Subsystem selection for digital twin development: A case study on an unmanned underwater vehicle

Kutzke, Demetrious T.; Carter, James B.; Hartman, Benjamin T.

doi:10.1016/j.oceaneng.2021.108629

Cited by 28 publications

(9 citation statements)

References 34 publications

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“…For that, Zhang et al [ 56 ] define a set of metrics to analyze how to define the right DT for a system. Similarly, Kutzke et al [ 57 ] propose an approach to evaluate which subsystems and functionalities will be implemented in the DT. It chooses the DT subsystems based on a set of priority metrics for each component.…”

Section: Digital Twin Designmentioning

confidence: 99%

Design, Modeling and Implementation of Digital Twins

Segovia

García-Alfaro

2022

Sensors

133

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A Digital Twin (DT) is a set of computer-generated models that map a physical object into a virtual space. Both physical and virtual elements exchange information to monitor, simulate, predict, diagnose and control the state and behavior of the physical object within the virtual space. DTs supply a system with information and operating status, providing capabilities to create new business models. In this paper, we focus on the construction of DTs. More specifically, we focus on determining (methodologically) how to design, create and connect physical objects with their virtual counterpart. We explore the problem into several phases: from functional requirement selection and architecture planning to integration and verification of the final (digital) models. We address as well how physical components exchange real-time information with DTs, as well as experimental platforms to build DTs (including protocols and standards). We conclude with a discussion and open challenges.

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Section: Digital Twin Designmentioning

confidence: 99%

Design, Modeling and Implementation of Digital Twins

Segovia

García-Alfaro

2022

Sensors

133

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“…Their digital twin is a physicsbased model used to generate training data for the pathplanner; neither data flows nor a model update were implemented. Data flows and model update have not been implemented also in (Kutzke et al, 2021) and (Lambertini et al, 2022): in the former, a graph of the digital twin of an unmanned underwater vehicle is defined where the nodes are sub-models of the whole model; it is unclear whether the authors used a physics-based or statisticsbased modeling approach; in the latter, an underwater drone is designed and built while the digital twin is left as an important future work. To estimate the speed loss of a ship due to marine fouling, Coraddu et al (Coraddu et al, 2019) trained an extreme learning machine (Huang et al, 2006) on real-world data.…”

Section: Resultsmentioning

confidence: 99%

“…3 Ph. system Score (Vasanthan and Nguyen, 2021) Yes (physics) No (none) No Vessel 1 (Coraddu et al, 2019) Yes (statistics) No (P → M → H) No Ship 1.5 (Taskar and Andersen, 2021) Yes (physics) No (P → M → H) No Ship 1.5 (Kutzke et al, 2021) Yes (n.…”

Section: Workmentioning

confidence: 99%

Digital Twins for Marine Operations: A Brief Review on Their Implementation

Zocco¹,

Wang²,

Van³

2023

Preprint

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While the concept of a digital twin to support maritime operations is gaining attention for predictive maintenance, real-time monitoring, control, and overall process optimization, clarity on its implementation is missing in the literature. Therefore, in this review we show how different authors implemented their digital twins, discuss our findings, and finally give insights on future research directions.

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“…This sharp increase in the complexity of ensuring the proper system behavior during the course of production can be successfully achieved only by the extensive use of model-based simulation [14]. These concepts were extended later on to simulations merging physical and virtual worlds in all lifecycle phases in the case of mechatronic systems [15], marine fouling monitoring [16], wind turbines [17], underwater vehicles [18], ship operation in waves [19], and others. Except for simulation, the importance of the digital thread, as a tissue connecting digital twins and physical objects, is stressed in the context of Industry 4.0 [20], while a distinction between digital models, digital shadows, and digital twins is pointed out in [21].…”

Section: Brief Literature Reviewmentioning

confidence: 99%

Towards Digital Twinning of Fabrication Lines in Shipyards

Hadžić

Ložar

Opetuk

et al. 2023

JMSE

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The digital twinning concept stands as a remarkable opportunity to integrate sophisticated mathematical models within the context of existing manufacturing systems. Such models may provide shipyard management with predictive analytics, improving the final results at the strategic, tactical, and operational levels. Therefore, the possibility of integrating the Markovian-framework-based finite-state method into the context of ship production is presented in this study, including its outline, digital thread, and factory-floor data reliance. First, the predictive analytics problem is addressed by the finite-state method in the case of the shipyard’s fabrication line, and the obtained results are validated afterward using a numerical model through discrete-event theory. The predictive analytics indicate an almost ideal balancing of the fabrication line, except for the buffers storing stiffeners before the coat-dying and marking operations. In addition, the improvability analysis of the shipyard’s fabrication lines extended the scope of the predictive analytics using bottleneck identification and affecting the key performance indicators through a digital thread, as well as by improved maintenance strategies.

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Subsystem selection for digital twin development: A case study on an unmanned underwater vehicle

Cited by 28 publications

References 34 publications

Design, Modeling and Implementation of Digital Twins

Design, Modeling and Implementation of Digital Twins

Digital Twins for Marine Operations: A Brief Review on Their Implementation

Towards Digital Twinning of Fabrication Lines in Shipyards

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