trade - Production.; Industria del automóvil - Automatización.; Automobile industry and trade - Automation.; Automobiles - Manufacturing - Remote sensing. |
Publisher: | Trans Tech. |
Citation: | Peinado Asensi, I., Montés, N., García, E. & Falcó, A. (2022). Towards a hybrid twin model to obtain the formability of a car body part in real time. Key Engineering Materials, vol. 926 (22 jul. 2022), pp. 2277-2284. DOI: https://doi.org/10.4028/p-1v1o17 |
Abstract: | In recent days there are many possibilities in develop solutions for industrial manufacturing process thanks to the emerging technology based in Industry 4.0, where one can measure and manage data from an industrial process in real time been able to know more information than ever before from the process. But still having challenges in complex process where monitoring data and give a solution is less intuitive, mostly due to a complex physical definition of the process and manufacturing car body parts in automotive is a clear example. In deep drawing process is common to have variations in the process parameters and they can carry out bad manufactured parts. The cycle time, the robust process and the complex physics in the process are the main problems to obtain feasible information from the process. In the following it is proposed a new methodology to have full knowledge of the process applying the so-called method Hybrid Twin. |
Description: | Este artículo se encuentra disponible en la siguiente URL: https://www.scientific.net/KEM.926.2277 |
URI: | http://hdl.handle.net/10637/14313 |
Rights : | http://creativecommons.org/licenses/by/4.0/deed.es |
ISSN: | 1013-9826. 1662-9795 (Electrónico) |
Language: | es |
Issue Date: | 22-Jul-2022 |
Center : | Universidad Cardenal Herrera-CEU |
Appears in Collections: | Dpto. Matemáticas, Física y Ciencias Tecnológicas |
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