Study on Construction Cost Estimation Framework Based on BIM Technology

Abstract

BIM, an acronym for Building Information Modelling, is a technology-based strategy that has garnered global recognition for its capacity to transform construction productivity. During the initial stages of construction undertakings, the economic viability and cost analysis wield a substantial influence on project administration and execution. Regrettably, the present cost estimation technique solely takes into account regional information, which results in inaccuracies and the exclusion of other pertinent factors. This thesis introduces a framework for conducting quantitative take-off (QTO) and cost estimation within a BIM environment. The framework includes an approach-based costing tool that addresses cost uncertainty related to the detailed information that defines BIM model element properties. Currently, there are limited available tools that can handle the specifics of QTO and cost estimation using only the BIM platform. Moreover, cost estimators have limited experience in leveraging and managing information within semantic-rich BIM models. The framework aims to manage and quantify unmanaged BIM item parameters as work items to mitigate uncertainties in model-based costing. The approach-based system developed in this thesis helps estimators to perform QTO and cost estimation within a BIM environment. It uses BIM element parameters to drive work elements associated with the parameter host element and captures scope cost not designed into BIM models for the design team. The system comprises four modules, namely Estimating Requirements Defining, Estimating Planning and Structuring, Quantifying and Costing, and Model-Based Historical Costing Data collection. The complete system can generate project cost estimation based on the 3D BIM model. To support this framework, a computational engine has been developed within the current Virtual Design-Build (VDC) model review software. The calculation engine facilitates BIM authoring and BIM data review. A case study was conducted to compare the unit of quantification and cost of the framework to existing methods. The results showed that the model-based system had better costing accuracy than the BIM QTO method and improved speed compared to conventional methods. The framework provides a systematic workflow for performing detailed cost estimation while leveraging the parameters stored in BIM models. Keywords: BIM (building information modeling); construction cost estimation; approach-based construction cost estimation, virtual design build and parameters.