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Related papers: Towards a Digital Twin Framework in Additive Manuf…

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A digital twin is a virtual representation that accurately replicates its physical counterpart, fostering bi-directional real-time data exchange throughout the entire process lifecycle. For Laser Directed Energy Deposition of Wire…

Computational Engineering, Finance, and Science · Computer Science 2024-12-05 Maximilian Kannapinn , Fabian Roth , Oliver Weeger

A digital twin (DT), with the components of a physics-based model, a data-driven model, and a machine learning (ML) enabled efficient surrogate, behaves as a virtual twin of the real-world physical process. In terms of Laser Powder Bed…

Signal Processing · Electrical Eng. & Systems 2024-05-17 Ning Liu , Xuxiao Li , Manoj R. Rajanna , Edward W. Reutzel , Brady Sawyer , Prahalada Rao , Jim Lua , Nam Phan , Yue Yu

Digital Twin -- a virtual replica of a physical system enabling real-time monitoring, model updating, prediction, and decision-making -- combined with recent advances in machine learning, offers new opportunities for proactive control…

Machine Learning · Computer Science 2025-04-14 Yi-Ping Chen , Vispi Karkaria , Ying-Kuan Tsai , Faith Rolark , Daniel Quispe , Robert X. Gao , Jian Cao , Wei Chen

This paper explores the development and practical application of a predictive digital twin specifically designed for condition monitoring, using advanced mathematical models and thermal imaging techniques. Our work presents a comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Daniel Menges , Florian Stadtmann , Henrik Jordheim , Adil Rasheed

Digital Twin (DT) technologies are transforming manufacturing by enabling real-time prediction, monitoring, and control of complex processes. Yet, applying DT to deformation-based metal forming remains challenging because of the strongly…

Systems and Control · Electrical Eng. & Systems 2025-11-17 Yi-Ping Chen , Derick Suarez , Ying-Kuan Tsai , Vispi Karkaria , Guanzhong Hu , Zihan Chen , Ping Guo , Jian Cao , Wei Chen

Digital twins enable real-time simulation and prediction in engineering systems. This paper presents a novel framework for predictive digital twins of a headlamp heatsink, integrating physics-based reduced-order models (ROMs) from…

Machine Learning · Computer Science 2025-05-13 Tamilselvan Subramani , Sebastian Bartscher

Thermal multi-phase flow simulations are indispensable to understanding the multi-scale and multi-physics phenomena in metal additive manufacturing (AM) processes, yet accurate and robust predictions remain challenging. This book chapter…

Computational Engineering, Finance, and Science · Computer Science 2022-06-13 Jinhui Yan , Qiming Zhu , Ze Zhao

Early detection and correction of defects are critical in additive manufacturing (AM) to avoid build failures. In this paper, we present a multisensor fusion-based digital twin for in-situ quality monitoring and defect correction in a…

Image and Video Processing · Electrical Eng. & Systems 2023-04-13 Lequn Chen , Xiling Yao , Kui Liu , Chaolin Tan , Seung Ki Moon

Accurately predicting the temperature field in metal additive manufacturing (AM) processes is critical to preventing overheating, adjusting process parameters, and ensuring process stability. While physics-based computational models offer…

Machine Learning · Computer Science 2024-01-05 Pouyan Sajadi , Mostafa Rahmani Dehaghani , Yifan Tang , G. Gary Wang

The manufacturing sector has a substantial influence on worldwide energy consumption. Therefore, improving manufacturing system energy efficiency is becoming increasingly important as the world strives to move toward a more resilient and…

Systems and Control · Electrical Eng. & Systems 2023-09-20 Hongliang Li , Herschel C. Pangborn , Ilya Kovalenko

The real-time supervision of production processes is a common challenge across several industries. It targets process component monitoring and its predictive maintenance in order to ensure safety, uninterrupted production and maintain high…

Machine Learning · Computer Science 2026-02-27 Osimone Imhogiemhe , Yoann Jus , Hubert Lejeune , Saïd Moussaoui

Additive Manufacturing (AM) is a manufacturing paradigm that builds three-dimensional objects from a computer-aided design model by successively adding material layer by layer. AM has become very popular in the past decade due to its…

Machine Learning · Computer Science 2019-08-12 Arindam Paul , Mojtaba Mozaffar , Zijiang Yang , Wei-keng Liao , Alok Choudhary , Jian Cao , Ankit Agrawal

Digital twin (DT) technology enables real-time simulation, prediction, and optimization of physical systems, but practical deployment faces challenges from high data requirements, proprietary data constraints, and limited adaptability to…

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…

Human-Computer Interaction · Computer Science 2024-05-22 Vuthea Chheang , Saurabh Narain , Garrett Hooten , Robert Cerda , Brian Au , Brian Weston , Brian Giera , Peer-Timo Bremer , Haichao Miao

A digital twin (DT) is a virtual representation of physical process, products and/or systems that requires a high-fidelity computational model for continuous update through the integration of sensor data and user input. In the context of…

Machine Learning · Computer Science 2023-11-15 Yangfan Li , Satyajit Mojumder , Ye Lu , Abdullah Al Amin , Jiachen Guo , Xiaoyu Xie , Wei Chen , Gregory J. Wagner , Jian Cao , Wing Kam Liu

Physics-informed dynamical system models form critical components of digital twins of the built environment. These digital twins enable the design of energy-efficient infrastructure, but must be properly calibrated to accurately reflect…

Machine Learning · Computer Science 2021-06-30 Ankush Chakrabarty , Gordon Wichern , Christopher Laughman

We introduce a novel digital twin framework for predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the digital twin framework can be used to enhance automotive safety and…

Machine Learning · Computer Science 2024-08-13 Vispi Karkaria , Jie Chen , Christopher Luey , Chase Siuta , Damien Lim , Robert Radulescu , Wei Chen

The potential of digital twin technology is immense, specifically in the infrastructure, aerospace, and automotive sector. However, practical implementation of this technology is not at an expected speed, specifically because of lack of…

Machine Learning · Statistics 2021-03-30 Shailesh Garg , Ankush Gogoi , Souvik Chakraborty , Budhaditya Hazra

A digital twin is a surrogate model that has the main feature to mirror the original process behavior. Associating the dynamical process with a digital twin model of reduced complexity has the significant advantage to map the dynamics with…

Numerical Analysis · Mathematics 2024-03-19 Diana Alina Bistrian , Omer San , Ionel Michael Navon

In additive manufacturing (AM), particularly for laser-based metal AM, process optimization is crucial to the quality of products and the efficiency of production. The identification of optimal process parameters out of a vast parameter…

Materials Science · Physics 2024-07-25 Xiao Shang , Evelyn Li , Ajay Talbot , Haitao Wen , Tianyi Lyu , Jiahui Zhang , Yu Zou
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