This paper discusses an object-oriented event-driven simulation as a digital twin of a flexible assembly cell coordinated with a robot to perform assembly tasks alongside human. The digital twin ...extends the use of virtual simulation models developed in the design phase of a production system to operations for real-time control, dynamic skill-based tasks allocation between human and robot, sequencing of tasks and developing robot program accordingly. The methodology combines lean methods of manual assembly in human–robot collaboration paving path towards flexible human–robot work teams. The study is validated with an industrial case study involving dexterous assembly tasks.
Digital twins represent real objects or subjects with their data, functions, and communication capabilities in the digital world. As nodes within the internet of things, they enable networking and ...thus the automation of complex value-added chains. The application of simulation techniques brings digital twins to life and makes them experimentable; digital twins become experimentable digital twins (EDTs). Initially, these EDTs communicate with each other purely in the virtual world. The resulting networks of interacting EDTs model different application scenarios and are simulated in virtual testbeds, providing new foundations for comprehensive simulation-based systems engineering. Its focus is on EDTs, which become more detailed with every single application. Thus, complete digital representations of the respective real assets and their behaviors are created successively. The networking of EDTs with real assets leads to hybrid application scenarios in which EDTs are used in combination with real hardware, thus realizing complex control algorithms, innovative user interfaces, or mental models for intelligent systems.
When, in 1956, Artificial Intelligence (AI) was officially declared a research field, no one would have ever predicted the huge influence and impact its description, prediction, and prescription ...capabilities were going to have on our daily lives. In parallel to continuous advances in AI, the past decade has seen the spread of broadband and ubiquitous connectivity, (embedded) sensors collecting descriptive high dimensional data, and improvements in big data processing techniques and cloud computing. The joint usage of such technologies has led to the creation of digital twins, artificial intelligent virtual replicas of physical systems. Digital Twin (DT) technology is nowadays being developed and commercialized to optimize several manufacturing and aviation processes, while in the healthcare and medicine fields this technology is still at its early development stage. This paper presents the results of a study focused on the analysis of the state-of-the-art definitions of DT, the investigation of the main characteristics that a DT should possess, and the exploration of the domains in which DT applications are currently being developed. The design implications derived from the study are then presented: they focus on socio-technical design aspects and DT lifecycle. Open issues and challenges that require to be addressed in the future are finally discussed.
Technological advancements of urban informatics and vehicular intelligence have enabled connected smart vehicles as pervasive edge computing platforms for a plethora of powerful applications. ...However, varies types of smart vehicles with distinct capacities, diverse applications with different resource demands as well as unpredictive vehicular topology, pose significant challenges on realizing efficient edge computing services. To cope with these challenges, we incorporate digital twin technology and artificial intelligence into the design of a vehicular edge computing network. It centrally exploits potential edge service matching through evaluating cooperation gains in a mirrored edge computing system, while distributively scheduling computation task offloading and edge resource allocation in an multiagent deep reinforcement learning approach. We further propose a coordination graph driven vehicular task offloading scheme, which minimizes offloading costs through efficiently integrating service matching exploitation and intelligent offloading scheduling in both digital twin and physical networks. Numerical results based on real urban traffic datasets demonstrate the efficiency of our proposed schemes.
With the development of technologies, such as big data, cloud computing, and the Internet of Things (IoT), digital twin is being applied in industry as a precision simulation technology from concept ...to practice. Further, simulation plays a very important role in the healthcare field, especially in research on medical pathway planning, medical resource allocation, medical activity prediction, etc. By combining digital twin and healthcare, there will be a new and efficient way to provide more accurate and fast services for elderly healthcare. However, how to achieve personal health management throughout the entire lifecycle of elderly patients, and how to converge the medical physical world and the virtual world to realize real smart healthcare, are still two key challenges in the era of precision medicine. In this paper, a framework of the cloud healthcare system is proposed based on digital twin healthcare (CloudDTH). This is a novel, generalized, and extensible framework in the cloud environment for monitoring, diagnosing and predicting aspects of the health of individuals using, for example, wearable medical devices, toward the goal of personal health management, especially for the elderly. CloudDTH aims to achieve interaction and convergence between medical physical and virtual spaces. Accordingly, a novel concept of digital twin healthcare (DTH) is proposed and discussed, and a DTH model is implemented. Next, a reference framework of CloudDTH based on DTH is constructed, and its key enabling technologies are explored. Finally, the feasibility of some application scenarios and a case study for real-time supervision are demonstrated.
