Digital Twin Driven Requirement Conversion in Smart Customized Design

Gu, Ye; Zhang, Shuyou; Qiu, Lemiao

doi:10.1109/access.2021.3075069

Cited by 12 publications

(5 citation statements)

References 38 publications

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“…This method efficiently solves the problem of data collection when there are inadequate sensors or when there is a failure. Furthermore, the artificial-neural-network-based digital model may mimic virtual twin data to compensate for the lack of real-world data [22].…”

Section: Reliable Data Collectionmentioning

confidence: 99%

A Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications

Wu,

Ji,

et al. 2023

Sensors

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With the rapid development of industrial digitalization and intelligence, there is an urgent need to accurately depict the physical world in digital space, and, in turn, regulate and optimize the behavior of physical entities based on massive data collection and analysis. As a technology that combines virtual space and physical space, digital twin can satisfy all of the above needs, and has attracted widespread attention. Due to the promising application prospects of digital twins, both academia and industry have launched research in this field, and related studies have been conducted from different perspectives. Accordingly, some articles summarizing the existing work have also been published, but they are all from a single perspective, lacking a systematic introduction and summary. Based on this, this paper conducts a comprehensive review of the existing work on digital twins from four perspectives: data, model, network and application, and strives to gain a better understanding of the development of the field from the physical to the virtual and back to the physical. Meanwhile, current research challenges and future directions for the development of digital twins are all discussed.

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Section: Reliable Data Collectionmentioning

confidence: 99%

A Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications

Wu,

Ji,

et al. 2023

Sensors

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“…Undoubtedly, digital twins can be used for design optimization. Gu et al [20] converted requirements to customize engineering design of elevators. Li et al [21] applied digital twins to optimize the energy management strategy for plug-in hybrid electric vehicles (PHEVs) while fusing cyber-physical operational data.…”

Section: Related Workmentioning

confidence: 99%

“…Although Rodríguez et al [26] proposed a co-simulation framework which enables bi-directional connectivity between the inverter and its digital twin, the majority of related research works above focuses on building the digital replica by machine learning [20], [24], optimization [21], [23], simulation [9], [22], [28], or combination of the methods [25]. Considering the research objective, this work focuses on building the digital twin using optimization and simulation.…”

Section: Related Workmentioning

confidence: 99%

Digital Twinning From Vehicle Usage Statistics for Customer-Centric Automotive Systems Engineering

Ling

2023

IEEE Open J. Intell. Transp. Syst.

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Towards customer-centric automotive systems engineering, it is essential to incorporate physical models and vehicle usage behavior into decision support systems (DSSs). Such DSSs tend to apply digital twin concepts, where simulations are parameterized with fine-grained time-series data acquired from customer fleets. However, logging vast amounts of data from customer fleets is costly and raises privacy concerns. Alternatively, these time-series data can be aggregated into vehicle usage statistics. The feasibility of creating digital twins from these vehicle usage statistics and the corresponding DSSs for systems engineering is yet to be established. This paper aims to demonstrate this feasibility by proposing a DSS framework that integrates four key elements of digital twinning: aggregate usage statistics from customer fleets, logging data from testing fleets, physical models for vehicle simulation, and evaluation models to derive decision support metrics. The digital twinning involves a four-step process: pre-processing, profiling, simulation, and post-processing. Based on a real-world fleet of 57110 vehicles and four evaluation metrics, a proof of concept is conducted. Results show that the digital twin covers the evaluation metrics of 99% of the vehicles and reaches an average fleet twinning accuracy of 91.09%, which indicates the feasibility and plausibility of the proposed DSS framework.

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“…They can intuitively perceive the internal operations in machines through immersive VR/AR devices. Examples for application of VR -digital twin integration include remote surgery [22], customised product development [23], manufacturing planning [24] and machining process monitoring [25].…”

Section: Integration Of Virtual Reality and Digital Twinsmentioning

confidence: 99%

A Conceptual Framework for Construction Safety Training using Dynamic Virtual Reality Games and Digital Twins

Harichandran¹,

Johansen²,

Jacobsen³

et al. 2021

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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The construction industry is suffering from a high rate of accidents that significantly affect the overall performance of projects. Compared to the conventional safety training methods, Virtual Reality (VR) games offer a more immersive and interactive learning experience for the participants. However, training scenarios in most of the existing VR games lack complex tasks and the realistic environment required for actual construction. This work proposes a conceptual framework for dynamically updating VR training games through information streaming from the digital twins. The training scenarios in VR games are automatically created from the project intent information, project status knowledge, safety regulations, and historical knowledge provided by the digital twins. Therefore, construction workers can be trained in realistic training environments with relevant tasks they soon afterwards pursue. Dynamic VR training is expected mutually beneficial for enhanced digital twins and periodic construction safety management. Inadequate technology readiness level of the construction industry and difficulty in collecting good quality data are some of the major challenges for implementing this framework.

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Digital Twin Driven Requirement Conversion in Smart Customized Design

Cited by 12 publications

References 38 publications

A Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications

A Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications

Digital Twinning From Vehicle Usage Statistics for Customer-Centric Automotive Systems Engineering

A Conceptual Framework for Construction Safety Training using Dynamic Virtual Reality Games and Digital Twins

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