Digital twin-based smart production management and control framework for the complex product assembly shop-floor

By Cunbo Zhuang, Jianhua Liu, Hui Xiong. The International Journal of Advanced Manufacturing Technology, 2018

562 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/fcafd81c24526abb9dd3e537c013cb765f5772e8

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In Industrial and Manufacturing Engineering

Citations in the corpus

A Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning (2019, background): “[18] primarily introduced the key technologies in digital twin based shop-floor, and presented a digital twin and big data driven production management and control platform.”
Characterising the Digital Twin: A systematic literature review (2020, methodology): “5 Fidelity [33] [80] [108] [24] [85] [8] [56] [88] [68] [112] [99] [78] [32] [111] [36] [7] [71] [63] [61] [73] [20] [67] [6] [4] [48] [55] [95] [16] [92] [98] [87] [9] [66] [110] [18] [89] [12]”
Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues (2020, methodology): “[55] Satellite assembly system CAD model + Behavior model + Rule model Smart production management and control”
From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry (2021, unknown): “…Twin originated from the aerospace field (Shafto et al. 2010), and then expanded to industrial manufacturing (Negri et al. 2017, Kritzinger et al. 2018, Zhuang et al. 2018, Tchana et al. 2019, Zhang et al. 2019), has attracted increasing attention in the built environment domain in recent years.”
The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities (2021, background): “there exist some digital twins that are mirrors of processes in the physical world, such as digital twins of a mobile-edge computing (MEC) system [22], human protein–protein interaction (PPI) [23], supply chain [24], components-assembly at a manufacturing unit, and job scheduling [25].”
Digital twin paradigm: A systematic literature review (2021, methodology): “29 (Zhuang et al., 2018) “a dynamic model in the virtual world that is fully consistent with its corresponding physical entity in the real world and can simulate its physical counterpart’s characteristics, behaviour, life, and performance in a timely fashion.””
Impacts of Industry 4.0 technologies on Lean principles (2019, background): “…in simulations (e.g. Block, Lins, and Kuhlenkötter 2018; Heger, Grundstein, and Freitag 2017; Ismail, Wang, and Poolton 2015; Kück et al. 2016; Leitão, Colombo, and Karnouskos 2016; Mousavi and Siervo 2017; Rüßmann et al. 2015; Saez et al. 2015; Snyman and Bekker 2017; Zhuang, Liu, and Xiong 2018).”