Rapid advances in new generation information technologies, such as big data analytics, internet of things (IoT), edge computing and artificial intelligence, have nowadays driven traditional ...manufacturing all the way to intelligent manufacturing. Intelligent manufacturing is characterised by autonomy and self-optimisation, which proposes new demands such as learning and cognitive capacities for manufacturing cell, known as the minimum implementation unit for intelligent manufacturing. Consequently, this paper proposes a general framework for knowledge-driven digital twin manufacturing cell (KDTMC) towards intelligent manufacturing, which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimising and controlling strategy. Three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analysed, which equip KDTMC with the capacities of self-thinking, self-decision-making, self-execution and self-improving. The implementing methods of KDTMC are also introduced by a thus constructed test bed. Three application examples about intelligent process planning, intelligent production scheduling and production process analysis and dynamic regulation demonstrate the feasibility of KDTMC, which provides a practical insight into the intelligent manufacturing paradigm.
6G is envisioned to empower wireless communication and computation through the digitalization and connectivity of everything, by establishing a digital representation of the real network environment. ...Mobile edge computing (MEC), as one of the key enabling factors, meets unprecedented challenges during mobile offloading due to the extremely complicated and unpredictable network environment in 6G. The existing works on offloading in MEC mainly ignore the effects of user mobility and the unpredictable MEC environment. In this paper, we present a new vision of Digital Twin Edge Networks (DITEN) where digital twins (DTs) of edge servers estimate edge servers' states and DT of the entire MEC system provides training data for offloading decision. A mobile offloading scheme is proposed in DITEN to minimize the offloading latency under the constraints of accumulated consumed service migration cost during user mobility. The Lyapunov optimization method is leveraged to simplify the long-term migration cost constraint to a multi-objective dynamic optimization problem, which is then solved by <inline-formula><tex-math notation="LaTeX">Actor</tex-math></inline-formula>-<inline-formula><tex-math notation="LaTeX">Critic</tex-math></inline-formula> deep reinforcement learning. Simulations results show that our proposed scheme effectively diminishes the average offloading latency, the offloading failure rate, and the service migration rate, as compared with benchmark schemes, while saving the system cost with DT assistance.
The Economics of Digital Twins Kshetri, Nir
Computer (Long Beach, Calif.),
2021-April, 2021-4-00, Volume:
54, Issue:
4
Journal Article
Peer reviewed
Open access
Digital twins provide a number of economic, health, social, and environmental benefits. Their value can be amplified by combining them with other technologies and tools.
Abstract
One method for finding reliable and cost-effective solutions for designing radioisotope production systems is represented by the “digital twin” philosophy of design. Looking at cyclotron ...solid targets, uncertainties of the particle beam, material composition and geometry play a crucial role in determining the results. The difference between what has been designed and what can be effectively manufactured, where processes such as electroplating are poorly controllable and generate large non-uniformities in deposition, must also be considered. A digital twin, where the target geometry is 3D scanned from real models, can represent a good compromise for connecting “ideal” and “real” worlds. Looking at the
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Ni(p,n)
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Cu reaction, different Unstructured-Mesh MCNP6 models have been built starting from the 3D solid target system designed and put into operation by COMECER. A characterization has been performed considering the designed ideal target and a 3D scan of a real manufactured target measured with a ZEISS contact probe. Libraries and physics models have been also tested due to limited cross-section data. Proton spectra in the target volume, 3D proton-neutron-photon flux maps, average energies, power to be dissipated, shut-down dose-rate,
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Cu yield compared with various sources of experimental data and beam axial shifting impact, have been estimated. A digital twin of the
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Ni(p,n)
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Cu production device has been characterized, considering the real measured target geometry, paving the way for a fully integrated model suitable also for thermal, structural or fluid-dynamic analyses.
Towards adaptive digital twins architecture Ogunsakin, Rotimi; Mehandjiev, Nikolay; Marin, Cesar A.
