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Big data for design options repository: Towards a DFMA approach for offsite construction

Gbadamosi, Abdul-Quayyum; Oyedele, Lukumon; Mahamadu, Abdul-Majeed; Kusimo, Habeeb; Bilal, Muhammad; Davila Delgado, Juan Manuel; Muhammed-Yakubu, Naimah

Authors

Abdul Gbadamosi Abdul.Gbadamosi@uwe.ac.uk
Research Associate - Big Data Application Development

Abdul Mahamadu Abdul.Mahamadu@uwe.ac.uk
Senior Lecturer in Project Management in the Built Environment

Habeeb Kusimo Habeeb.Kusimo@uwe.ac.uk
Research Associate - Digital Construction with Big Data

Muhammad Bilal Muhammad.Bilal@uwe.ac.uk
Associate Professor - Big Data Application

Manuel Davila Delgado Manuel.Daviladelgado@uwe.ac.uk
Associate Professor - AR/VR Development with Artificial Intelligence

Naimah Muhammed-Yakubu Naimah.Muhammed-Yakubu@uwe.ac.uk
Research Associate - Project Analytics using Digital Technologies



Abstract

A persistent barrier to the adoption of offsite construction is the lack of information for assessing prefabrication alternatives and the choices of suppliers. This study integrates three aspects of offsite construction, including BIM, DFMA and big data, to propose a Big data Design Options Repository (BIG-DOR). The proposed BIG-DOR system will connect BIM clients to manufacturers/supplier’s information such as prefab component cost and production lead times. In this study, we propose a framework for integrating BIG-DOR into the process of offsite construction delivery. The design of the BIG-DOR system architecture, as well as the key components such as the DFMA option-based 3D objects classifier, is presented. The contribution to the knowledge of this study is the successful integration of BIM, big data, DFMA and offsite construction in a single framework and the development of a design alternatives assessment system for offsite construction adoption using this framework.

Citation

Gbadamosi, A., Oyedele, L., Mahamadu, A., Kusimo, H., Bilal, M., Davila Delgado, J. M., & Muhammed-Yakubu, N. (2020). Big data for design options repository: Towards a DFMA approach for offsite construction. Automation in Construction, 120, https://doi.org/10.1016/j.autcon.2020.103388

Journal Article Type Article
Acceptance Date Aug 29, 2020
Online Publication Date Oct 3, 2020
Publication Date Dec 1, 2020
Deposit Date Sep 6, 2020
Publicly Available Date Oct 4, 2021
Journal Automation in Construction
Print ISSN 0926-5805
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 120
Article Number 103388
DOI https://doi.org/10.1016/j.autcon.2020.103388
Keywords Offsite construction, big data, DFMA, BIM, Big-DOR
Public URL https://uwe-repository.worktribe.com/output/6663743
Publisher URL https://www.journals.elsevier.com/automation-in-construction