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Digital twinning for smart restoration of classic cars
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Orientador(es)
Resumo(s)
Classic cars hold substantial value in the automotive industry, and the restoration process plays a pivotal role in increasing their worth. Ensuring the certification of these restoration processes is vital, as is keeping owners well-informed about the ongoing procedures taking place in their appreciated vehicles. By monitoring and controlling these restoration activities, the management of classic car workshops can effectively optimize their operations, empower owners with pertinent information, and preserve the authentic nature of these vintage automobiles. This study aims to develop a digital twin system for a classic car bodywork restoration shop workshop. The latter integrates multiple sensor technologies, including location tracking, humidity and temperature sensing, accelerometer monitoring, and smart plugs, to facilitate the identification of ongoing activities of classic car bodywork restoration process instances. By leveraging these sensors, the digital twin system may simulate and control workshop operations more effectively. We perform a systematic rapid review of related work and, based on state-of-the-art practices, we identify existing architectures and software applications used for creating digital twin systems. Then, we propose the architecture for our digital twin system, detailing its functionalities. We aim at contributing to advancing digital twin technology in classic car bodywork restoration, enhancing its authenticity, and fostering improved management practices, and overall experience for classic car owners.
Descrição
Funding Information:
This work was produced with the support of INCD funded by FCT and FEDER under the project 01/SAICT/2016 n\u00BA022153.
Publisher Copyright:
© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
Palavras-chave
bodywork restoration classic cars digital transformation digital twin industry 4.0 IoT General Computer Science