What are the major digital twin architecture?
Best insight from top research papers
Major digital twin architectures include hybrid simulation optimization models for decision support and forecasting, architectures based on the Web of Things (WoT) standard with Deep Reinforcement Learning (DRL) techniques for smart environments, multi-level modular architectures with microservice design for nuclear power plant safety, cloud-fog architectures for real-time requirements with reduced latency, and architectures enabling data exchange between physical and virtual entities in Industry 4.0. These architectures vary in complexity and application, catering to diverse needs such as production management, smart environment optimization, nuclear safety, real-time response, and vertical/horizontal integration in manufacturing systems. Each architecture leverages specific technologies and design principles to create effective digital twins for various domains.
Answers from top 4 papers
More filters
| Papers (4) | Insight |
|---|---|
130 Citations | The major digital twin architecture consists of six layers: local data, IoT Gateway, cloud-based databases, and emulations/simulations, enabling real-time data exchange between physical and virtual entities in manufacturing. |
| The major digital twin architecture for the New Safe Confinement of the Chernobyl Nuclear Power Plant is multi-level, modular, and based on a microservice architecture for flexibility and security. | |
Open access•Posted Content | Cloud-fog architecture is a major digital twin architecture, enhancing real-time performance by distributing computing power closer to the edge, reducing latency, and improving response times. |
3 Citations | The major digital twin architecture proposed in the paper is a hybrid simulation/optimization model, designed for decision support and forecasting in production management for industrial scheduling problems. |
Related Questions
What are the best ways to implement Digital Twins?5 answersThe best ways to implement Digital Twins involve methodological approaches, such as involving future users early in the development process. Additionally, utilizing real-time simulation to emulate physical systems can enhance accuracy and dynamic behavior, as seen in a hierarchical Digital Twin architecture for grid planning and operation. Implementing digital twins in systems of adaptive control for robotic manipulators can optimize workload and increase control accuracy, especially by representing kinematic diagrams in a vector model for efficient computational load. Moreover, applying digital twins in sports training, with sophisticated prediction models and user-friendly interfaces, can significantly improve training efficiency based on individual performance differences. Overall, combining these approaches can lead to successful Digital Twin implementations across various domains, ensuring enhanced decision-making, control, and operational efficiency.
How to build digital twins?3 answersDigital twins can be built using various methods and approaches. One approach is to use applied computing on embedded computers to construct digital twins based on flexible threads. Another method involves instantiating the ISO 23247 framework for building digital twins, as described in a case study of a manufacturing system comprising robot arms, a CNC machine tool, and a coordinate measuring machine (CMM). Additionally, a novel approach involves extracting fundamental knowledge from a production process and mapping it to an expert fuzzy rule set, which can then be used to generate augmented data and improve artificial neural network (ANN) models for representing digitized machines as digital twins. Another approach is to merge information from heterogeneous sources using a graph-based approach, which facilitates the creation of digital twins for existing manufacturing systems. Finally, a methodical approach involving the development of functional architectures and the involvement of future users early in the process can be followed to build digital twins in existing infrastructures.
What is digital twin twin?3 answersA digital twin is a virtual representation of a physical system or process that incorporates real-time data and simulation capabilities. It is created by integrating technologies such as sensors, IoT devices, and machine learning algorithms. Digital twins are used in various industries, including manufacturing, construction, oil and gas, and medicine. They provide benefits such as real-time monitoring, data analysis, and simulation of different scenarios, leading to improved efficiency and decision-making. In the oil and gas industry, digital twins can enhance operational efficiency, asset management, and the simulation of new assets. In medicine, digital twins have the potential to improve prevention of cardiovascular diseases and enable personalized healthcare. The digital twin ecosystem comprises sensor technologies, IoT, simulation and modeling, and machine learning. Overall, digital twins are a disruptive technology that creates a living data model of industrial assets, allowing for proactive identification of issues and prediction of future performance.
What is a mobility digital twin architecture?5 answersA mobility digital twin architecture is an implementation of digital twin technology in the transportation domain. It creates digital replicas of various physical mobility entities such as vehicles, drivers, and pedestrians. The architecture consists of three building blocks in the physical space: Human, Vehicle, and Traffic, along with their associated digital twins in the digital space. The architecture aims to facilitate high-fidelity and real-time digital twin model construction for connected and automated vehicles. It includes an end-to-end system framework that involves sensory data collection, offloading, and processing. The framework also incorporates artificial intelligence (AI)-based data-driven cloud-edge-device interactions to enable mobility services. The visualization of mobility digital twin is proposed to augment existing perception systems in connected and autonomous vehicles by twinning high-fidelity and manipulable geometry representations for causal traffic participants in the digital space.
When was the first digital twin created?5 answersThe concept of digital twins has a long history in science, but the first example of a conceptual rethinking using the digital twins concept was presented in the field of material science of high-tech graphene materials. However, the first digital twin created for the manufacturing industry was developed earlier.
What is a digital twin?1 answersA digital twin is a virtual model of a physical entity that has dynamic, bi-directional links with its corresponding physical entity in the digital domain. It serves as a digital shadow, reflecting the status and operation of its physical twin, and a digital thread, recording the evolution of the physical twin over time. Digital twins are increasingly used in various industries, including medicine and public health. In these fields, digital twin technology can drive a transformation of traditional electronic health records and enable personalized treatments and interventions. However, the concept of a digital twin lacks a unified definition, leading to a variety of definitions in the literature. To address this, a consolidated and generalized definition is proposed, along with characteristics to distinguish a digital twin from other digital technologies. Additionally, three sub-concepts of digital twins are identified: Engineering Twin, Production Twin, and Operation Twin. The term "Digital Twin System" is suggested to highlight its complex interconnected substructure.