Computers in industry,
August 2023, 2023-08-00, Volume:
149
Journal Article
Peer reviewed
Open access
The use of Digital Twins (DTs) for continuously optimising manufacturing systems under a constant stream of changes, also known as ”online optimisation”, is taken for granted by many authors but ...rarely demonstrated possible given the challenges in keeping a DT synchronised with its real system whilst using it to run look-ahead simulations. This research addresses this gap by demonstrating that online optimisation is achievable alongside real-time look-ahead simulation in DTs, even under constant changes in the system being modelled. The main enabling factor is a proposed architecture which can underpin a Digital Twin with Adaptive capabilities, or Adaptive Digital Twin (ADT). The capabilities include Real-time Simulation, Online Optimisation, and Adaptivity (RSO2A). The proposed ADT architecture is suitable for constantly changing production environments with unpredictable demands, for example, those envisioned to deliver the concept of mass personalisation, allowing customers to co-create and co-design products based on personal preferences. To demonstrate and validate the support of the ADT architecture for RSO2A, an Adaptive Manufacturing System (AMS) for mass personalisation is developed in silico. The AMS is underpinned by the proposed ADT architecture and simulated its operation and adaptation using realistic shoe personalisation scenarios. The simulation output demonstrates how the proposed architecture and the ADT built with it enable the AMS to maintain continuous production of personalised shoes and continuously re-configure its layout to adapt to new changes in the production environment.
•The development of Adaptive Digital Twins architecture with appropriate abstractions for real-time simulation, online optimisation, and adaptivity.•The development of Adaptive Manufacturing System for mass personalisation production environment.•Real-time layout optimisation capability enabled by Adaptive Digital Twins architecture.
Recently, low-orbit satellite networks have gained lots of attention from the society due to their wide coverage, low transmission latency, and storage and computing capacity. Providing seamless ...connectivity to users in different areas is envisioned as a promising solution, especially in remote areas and for marine communication. However, when jointly used with terrestrial networks composing satellite-terrestrial networks, the satellite moving speed is much faster than the ground terminal, which can cause inconsistent service from a single satellite, and therefore lead to frequent satellite handover. Moreover, due to the dynamic and time slot visibility of satellites, the topology of an intersatellite changes frequently, which results in loops during satellite handover, thereby reducing the utilization of links. To address these problems, we propose a digital twin-assisted storage strategy for satellite-terrestrial networks (INTERLINK), which leverages the digital twins (DTs) to map the satellite networks to virtual space for better communication. Specifically, we first propose a satellite storage-oriented handover scheme to minimize the handover frequency by considering the limited access time and capacity constraints of satellites. Then, a multiobjective optimization problem is formulated to obtain the optimal satellite by genetic algorithm. Finally, considering the timing visibility of the satellite links, a digital twin-assisted intersatellite routing scheme is introduced to improve the quality of data delivery between satellites. Simulation results demonstrate that the proposed INTERLINK can reduce both handover times and average propagation delay compared with its counterparts. Meanwhile, benefitting from integrated DT, both the quality of data delivery and the delay of intersatellite links are considerably improved.
Most of the buildings that exist today were built based on 2D drawings. Building information models that represent design-stage product information have become prevalent in the second decade of the ...21st century. Still, it will take many decades before such models become the norm for all existing buildings. In the meantime, the building industry lacks the tools to leverage the benefits of digital information management for construction, operation, and renovation. To this end, this paper reviews the state-of-the-art practice and research for constructing (generating) and maintaining (updating) geometric digital twins. This paper also highlights the key limitations preventing current research from being adopted in practice and derives a new geometry-based object class hierarchy that mainly focuses on the geometric properties of building objects, in contrast to widely used existing object categorisations that are mainly function-oriented. We argue that this new class hierarchy can serve as the main building block for prioritising the automation of the most frequently used object classes for geometric digital twin construction and maintenance. We also draw novel insights into the limitations of current methods and uncover further research directions to tackle these problems. Specifically, we believe that adapting deep learning methods can increase the robustness of object detection and segmentation of various types; involving design intents can achieve a high resolution of model construction and maintenance; using images as a complementary input can help to detect transparent and specular objects; and combining synthetic data for algorithm training can overcome the lack of real labelled datasets.
This paper reviews the current status and advancement of Digital Twin-driven smart manufacturing, with highlights on the following aspects:•Presented the connotation of Digital Twin-driven smart ...manufacturing and its potential impacts.•Proposed a reference model for constructing a Digital Twin, comprising of an information model, data processing and industrial communication technologies.•Discussed seven crucial research issues for developing Digital Twin applications for smart manufacturing.
This paper reviews the recent development of Digital Twin technologies in manufacturing systems and processes, to analyze the connotation, application scenarios, and research issues of Digital Twin-driven smart manufacturing in the context of Industry 4.0. To understand Digital Twin and its future potential in manufacturing, we summarized the definition and state-of-the-art development outcomes of Digital Twin. Existing technologies for developing a Digital Twin for smart manufacturing are reviewed under a Digital Twin reference model to systematize the development methodology for Digital Twin. Representative applications are reviewed with a focus on the alignment with the proposed reference model. Outstanding research issues of developing Digital Twins for smart manufacturing are identified at the end of the paper.
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.
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