Please use this identifier to cite or link to this item:
Title: Digital twins for additive manufacturing : a state‐of‐the‐art review
Authors: Zhang, Li
Chen, Xiaoqi
Zhou, Wei
Cheng, Taobo
Chen, Lijia
Guo, Zhen
Han, Bing
Lu, Longxin
Keywords: Engineering::Mechanical engineering
Issue Date: 2020
Source: Zhang, L., Chen, X., Zhou, W., Cheng, T., Chen, L., Guo, Z., . . . Lu, L. (2020). Digital Twins for Additive Manufacturing: A State-of-the-Art Review. Applied Sciences, 10(23), 8350-. doi:10.3390/app10238350
Journal: Applied Sciences
Abstract: With the development of Industry 4.0, additive manufacturing will be widely used to produce customized components. However, it is rather time‐consuming and expensive to produce components with sound structure and good mechanical properties using additive manufacturing by a trial‐and‐error approach. To obtain optimal process conditions, numerous experiments are needed to optimize the process variables within given machines and processes. Digital twins (DT) are defined as a digital representation of a production system or service or just an active unique product characterized by certain properties or conditions. They are the potential solution to assist in overcoming many issues in additive manufacturing, in order to improve part quality and shorten the time to qualify products. The DT system could be very helpful to understand, analyze and improve the product, service system or production. However, the development of genuine DT is still impeded due to lots of factors, such as the lack of a thorough understanding of the DT concept, framework, and development methods. Moreover, the linkage between existing brownfield systems and their data are under development. This paper aims to summarize the current status and issues in DT for additive manufacturing, in order to provide more references for subsequent research on DT systems.
ISSN: 2076-3417
DOI: 10.3390/app10238350
Rights: © 2020 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

Files in This Item:
File Description SizeFormat 
applsci-10-08350-v2-1.pdf2.56 MBAdobe PDFView/Open

Page view(s)

Updated on Aug 10, 2022

Download(s) 50

Updated on Aug 10, 2022

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.