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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

Digital twins in additive manufacturing

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Md Hossain 1, 2, * and Md Bahar Uddin 3, 4

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 Article
 
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 909-918.
Article DOI: 10.30574/wjaets.2024.13.2.0645
DOI url: https://doi.org/10.30574/wjaets.2024.13.2.0645

Received on 18 November 2024; revised on 24 December 2024; accepted on 26 December 2024

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.

Additive Manufacturing; Digital Twin; Industry 4.0; Process Optimization; Smart Manufacturing; Real-Time Monitoring; Sustainability

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2024-0645.pdf

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Md Hossain and Md Bahar Uddin. Digital twins in additive manufacturing. World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 909-918. Article DOI: https://doi.org/10.30574/wjaets.2024.13.2.0645 

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