An assembly precision analysis method based on a general part digital twin model

Wang, Ke; Liu, Daxin; Liu, Zhenyu; Wang, Qide; Tan, Jianrong

doi:10.1016/j.rcim.2020.102089

Cited by 48 publications

(11 citation statements)

References 37 publications

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“…A dedicated research by Detzner and Eigner (2021) evaluated different methods and suggested an optimal one for feature selection in root-cause analysis. Other works with similar direction include improving assembly process quality management supported by learning algorithm (Franciosa et al, 2020), and process dynamic optimisation (Wang et al, 2021). At the same time, general framework for DT-based assembly process planning and dynamic evaluation method was also proposed .…”

Section: Cluster 9: Dt In Product Assembly Processmentioning

confidence: 99%

Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review

Nguyen

Duong

Nguyen

et al. 2022

International Journal of Production Economics

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Section: Cluster 9: Dt In Product Assembly Processmentioning

confidence: 99%

Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review

Nguyen

Duong

Nguyen

et al. 2022

International Journal of Production Economics

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“…From the perspective of the entire life cycle of public opinion, PODT serves diferent manners during four different periods-emergence and formation, growth and spread, stabilization and climax, and decline and ebb [11,12].…”

Section: Why Digital Twin Of Public Opinion?mentioning

confidence: 99%

Towards Public Opinion Digital Twin: A Conceptual Prototype

Feng

et al. 2022

Scientific Programming

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This paper proposes a novel modeling concept, the “public opinion digital twin,” for public opinion analysis. The public opinion digital twin can be regarded as an experimental sandbox for social science. By digitalizing public data acquired from cyberspace into digital models, the modeling enables practical simulation, data analytics, scenario reflection, and decision support in a digital space with fine controllability, so that all possible evolutions of the research target can be analyzed. By simply inputting or filtering variables, any number of future scenarios are simulated, the effect models of each strategy for coping with public opinion are presented, and the optimized solution can be derived from continuous deep learning. If a robust digital twin is established and the required digital replicas are constantly updated, the system can perform risk assessments and trend predictions for social events. In this case, public opinion information can provide intelligent decision support for governments or enterprises and significantly facilitate social loss aversion, which will greatly advance the revolution in production, dissemination, and guidance.

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“…Wang K et al [32] proposed an assembly accuracy analysis method based on universal parts digital twin model, which can effectively identify the effects of manufacturing errors and assembly process errors on assembly accuracy. Dai S et al [33] proposed an information modeling method for the digital twin model of prefabricated parts to ensure the reusability of manufacturing data.…”

Section: Introductionmentioning

confidence: 99%

Digital twin–based dynamic prediction and simulation model of carbon efficiency in gear hobbing process

et al. 2023

Int J Adv Manuf Technol

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The transformation of manufacturing industry to green manufacturing is one of the important tasks to achieve the carbon peaking and carbon neutrality goals, which needs to improve the use efficiency of unit carbon emission.Aiming at the defect of static model in predicting accuracy and reflecting real-time machining state, a dynamic prediction and simulation model of carbon efficiency in hobbing process based on digital twin is proposed. After analyzing the dynamic characteristics of carbon emission during hobbing, three carbon efficiency targets are defined.Then a dynamic prediction and simulation model is constructed based on convolutional neural network and dynamic discrete event system specification. The framework of the carbon efficiency digital twin (CEDT) of the hobbing process is built, and the dynamic prediction and simulation models are integrated into CEDT as virtual models.Finally, the model is applied to a case study to verify the effectiveness of the method, and the influence of dynamic parameters is discussed. This model can realize the dynamic analysis of carbon emission in hobbing process, provide support for the real-time dynamic optimization of carbon efficiency in hobbing process, and help enterprises to realize green manufacturing.

show abstract

An assembly precision analysis method based on a general part digital twin model

Cited by 48 publications

References 37 publications

Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review

Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review

Towards Public Opinion Digital Twin: A Conceptual Prototype

Digital twin–based dynamic prediction and simulation model of carbon efficiency in gear hobbing process

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