The rapid development of industrial Internet of Things (IIoT) requires industrial production towards digitalization to improve network efficiency. Digital Twin is a promising technology to empower ...the digital transformation of IIoT by creating virtual models of physical objects. However, the provision of network efficiency in IIoT is very challenging due to resource-constrained devices, stochastic tasks, and resources heterogeneity. Distributed resources in IIoT networks can be efficiently exploited through computation offloading to reduce energy consumption while enhancing data processing efficiency. In this article, we first propose a new paradigm digital twin network to build network topology and the stochastic task arrival model in IIoT systems. Then, we formulate the stochastic computation offloading and resource allocation problem to minimize the long-term energy efficiency. As the formulated problem is a stochastic programming problem, we leverage Lyapunov optimization technique to transform the original problem into a deterministic per-time slot problem. Finally, we present asynchronous actor-critic algorithm to find the optimal stochastic computation offloading policy. Illustrative results demonstrate that our proposed scheme is able to significantly outperforms the benchmarks.
Using Digital Twins in healthcare Boată, Adriana; Angelescu, Radu; Dobrescu, Radu
Scientific Bulletin. Series C, Electrical Engineering and Computer Science,
01/2021
4
Journal Article
Peer reviewed
This paper aims to summarize the progress made in the use of the Digital Twin (DT) concept for choosing the right drug for a person, as well as presenting a subnet model that predicts existing drugs ...for a particular pathology, based on genetic expressions involved in the disease, and genes addressed by therapy. Finally, as a result of the research, the paper discusses how the proposed method can be applied to search for a medication for the disease caused by the Covid 19 virus, with reference to the results of some clinical trials conducted after the onset of the pandemic.
The rapid development of artificial intelligence and 5G paradigm, opens up new possibilities for emerging applications in industrial Internet of Things (IIoT). However, the large amount of data, the ...limited resources of Internet of Things devices, and the increasing concerns of data privacy, are major obstacles to improve the quality of services in IIoT. In this article, we propose the digital twin edge networks (DITENs) by incorporating digital twin into edge networks to fill the gap between physical systems and digital spaces. We further leverage the federated learning to construct digital twin models of IoT devices based on their running data. Moreover, to mitigate the communication overhead, we propose an asynchronous model update scheme and formulate the federated learning scheme as an optimization problem. We further decompose the problem and solve the subproblems based on the deep neural network model. Numerical results show that our proposed federated learning scheme for DITEN improves the communication efficiency and reduces the transmission energy cost.
Sensor technologies empower Industry 4.0 by enabling integration of in-field and real-time raw data into digital twins. However, sensors might be unreliable due to inherent issues and/or ...environmental conditions. This article aims at detecting anomalies in measurements from sensors, identifying the faulty ones and accommodating them with appropriate estimated data, thus paving the way to reliable digital twins. More specifically, we propose a general machine-learning-based architecture for sensor validation built upon a series of neural-network estimators and a classifier. Estimators correspond to virtual sensors of all unreliable sensors (to reconstruct normal behaviour and replace the isolated faulty sensor within the system), whereas the classifier is used for detection and isolation tasks. A comprehensive statistical analysis on three different real-world data-sets is conducted and the performance of the proposed architecture validated under hard and soft synthetically-generated faults.
Digital twin technology is considered as a key technology to realize cyber-physical systems (CPS). However, due to the complexity of building a digital equivalent in virtual space to its physical ...counterpart, very little progress has been achieved in digital twin application, especially in the complex product assembly shop-floor. In this paper, we propose a framework of digital twin-based smart production management and control approach for complex product assembly shop-floors. Four core techniques embodied in the framework are illustrated in detail as follows: (1) real-time acquisition, organization, and management of the physical assembly shop-floor data, (2) construction of the assembly shop-floor digital twin, (3) digital twin and big data-driven prediction of the assembly shop-floor, and (4) digital twin-based assembly shop-floor production management and control service. To elaborate how to apply the proposed approach to reality, we present detailed implementation process of the proposed digital twin-based smart production management and control approach in a satellite assembly shop-floor scenario. Meanwhile, the future work to completely fulfill digital twin-based smart production management and control concept for complex product assembly shop-floors are discussed.
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