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Towards fully BIM-enabled building automation and robotics: A perspective of lifecycle information flow

journal contribution
posted on 06.01.2022, 15:32 authored by Jiale Zhang, Hanbin Luo, Jerry XuJerry Xu
The architecture, engineering, and construction (AEC) industry has seen a continuous growth in the application of Building Information Modelling (BIM) over the last two decades while building automation and robotics is also gaining ground in the meantime. With more joint applications of both BIM and robotics being exposed, the compatibility of BIM for robotic building construction and maintenance has been found to be fundamentally key to further practical implementations. This paper presents an integrated review combining quantitative and qualitative analyses to clarify the development roadmap of BIM-enabled building automation and robotics. Firstly, information and data management in Digital Twin and robotic building tasks is recapped as the prior knowledge. Secondly, a systematic review on BIM-related research topics in the last 18 years is conducted to demonstrate the inevitability and feasibility of BIM-robot integration, informed by the evolution of lifecycle building information flow. Then, critical analysis on three typical examples of BIM-based robotic construction (i.e. printing, assembling, and welding) are successively performed to reflect the potential BIM-robot integration mechanism and challenges ahead. Finally, a new unified robot-oriented BIM framework, namely BIMfAR, is proposed to conclude the cogitation based on the above analyses. Under the BIMfAR framework, definitions of basic concepts and a practical workflow are discussed to provide guidelines for future applications.

Funding

National Key R&D Program of China (Grant number 2018YFB1306905

History

School

  • Architecture, Building and Civil Engineering

Published in

Computers in Industry

Volume

135

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Computers in Industry and the definitive published version is available at https://doi.org/10.1016/j.compind.2021.103570

Acceptance date

04/11/2021

Publication date

2021-12-09

Copyright date

2022

ISSN

0166-3615

Language

en

Depositor

Mr Jerry Xu. Deposit date: 28 December 2021

Article number

103570