Digital Application of Construction Project Cost Risk Control and Management Based on BIM Technology

被引:0
|
作者
Li, Xiufang [1 ]
Jia, Xiaorui [1 ]
Huang, Mingqiang [1 ]
机构
[1] Xiamen University of Technology, Fujian, Xiamen,361024, China
关键词
Architectural design - Budget control - Cost benefit analysis - Cost engineering - Investments - Project management - Structural design;
D O I
10.2478/amns-2024-0529
中图分类号
学科分类号
摘要
The core objective of this study is to explore the application of BIM technology in the whole process of cost management of construction projects and to assess the project risk. The study covers the key stages of project planning, design, transaction and construction, and focuses on analyzing the cost management process of investment decision, design estimate, transaction and construction. Through questionnaire surveys and expert interviews with 72 valid samples, this study collects data on green building and analyzes the quality of the risk assessment data. Through questionnaire survey and expert interviews with 72 good samples, this study collects data on green building and analyzes the quality of the risk assessment data. In establishing the BIM-based project cost risk model, the study analyzes the management elements of BIM and IPD in detail, including the quantification of technical and management components. three case projects show that the application of BIM and IPD technologies in different projects has different focuses, and produces other management effects. for example, the number of engineering changes (e.g., the number of changes to the project) exhibited by the project B For example, the number of project changes (NCO) is 35, the cost change rate (COP) is 0.93%, the duration change rate (DCP) is -10.25%, and the number of contract negotiations (NRFI) is 6. The risk evaluation model is applied in a mixed-use project in Xiamen, China, and the results of the simulation experiments show that the method is effective in realizing the risk assessment of the construction project, and the clustered nature of the output features is good. The average value of the risk fuzzy variable is 0.576, and the minimum value is 0.192. © 2023 Xiufang Li, Xiaorui Jia and Mingqiang Huang, published by Sciendo.
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