Implementation of a novel data-driven approach to optimise UK offsite housing delivery

Ashayeri, I., Goulding, J., Heesom, D., Arif, M., Moore, N., Obi, Lovelin, Ahmed, N. and Saini, M. (2022) Implementation of a novel data-driven approach to optimise UK offsite housing delivery. IOP Conference Series: Earth and Environmental Science, 1101 (4). 042029. ISSN 1755-1307

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Several countries have started to more purposefully apply advanced offsite delivery approaches to meet specific housing shortages. The United Kingdom (UK) is no exception. Whilst the concepts and benefits of Modern Methods of Construction are 'typically' well understood, it is generally accepted that there is a paucity of knowledge on the actual understanding of optimization per se, ergo, the interrelationships between processes, and the wider understanding of 'pooling' [resource management] to promote and maximize synergy - especially to target areas of lag or bottlenecks. In this respect, the research methodological approach adopted in this paper used a single case study to critically evaluate an offsite steel-frame solution for the offsite market to deliver social housing. This approach also evaluated the potential of Generative Design, Discrete Event Simulation, and Digital Twins. Findings of this ongoing research include new opportunities and strategies for these technology-driven solutions, culminating in the development of a new conceptual offsite hub-and-spoke model. These are presented for discussion. This model allows decision-makers to interact with data in order to optimise solutions in line with demand and resource requirements.

Item Type: Article
Additional Information: Funding information: This work acknowledges the contribution and support of UK Research and Innovation (Project Reference: 106166).
Subjects: K100 Architecture
K200 Building
K400 Planning (Urban, Rural and Regional)
Department: Faculties > Engineering and Environment > Architecture and Built Environment
Depositing User: Elena Carlaw
Date Deposited: 06 Jan 2023 16:35
Last Modified: 06 Jan 2023 16:45

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