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Digital twins in additive manufacturing
1 College of Textile Technology, Bangladesh University of Textiles, Dhaka - 1208, Bangladesh.
2 Department of Manufacturing System Engineering and Management, California State University, Northridge, CA 91330, USA.
3 Pran RFL Group, Dhaka-1212, Bangladesh.
4 Department of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, Bangladesh.
Review
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 909-918.
Article DOI: 10.30574/wjaets.2024.13.2.0645
Publication history:
Received on 18 November 2024; revised on 24 December 2024; accepted on 26 December 2024
Abstract:
Additive Manufacturing (AM), a transformative production method, is gaining momentum across industries due to its ability to fabricate complex geometries with minimal waste. However, challenges in optimizing process parameters and ensuring quality control hinder its full potential. Digital Twins (DTs), virtual replicas of physical systems, have emerged as a solution to enhance AM processes by enabling real-time monitoring, simulation, and predictive analysis. The paper highlights key advancements in combining DTs with Industry 4.0 and 5.0 technologies, such as machine learning, augmented reality, and high-performance computing, to improve efficiency, scalability, and sustainability in manufacturing. Challenges including data quality, system integration, and computational demands are discussed, with a vision for adaptive and intelligent DT systems.
Keywords:
Additive Manufacturing; Digital Twin; Industry 4.0; Process Optimization; Smart Manufacturing; Real-Time Monitoring; Sustainability
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0