A Methodology to Develop and Implement Digital Twin Solutions for Manufacturing Systems

Qamsane, Yassine; Moyne, James; Toothman, Maxwell; Kovalenko, Ilya; Balta, Efe C.; Faris, John; Tilbury, Dawn M.; Barton, Kira

doi:10.1109/access.2021.3065971

Cited by 51 publications

(29 citation statements)

References 37 publications

(56 reference statements)

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“…Currently, there are no specific criteria or universal reference architectures to standardize the digital twinning process. According to the survey, there are mainly four types of representative architectures to offer guidelines and procedures for digital twinning: the generalized layered architecture [36,37], system development lifecycle-based method [38,39], Asset Administration Shell (AAS) framework [40,41], and ISO 23247 digital twin architecture [42]. In fact, whatever they say, the basic configuration of a digital twin system consists of three main parts: a physical entity (asset, process, or system) in real space (physical twin); a digital representation of the physical counterpart in cyberspace; and the cross-space entity to fuse and align the data and information between the physical side and virtual space.…”

Section: Digital Twin Modeling Methodsmentioning

confidence: 99%

Digital Twin-Driven Reconfigurable Fixturing Optimization for Trimming Operation of Aircraft Skins

2022

Aerospace

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The incomplete constraint induced by multipoint reconfigurable fixturing and the inherently weak rigidity of thin shell parts significantly hinder the stability of flexible fixturing systems. In particular, during the trimming operation, the number of effective locators may change with the progressive separation of the desired shape from that of the blank part, which easily produces the cliff effect (instantaneous dramatic reduction) of the system stiffness. As a result, the location layout becomes a main crux in reality. Regarding this issue, the author herein presents a digital twin-based decision-making methodology to generate reconfigurable fixturing schemes through integrating virtual and physical information. Considering the intrinsic features of the trimming process, such as the time-varying propagation of the system stiffness and the coupling effects of multiattribute process parameters, the hidden Markov model was introduced to cope with reconfigurable fixturing optimization. To achieve fast convergence and seek a feasible solution, local information (where low system rigidity occurs) was extracted and shared to guide the optimization process in a front-running simulation. To demonstrate the presented method, trimming experiments were performed on a large-size compliant workpiece held by a reconfigurable fixturing system that was developed independently by our research group. The experimental results indicate that the proposed method could adaptively iterate out the optimal locating schema and process control reference from the virtual fixturing and trimming simulation to guarantee the time-varying stability of the trimming process in the real world. Clearly, the digital twin-based reconfigurable fixturing planning approach generated a high possibility of building a context-specific, closed-loop decision-making paradigm and allowing the reconfigurable fixturing system to behave in a more adaptable and flexible manner.

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Section: Digital Twin Modeling Methodsmentioning

confidence: 99%

Digital Twin-Driven Reconfigurable Fixturing Optimization for Trimming Operation of Aircraft Skins

2022

Aerospace

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“…As the development trend of DTs has accelerated in recent years, more and more companies have begun to adopt DTs to optimize processes and make database decisions in real-time, becoming a pioneer in the adoption of DTs in capital-intensive industries such as manufacturing, utilities, and energy [140][141][142]. If early practitioners showed a first-mover advantage in many industry sectors, others followed.…”

Section: Dts Modeling Research Limitations and Future Prospectsmentioning

confidence: 99%

Modeling Methods of 3D Model in Digital Twins

Liu¹,

Li²,

Lv³

2023

Computer Modeling in Engineering &Amp; Sciences

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To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the elds of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles. At the same time, the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data, Internet of Things, Cloud Computing, Arti cial Intelligence, and game technology. Therefore, although some results have been achieved, there are still limitations. This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

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“…The digital twin implementation layers intend to provide generic technology elements to be used selectively in designing and establishing various digital twin applications [37]. Application domains, such as energy, transportation, logistics, environment, manufacturing, and smart cities, have different working environments and service requirements [38]- [41].…”

Section: F Applicationsmentioning

confidence: 99%

Digital Twin: Technology Evolution Stages and Implementation Layers With Technology Elements

Jeong¹,

Baek

Lim

et al. 2022

IEEE Access

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Digital twin has recently received considerable attention in various industry domains. The digital twin replicates physical objects (e.g., people, objects, spaces, systems, and processes) in the real world into digital objects in the digital world. It also provides various simulations to solve problems in the real world or to improve situational operations. Therefore, the digital twin is a convergence of various technologies, such as advanced machine-learning algorithms, data analytics, super-resolution visualization and modeling, and simulation. Because the digital twin is a complicated technology, a step-by-step implementation that includes many technology elements should be considered to create a digital twin model. In this study, implementation layers are introduced to guide practical implementations of the digital twin. In addition, technology elements were suggested for the presented implementation layers. Because the suggested technology elements include clear technology definitions, various application domains (e.g., energy, transportation, logistics, environment, manufacturing, and smart cities) can easily utilize the introduced implementation layers and technology elements according to the intended purpose. Furthermore, this paper describes the evolution of digital twins. Digital twin technology has evolved continuously since 2002, when the digital twin concept was first introduced. In the described evolution levels, we show the future aspects of digital twin technology, according to the technological evolution direction. Therefore, the digital twin model can be efficiently created by considering the evolution direction and future aspects by using the suggested digital twin evolution levels.

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A Methodology to Develop and Implement Digital Twin Solutions for Manufacturing Systems

Cited by 51 publications

References 37 publications

Digital Twin-Driven Reconfigurable Fixturing Optimization for Trimming Operation of Aircraft Skins

Digital Twin-Driven Reconfigurable Fixturing Optimization for Trimming Operation of Aircraft Skins

Modeling Methods of 3D Model in Digital Twins

Digital Twin: Technology Evolution Stages and Implementation Layers With Technology Elements

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