A critical review of digital value engineering in building design towards automated construction

被引:0
|
作者
Khan, Abdul Mateen [1 ]
Alaloul, Wesam Salah [1 ]
Musarat, Muhammad Ali [1 ,2 ]
机构
[1] Univ Teknol PETRONAS, Dept Civil & Environm Engn, Bandar Seri Iskandar 32610, Perak, Malaysia
[2] Univ Teknol PETRONAS, Inst Autonomous Syst, Offshore Engn Ctr, Bandar Seri Iskandar 32610, Perak, Malaysia
关键词
Value engineering; Construction optimization; BIM; Digital visualization; Automated tracking; Lifecycle integration; INFORMATION MODELING BIM; ENVIRONMENTAL-QUALITY IEQ; VALUE MANAGEMENT; PROJECTS; OPTIMIZATION; METHODOLOGY; PERFORMANCE; BENEFITS; COST; IMPLEMENTATION;
D O I
10.1007/s10668-024-05595-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Value engineering (VE) has the potential to increase sustainability in buildings by optimizing function-to-cost ratios. However, outdated manual procedures limit integration and consistency in construction projects, necessitating the evaluation of VE automation. This review examines VE automation in building design and construction. A systematic analysis of 664 publications from major databases was conducted, yielding 136 relevant articles. Bibliometric analysis using descriptive statistics and keyword mapping identified key VE methodologies and building types. Key technologies in VE automation include BIM, advanced algorithms, and data integration. These tools enable automated layout generation, material selection, and technical configurations, enhancing value optimization. BIM serves as a central data platform, improving stakeholder collaboration. Algorithms rapidly generate design alternatives, optimizing decision-making. Data integration ensures accuracy across project stages. Challenges include incomplete databases, lifecycle integration issues, and resistance to change. A continuous digital VE framework is proposed to address these barriers. This framework emphasizes the seamless integration of VE tools with BIM platforms, enhancing interoperability and user engagement. In the future, there will be further opportunities to advance VE automation through the creation of more advanced predictive analytics algorithms, more real-time data processing capabilities, and increased interoperability amongst various digital tools. The integration of machine learning and artificial intelligence into VE processes is also suggested to further enhance optimization and efficiency in construction projects.
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页数:46
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