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

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Title: A critical review of digital value engineering in building design towards automated construction.
Authors: Khan, Abdul Mateen1 (AUTHOR), Alaloul, Wesam Salah1 (AUTHOR) wesam.alaloul@utp.edu.my, Musarat, Muhammad Ali1,2 (AUTHOR)
Source: Environment, Development & Sustainability. Jul2026, Vol. 28 Issue 7, p17587-17632. 46p.
Subject Terms: *Value engineering, *Building information modeling, *Industrialized building, *Sustainability, *Data integration, *Building design & construction, *Algorithms, *Machine learning
Abstract: 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 However, outdated manual procedures limit integration and consistency in construction projects, necessitating the evaluation of VE automation.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. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194936962
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Label: Title
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  Data: A critical review of digital value engineering in building design towards automated construction.
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  Data: <searchLink fieldCode="AR" term="%22Khan%2C+Abdul+Mateen%22">Khan, Abdul Mateen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Alaloul%2C+Wesam+Salah%22">Alaloul, Wesam Salah</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wesam.alaloul@utp.edu.my</i><br /><searchLink fieldCode="AR" term="%22Musarat%2C+Muhammad+Ali%22">Musarat, Muhammad Ali</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Environment%2C+Development+%26+Sustainability%22">Environment, Development & Sustainability</searchLink>. Jul2026, Vol. 28 Issue 7, p17587-17632. 46p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Value+engineering%22">Value engineering</searchLink><br />*<searchLink fieldCode="DE" term="%22Building+information+modeling%22">Building information modeling</searchLink><br />*<searchLink fieldCode="DE" term="%22Industrialized+building%22">Industrialized building</searchLink><br />*<searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+integration%22">Data integration</searchLink><br />*<searchLink fieldCode="DE" term="%22Building+design+%26+construction%22">Building design & construction</searchLink><br />*<searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10668-024-05595-1
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 46
        StartPage: 17587
    Subjects:
      – SubjectFull: Value engineering
        Type: general
      – SubjectFull: Building information modeling
        Type: general
      – SubjectFull: Industrialized building
        Type: general
      – SubjectFull: Sustainability
        Type: general
      – SubjectFull: Data integration
        Type: general
      – SubjectFull: Building design & construction
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Machine learning
        Type: general
    Titles:
      – TitleFull: A critical review of digital value engineering in building design towards automated construction.
        Type: main
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          Name:
            NameFull: Khan, Abdul Mateen
      – PersonEntity:
          Name:
            NameFull: Alaloul, Wesam Salah
      – PersonEntity:
          Name:
            NameFull: Musarat, Muhammad Ali
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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              Value: 1387585X
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              Value: 28
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Environment, Development & Sustainability
              Type: main
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