Digital Twin in Industry: State-of-the-Art
TL;DR: This paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development ofDTs, and the major DT applications in industry and outlines the current challenges and some possible directions for future work.
Abstract: Digital twin (DT) is one of the most promising enabling technologies for realizing smart manufacturing and Industry 4.0. DTs are characterized by the seamless integration between the cyber and physical spaces. The importance of DTs is increasingly recognized by both academia and industry. It has been almost 15 years since the concept of the DT was initially proposed. To date, many DT applications have been successfully implemented in different industries, including product design, production, prognostics and health management, and some other fields. However, at present, no paper has focused on the review of DT applications in industry. In an effort to understand the development and application of DTs in industry, this paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development of DTs, and the major DT applications in industry. This paper also outlines the current challenges and some possible directions for future work.
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TL;DR: Digital twins as discussed by the authors is an emerging concept that has become the centre of attention for industry and, in recent years, academia and a review of publications relating to Digital Twins is performed, producing a categorical review of recent papers.
Abstract: Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.
739 citations
TL;DR: This work reviews the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Abstract: Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
660 citations
Cites background from "Digital Twin in Industry: State-of-..."
...The state-of-the-art of digital twin applications in industrial settings has been studied systematically in [42], where the authors concluded that the most popu-...
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TL;DR: A comprehensive and in-depth review of these literatures to analyze digital twin from the perspective of concepts, technologies, and industrial applications is conducted.
555 citations
TL;DR: 5-dimension digital twin model provides reference guidance for understanding and implementing digital twin, and the frequently-used enabling technologies and tools for digital twin are investigated and summarized to provide Technologies and tools references for the applications of digital twin in the future.
541 citations
TL;DR: The paper reviews the multi-faceted applications of BIM during the construction stage and highlights limits and requirements, paving the way to the concept of a Construction Digital Twin, described in terms of underpinning research themes, while elaborating on areas for future research.
401 citations
References
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TL;DR: In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed, and three cases are given to illustrate the future applications of digital twin in three phases of a product respectively.
Abstract: Nowadays, along with the application of new-generation information technologies in industry and manufacturing, the big data-driven manufacturing era is coming. However, although various big data in the entire product lifecycle, including product design, manufacturing, and service, can be obtained, it can be found that the current research on product lifecycle data mainly focuses on physical products rather than virtual models. Besides, due to the lack of convergence between product physical and virtual space, the data in product lifecycle is isolated, fragmented, and stagnant, which is useless for manufacturing enterprises. These problems lead to low level of efficiency, intelligence, sustainability in product design, manufacturing, and service phases. However, physical product data, virtual product data, and connected data that tie physical and virtual product are needed to support product design, manufacturing, and service. Therefore, how to generate and use converged cyber-physical data to better serve product lifecycle, so as to drive product design, manufacturing, and service to be more efficient, smart, and sustainable, is emphasized and investigated based on our previous study on big data in product lifecycle management. In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed. The detailed application methods and frameworks of digital twin-driven product design, manufacturing, and service are investigated. Furthermore, three cases are given to illustrate the future applications of digital twin in the three phases of a product respectively.
1,571 citations
"Digital Twin in Industry: State-of-..." refers background in this paper
...They prescribed nine principles to improve the maintenance efficiency and reduce maintenance failure [51]....
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16 Apr 2012
TL;DR: In this article, the Digital Twin system integrates ultra-high fidelity simulation with the vehicle s on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to enable unprecedented levels of safety and reliability.
Abstract: Future generations of NASA and U.S. Air Force vehicles will require lighter mass while being subjected to higher loads and more extreme service conditions over longer time periods than the present generation. Current approaches for certification, fleet management and sustainment are largely based on statistical distributions of material properties, heuristic design philosophies, physical testing and assumed similitude between testing and operational conditions and will likely be unable to address these extreme requirements. To address the shortcomings of conventional approaches, a fundamental paradigm shift is needed. This paradigm shift, the Digital Twin, integrates ultra-high fidelity simulation with the vehicle s on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to mirror the life of its flying twin and enable unprecedented levels of safety and reliability.
1,183 citations
"Digital Twin in Industry: State-of-..." refers background in this paper
..., increase of reliability, and timely assessment of mission parameters) [7]....
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...Other subjects included geometry assurance, cyber–physical system, and additive manufacturing, wind farm [7], [40], [46], [65], [66]....
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...In 2012, the NASA formalized the definition of DTs and envisioned its prospects in the aerospace industry [7]....
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...In 2012, the concept of DTs was revisited by the National Aeronautics and Space Administration (NASA), which defined the DT as a multiphysics, multiscale, probabilistic, ultrafidelity simulation that reflects, in a timely manner, the state of a corresponding twin based on the historical data, real-time sensor data, and physical model [7]....
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TL;DR: The similarities and differences between big data and digital twin are compared from the general and data perspectives and how they can be integrated to promote smart manufacturing are discussed.
Abstract: With the advances in new-generation information technologies, especially big data and digital twin, smart manufacturing is becoming the focus of global manufacturing transformation and upgrading. Intelligence comes from data. Integrated analysis for the manufacturing big data is beneficial to all aspects of manufacturing. Besides, the digital twin paves a way for the cyber-physical integration of manufacturing, which is an important bottleneck to achieve smart manufacturing. In this paper, the big data and digital twin in manufacturing are reviewed, including their concept as well as their applications in product design, production planning, manufacturing, and predictive maintenance. On this basis, the similarities and differences between big data and digital twin are compared from the general and data perspectives. Since the big data and digital twin can be complementary, how they can be integrated to promote smart manufacturing are discussed.
856 citations
"Digital Twin in Industry: State-of-..." refers background in this paper
...to improve the performance of product/process in the physical space [2]....
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...Others [2]–[4], [6] argue that the DT contains three dimensions: physical, virtual, and connection parts....
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TL;DR: In this paper, the authors discuss the importance of industrial manufacturing for economy and society, including the question about the future of labor and technical and technological questions that have to be taken care of as well.
854 citations
"Digital Twin in Industry: State-of-..." refers background or methods in this paper
...respond to state changes even during an ongoing operation [27]....
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...units could execute orders automatically according to simulation results [27]....
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TL;DR: In this article, the authors propose a reference model based on the concept of Skin Model Shapes, which serves as a digital twin of the physical product in design and manufacturing, and address model conceptualization, representation, and implementation as well as applications along the product life cycle.
765 citations
"Digital Twin in Industry: State-of-..." refers background in this paper
...They argued that the DT enabled designers to evaluate the quality of a product even at the early stage [36]....
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