Digital Twins in Additive Manufacturing: A systematic review

IF 6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Internet of Things Pub Date : 2025-07-07 DOI:10.1016/j.iot.2025.101692

Md Manjurul Ahsan , Yingtao Liu , Shivakumar Raman , Zahed Siddique

{"title":"Digital Twins in Additive Manufacturing: A systematic review","authors":"Md Manjurul Ahsan , Yingtao Liu , Shivakumar Raman , Zahed Siddique","doi":"10.1016/j.iot.2025.101692","DOIUrl":null,"url":null,"abstract":"<div><div>Digital Twins (DTs) are becoming popular in Additive Manufacturing (AM) due to their ability to create virtual replicas of physical components of AM machines, which helps in real-time production monitoring. Advanced techniques such as Machine Learning (ML), Augmented Reality (AR), and simulation-based models play key roles in developing intelligent and adaptable DTs in manufacturing processes. However, questions remain regarding scalability, the integration of high-quality data, and the computational power required for real-time applications in developing DTs. Understanding the current state of DTs in AM is essential to address these challenges and fully utilize their potential in advancing AM processes. Considering this opportunity, this work aims to provide a comprehensive overview of DTs in AM by addressing the following four research questions: (1) What are the key types of DTs used in AM and their specific applications? (2) What are the recent developments and implementations of DTs? (3) How are DTs employed in process improvement and hybrid manufacturing? (4) How are DTs integrated with Industry 4.0 technologies? By discussing current applications and techniques, we aim to offer a better understanding and potential future research directions for researchers and practitioners in AM and DTs.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"33 ","pages":"Article 101692"},"PeriodicalIF":6.0000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet of Things","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2542660525002069","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

Digital Twins (DTs) are becoming popular in Additive Manufacturing (AM) due to their ability to create virtual replicas of physical components of AM machines, which helps in real-time production monitoring. Advanced techniques such as Machine Learning (ML), Augmented Reality (AR), and simulation-based models play key roles in developing intelligent and adaptable DTs in manufacturing processes. However, questions remain regarding scalability, the integration of high-quality data, and the computational power required for real-time applications in developing DTs. Understanding the current state of DTs in AM is essential to address these challenges and fully utilize their potential in advancing AM processes. Considering this opportunity, this work aims to provide a comprehensive overview of DTs in AM by addressing the following four research questions: (1) What are the key types of DTs used in AM and their specific applications? (2) What are the recent developments and implementations of DTs? (3) How are DTs employed in process improvement and hybrid manufacturing? (4) How are DTs integrated with Industry 4.0 technologies? By discussing current applications and techniques, we aim to offer a better understanding and potential future research directions for researchers and practitioners in AM and DTs.

查看原文本刊更多论文

增材制造中的数字孪生：系统回顾

数字孪生（dt）在增材制造（AM）中越来越流行，因为它们能够创建增材制造机器物理组件的虚拟副本，这有助于实时生产监控。机器学习（ML）、增强现实（AR）和基于仿真的模型等先进技术在制造过程中开发智能和适应性强的dt方面发挥着关键作用。然而，在开发DTs时，关于可伸缩性、高质量数据的集成以及实时应用程序所需的计算能力的问题仍然存在。了解增材制造中dt的现状对于应对这些挑战并充分利用其在推进增材制造过程中的潜力至关重要。考虑到这个机会，本工作旨在通过解决以下四个研究问题，提供AM中的dt的全面概述：(1)AM中使用的dt的关键类型及其具体应用是什么？(2) DTs的最新发展和实施情况如何？(3) DTs如何应用于工艺改进和混合制造？(4) dt如何与工业4.0技术相结合？通过讨论当前的应用和技术，我们旨在为AM和dt的研究人员和从业者提供更好的理解和潜在的未来研究方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Internet of Things Multiple-

CiteScore

3.60

自引率

5.10%

发文量

115

审稿时长

37 days

期刊介绍： Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.