Digital Twin Applications : A first systemization of their dimensions

Uhlenkamp, Jan-Frederik; Hribernik, Karl; Wellsandt, Stefan; Thoben, Klaus‐Dieter

doi:10.1109/ice.2019.8792579

Cited by 55 publications

(45 citation statements)

References 25 publications

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“…The more features are considered in a Digital Twin application, the closer it gets to representing its physical entity in its entirety. In other models, this is referred to as authenticity [86] or completeness [51].…”

Section: Discussionmentioning

confidence: 99%

“…Chakshu et al (2019) [98] refer to this aspect as semiactive Digital Twin. The communication dimension is referred to in other models as data acquisition [87], data integration level [86], connection [51], timing [8], or connectivity modes and update frequency [49]. The scope of the virtual entity is also described as Digital model richness, Simulation capabilities, and CPS intelligence [49], purpose [51], data processing [87], application level [8], and is considered in many of the Digital Twin terms in the level of sophistication or maturity.…”

Section: Discussionmentioning

confidence: 99%

“…We have separated this aspect from the scope of the virtual entity to evoke the explicit mentioning of the concrete user-specific value. Aspects of this are considered in the dimensions human interaction [49] and goals and user focus [86] used by other models.…”

Section: Discussionmentioning

confidence: 99%

“…The dimension product life cycle phase [49], [83], [86] is strongly related to the product domain and does not allow the application to a living being, for example, as also stated by Minerva et al (2020) [11], which is why it does not find explicit mentioning in our model. Nevertheless, any Digital Twin application within the product life cycle can be described with our model.…”

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

5-Dimension Cross-Industry Digital Twin Applications Model and Analysis of Digital Twin Classification Terms and Models

Newrzella¹,

Franklin

Haider

2021

IEEE Access

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A Digital Twin is an auspicious cross-industry concept in the era of digitalization, which promises a wide range of benefits such as efficiency improvements, predictions of future opportunities and challenges, and respective recommendations. At present, a variety of definitions and terms exist, causing increasing confusion among practitioners and users. Here we address this need for consolidation with a holistic view of the Digital Twin concept across industries. We analyze classification models and Digital Twin terms in academia and industry in order to propose a 5-dimension cross-industry Digital Twin applications model. This model, based on the core three-part Digital Twin concept introduced by Grieves in 2002, enables ease of understanding and cross-industry classification and development of applications within the concept of the Digital Twin. The proposed model consists of the dimensions scope of the physical entity, feature(s) of the physical entity, form of communication, scope of the virtual entity, and user-specific outcome/value created.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

5-Dimension Cross-Industry Digital Twin Applications Model and Analysis of Digital Twin Classification Terms and Models

Newrzella¹,

Franklin

Haider

2021

IEEE Access

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“…Fig. 1 expands these components to six dimensions, based on Uhlenkamp et al [8][9][10]. These identified dimensions are derived from frequent occurring application areas.…”

Section: The Digital Twin In Life Cycle Environmentmentioning

confidence: 99%

A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation

Passath

Huber

Biedermann

et al. 2021

Teh. glas. (Online)

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The digitalisation of the value chain promotes sophisticated virtual product models known as digital twins (DT) in all asset-life-cycle (ALC) phases. These models. however, fail on representing the entire phases of asset-life-cycle (ALC), and do not allow continuous life-cycle-costing (LCC). Hence, energy efficiency and resource optimisation across the entire circular value chain is neglected. This paper demonstrates how ALC optimisation can be achieved by incorporating all product life-cycle phases through the use of a RAMS²-toolbox and the generation of a knowledge-based DT. The benefits of the developed model are demonstrated in a simulation, considering RAMS2 (Reliability, Availability, Maintainability, Safety and Sustainability) and the linking of heterogeneous data, with the help of a dynamic Bayesian network (DBN).

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A Complete Digital Chain to Enable the Digital Twin of a Shop Floor

Noël¹,

Alpan²,

Mangione³

2020

Product Lifecycle Management Enabling Smart X

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Digital twins is a recent paradigm. It creates an entangled link between the physical system and its digital twin. The digital twin has obviously no sense without the existence of the physical system, but the physical system highly depends on the digital twin. This concept opens many new challenges and opportunities. Authors contributed to the construction of a digital twin architecture to manage a shop floor. The experience concerns a complete shop floor. To reach the status of digital twin, it was expected to reach simulation capacities and a complete digital chain to ensure the real time synchronisation of the real world with the underlying model which is the core component of the digital twin. A bottleneck was to create a coherent information system connecting information coming from various sources (MES, Machine Design, ERP, etc), then to propose first functions to demonstrate the added value of this digital twin; here a production simulation was expected within a visual 3D realistic representation of the shop floor. The simulation uses data directly captured from the shop floor to support better decision making. This paper presents the developed digital twin and its added value respect to production needs. It focuses on key performance indicators synchronisation as observed in the physical world and the impact on anticipation of the various futures depending on production decisions. It reports a first step of a digital twin deployment.

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Digital Twin Applications : A first systemization of their dimensions

Cited by 55 publications

References 25 publications

5-Dimension Cross-Industry Digital Twin Applications Model and Analysis of Digital Twin Classification Terms and Models

5-Dimension Cross-Industry Digital Twin Applications Model and Analysis of Digital Twin Classification Terms and Models

A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation

A Complete Digital Chain to Enable the Digital Twin of a Shop Floor

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