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Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems.
Leng, Jiewu; Zhou, Man; Xiao, Yuxuan; Zhang, Hu; Liu, Qiang; Shen, Weiming; Su, Qianyi; Li, Longzhang.
  • Leng J; Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou, 510006, China.
  • Zhou M; Department of Information Systems, City University of Hong Kong, 999077, Hong Kong, China.
  • Xiao Y; Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou, 510006, China.
  • Zhang H; Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou, 510006, China.
  • Liu Q; Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou, 510006, China.
  • Shen W; Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou, 510006, China.
  • Su Q; State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
  • Li L; Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System, State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou, 510006, China.
J Clean Prod ; 306: 127278, 2021 07 15.
Artículo en Inglés | MEDLINE | ID: covidwho-1201410
ABSTRACT
The COVID-19 has become a global pandemic that dramatically impacted human lives and economic activities. Due to the high risk of getting affected in high-density population areas and the implementation of national emergency measures under the COVID-19 pandemic, both travel and transportation among cities become difficult for engineers and equipment. Consequently, the costly physical commissioning of a new manufacturing system is greatly hindered. As an emerging technology, digital twins can achieve semi-physical simulation to avoid the vast cost of physical commissioning of the manufacturing system. Therefore, this paper proposes a digital twins-based remote semi-physical commissioning (DT-RSPC) approach for open architecture flow-type smart manufacturing systems. A digital twin system is developed to enable the remote semi-physical commissioning. The proposed approach is validated through a case study of digital twins-based remote semi-physical commissioning of a smartphone assembly line. The results showed that combining the open architecture design paradigm with the proposed digital twins-based approach makes the commissioning of a new flow-type smart manufacturing system more sustainable.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio pronóstico Idioma: Inglés Revista: J Clean Prod Año: 2021 Tipo del documento: Artículo País de afiliación: J.jclepro.2021.127278

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio pronóstico Idioma: Inglés Revista: J Clean Prod Año: 2021 Tipo del documento: Artículo País de afiliación: J.jclepro.2021.127278