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Feasibility of BIM-enabled Generative AI Platform for Data-driven Incremental Productivity Enhancement of Construction Cost Management (BIM-GAI)

Feasibility of BIM-enabled Generative AI Platform for Data-driven Incremental Productivity Enhancement of Construction Cost Management (BIM-GAI)
支持 BIM 的生成式 AI 平台用于数据驱动的增量式生产力增强建筑成本管理 (BIM-GAI) 的可行性
批准号:
10079600
负责人:
金额:
$6.33万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
已结题
起止时间:
2023 至 --

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英文摘要
The application of Generative Artificial Intelligence (GAI) can enhance productivity in cost management in construction SMEs by automating estimating cost plans, measured quantities, and predicting valuation and cashflows outcomes based on the designs, specifications, site information, and other non-graphical input variables. Currently, the UK BIM framework and 2011 Mandate have been ineffective in supporting SMEs' productivity using BIM with only 57% uptake (UKBIMA, 2021). Thus, evidencing a shortfall in the productivity of UK construction SMEs. BIM update has been limited in UK construction SMEs mainly because of cost and ease of use. Recent AI and machine learning developments present new opportunities to make BIM easier to apply in UK construction SMEs. GAI algorithms can potentially reduce errors and rework synonymous with a cost overrun in construction estimating and budgeting processes through deep learning-based generative models such as rule-based generative models within BIM through automation. The time required in producing bills of quantities, cost plans, valuation, final accounts and associated textual documents can be reduced significantly with a full version of BIM-enabled GAI. Construction cost management processes in the UK have been critiqued for errors in estimation and budgeting. Large-scale cost overruns in infrastructure projects have stifled the growth of SME construction companies in the UK. Cost management errors have led to rework and claims, impeding organisations' productive outputs. Furthermore, 69% of construction works experience cost overruns in the UK, creating productivity difficulties in construction SMEs (KPMG, 2023).Consequently, GAI has not been implemented in the construction management process to optimise productivity and mitigate incidents of errors and overruns. Hence, construction cost management needs to advance towards the new models of productivity improvement in the planning and construction stages. The application of GAI in the construction cost management process of SME companies in the UK will empower productivity through BIM. This feasibility study will study the pilot integration of BIM and GAI, datasets, ethical considerations, regulations, interfaces, GAI requirements user interface (UI) and user experience (UX). Furthermore, GAI has not been applied in BIM cost management-based tools such as BlueBeam, CostX and PlainSwift. **This feasibility study intends to use existing construction cost datasets from an SME construction company to develop a systems architecture, a Foundation large language learning model (FLM) and a pilot web-based integration of BIM and GAI to automate the cost estimation to engender productivity.**
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