TY  - INPR
TI  - Digital twin for product versus project lifecycles? development in manufacturing and construction industries
PB  - Springer Science and Business Media LLC
ID  - discovery10187366
Y1  - 2024/01/31/
N1  - This work is licensed under a Creative Commons Attribution 4.0 International License. The images
or other third-party material in this article are included in the Creative Commons license,
unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license,
users will need to obtain permission from the license holder to reproduce the material. To view a copy of this
license, visit http://creativecommons.org/licenses/by/4.0/
JF  - Journal of Intelligent Manufacturing
A1  - Abanda, FH
A1  - Jian, N
A1  - Adukpo, S
A1  - Tuhaise, VV
A1  - Manjia, MB
UR  - http://dx.doi.org/10.1007/s10845-023-02301-2
N2  - Digital twin, as an important enabling tool for digital transformation, has received increasing attention from researchers and practitioners since its definition was formalised. Especially in the global context and exacerbated by Covid-19, the applications of the digital twin have offered opportunities for many industries. While the digital twin has already been widely used in many sectors such as manufacturing and the construction industry?one of the key engines of economic development, is still lagging behind many other sectors. This study uses the systematic literature review to assess the applications of digital twin in manufacturing and construction respectively, the benefits it brings, and the impediments to its application. Based on this, a comparison is made of digital twin applications in the manufacturing and construction industries to draw lessons. This study concluded that although the use of digital twin in manufacturing is better than construction overall, it is still not reaching its full potential. Despite many benefits brought by the digital twin to construction during the project lifecycle, the construction sector faces even greater challenges than manufacturing in digital twin adoption. By comparison, this study drew five lessons to drive better adoption of the digital twin. The construction industry needs to accelerate the deployment of relevant hardware, promote the standard unification of digital twin, explore the whole lifecycle application of the digital twin, enhance data protection, and embrace changes. This study was limited in the scope of data collection. Future research could focus on gathering information from specific case studies, to produce more comprehensive perspectives.
KW  - Construction sector
KW  -  Digital Twin
KW  -  Digital transformation
KW  -  Manufacturing sector
KW  -  Lifecycle performance assessment
AV  - public
ER  -