Related papers: Training with Product Digital Twins for AutoRetail…
In the manufacturing industry, the digital twin (DT) is becoming a central topic. It has the potential to enhance the efficiency of manufacturing machines and reduce the frequency of errors. In order to fulfill its purpose, a DT must be an…
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms are increasingly seen as a promising paradigm to control and monitor software-based, "open", communication systems, which play the role of the physical…
The increased use of software in the operation and management of telecommunication networks has moved the industry one step closer to realizing autonomous network operation. One consequence of this shift is the significantly increased need…
Digital twins (DTs) are an emerging capability in additive manufacturing (AM), set to revolutionize design optimization, inspection, in situ monitoring, and root cause analysis. AM DTs typically incorporate multimodal data streams, ranging…
The industry increasingly relies on deep learning (DL) technology for manufacturing inspections, which are challenging to automate with rule-based machine vision algorithms. DL-powered inspection systems derive defect patterns from labeled…
The evolution and growing automation of collaborative robots introduce more complexity and unpredictability to systems, highlighting the crucial need for robot's adaptability and flexibility to address the increasing complexities of their…
The biopharmaceutical industry is increasingly developing digital twins to digitalize and automate the manufacturing process in response to the growing market demands. However, this shift presents significant challenges for human operators,…
Recent technological developments and advances in Artificial Intelligence (AI) have enabled sophisticated capabilities to be a part of Digital Twin (DT), virtually making it possible to introduce automation into all aspects of work…
Deep learning models have created great opportunities for data-driven fault diagnosis but they require large amount of labeled failure data for training. In this paper, we propose to use a digital twin to support developing data-driven…
Digital twins are becoming powerful tools in industrial applications, offering virtual representations of cyber-physical systems. However, verification of these models remains a significant challenge due to the potentially large datasets…
Digital Twins (DTs) are computational models that simulate the states and temporal dynamics of real-world systems, playing a crucial role in prediction, understanding, and decision-making across diverse domains. However, existing approaches…
In the way towards Industry 4.0, the complexity of the industrial systems increases due to the presence of multiple agents, Cyber-Physical Systems, distributed sensing, and big data introducing unknown dynamics that affect the production…
The convergence of modeling & simulation (M&S) and artificial intelligence (AI) is leaving its marks on advanced digital technology. Pertinent examples are digital twins (DTs) - high-fidelity, live representations of physical assets, and…
Digital Twins (DT) are essentially dynamic data-driven models that serve as real-time symbiotic "virtual replicas" of real-world systems. DT can leverage fundamentals of Dynamic Data-Driven Applications Systems (DDDAS) bidirectional…
Deep learning has been widely applied in recommender systems, which has achieved revolutionary progress recently. However, most existing learning-based methods assume that the user and item distributions remain unchanged between the…
The proliferation of diverse wireless services in 5G and beyond has led to the emergence of network slicing technologies. Among these, admission control plays a crucial role in achieving service-oriented optimization goals through the…
Smart Digital twins (SDTs) are being increasingly used to virtually replicate and predict the behaviors of complex physical systems through continual data assimilation enabling the optimization of the performance of these systems by…
The onset of Industry 4.0 is rapidly transforming the manufacturing world through the integration of cloud computing, machine learning (ML), artificial intelligence (AI), and universal network connectivity, resulting in performance…
The identification of Line-of-Sight (LoS) conditions is critical for ensuring reliable high-frequency communication links, which are particularly vulnerable to blockages and rapid channel variations. Network Digital Twins (NDTs) and…
Network digital twins (NDTs) facilitate the estimation of key performance indicators (KPIs) before physically implementing a network, thereby enabling efficient optimization of the network configuration. In this paper, we propose a…