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Applied Sciences
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Application of Building Information Modeling in Construction Management
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Application of Building Information Modeling in Construction Management

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 6215

Special Issue Editors

Prof. Dr. Hee Sung Cha

E-Mail Website
Guest Editor
Department of Architectural Engineering, Ajou University, Suwon 06499, Republic of Korea
Interests: Building Information Modeling; construction economics; project performance measurement; smart building technology; sustainable construction
Special Issues, Collections and Topics in MDPI journals
Dr. Shaohua Jiang

E-Mail Website
Guest Editor
Department of Constuction Management, Dalian University of Technology, Dalian, China
Interests: BIM-based construction project life-cycle management; integration of BIM with big data, cloud computing, IoT, mobile communication, etc.; open BIM international
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For decades, the construction industry has been tightly inter-mingled with building information modeling (BIM) to cope with challenging circumstances such as schedule shortages, cost overruns, and quality conformance. Although there is strong demand for applying BIM technology, relatively little attention has been focused on the construction management applications. The aim of this Special Issue is to tackle a wide spectrum of applications of BIM in the realm of construction management, including but not limited to the following:

  • Project management in construction;
  • Integrated digital delivery in construction industry;
  • Digital transformation in the construction industry;
  • Sustainable project management.

Prof. Dr. Hee Sung Cha
Dr. Shaohua Jiang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence in construction
  • building information modeling (BIM)
  • digital transformation
  • sustainable construction

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Published Papers (4 papers)

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Research

30 pages, 3937 KiB  
Article
Dynamic BIM Adoption Impact on Contract Cost Variance Factors Using PLS-SEM Techniques
by Khalid S. Al-Gahtani, Naif M. Alsanabani, Abdullah M. Alsugair, Saad I. Aljadhai and Hatim F. Alotaibi
Appl. Sci. 2024, 14(17), 8017; https://doi.org/10.3390/app14178017 - 7 Sep 2024
Viewed by 771
Abstract
This paper investigates the Building Information Modeling (BIM) adoption impact on the factors of Contract Cost Variance (CCV) over time. The study considers qualitative and quantitative data to identify the most common causes of CCV through pre-tendering. A partial least square-structure model (PLS-SEM) [...] Read more.
This paper investigates the Building Information Modeling (BIM) adoption impact on the factors of Contract Cost Variance (CCV) over time. The study considers qualitative and quantitative data to identify the most common causes of CCV through pre-tendering. A partial least square-structure model (PLS-SEM) procedure was used to develop a causal model and rank CCV factors based on their effect, partially based on prior survey raw data conducted in 2022 and the data from 94 projects. Construction industry experts assessed the prior five-year rate of BIM adoption on construction projects to infer the expected trend in BIM adoption in the future (until 2037). Based on the causal model of CCV factors and the future rates of BIM adoption, the dynamic impact of BIM on CCV factors over time was modeled and analyzed. The analysis shows that BIM reduces CCV over time by improving Estimator Performance (EP), Information Quality (IQ), and contractual procedure (CP). The results showed that the CP, EP, and EF have directly impacted CCV, and the PC and IQ indirectly affect the CCV. This paper considers the temporal aspect, examining how the impact of BIM on CCV factors evolves. This dynamic analysis is crucial for long-term strategic planning in construction management. Full article
(This article belongs to the Special Issue Application of Building Information Modeling in Construction Management)
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25 pages, 14227 KiB  
Article
Multi-Agent Simulation Approach for Modular Integrated Construction Supply Chain
by Ali Attajer and Boubakeur Mecheri
Appl. Sci. 2024, 14(12), 5286; https://doi.org/10.3390/app14125286 - 19 Jun 2024
Viewed by 1519
Abstract
The shift from traditional on-site to off-site construction marks a significant evolution in the construction industry, characterized by increasing levels of prefabrication. These advancements enhance construction efficiency, reduce lead times, and mitigate environmental impacts, leading to modular integrated construction (MiC). However, MiC presents [...] Read more.
The shift from traditional on-site to off-site construction marks a significant evolution in the construction industry, characterized by increasing levels of prefabrication. These advancements enhance construction efficiency, reduce lead times, and mitigate environmental impacts, leading to modular integrated construction (MiC). However, MiC presents complex supply chain challenges, particularly in the transportation of prefabricated components and fully integrated modules. This study addresses these challenges by employing a multi-agent simulation using AnyLogic to optimize MiC transport logistics. The simulation models the interactions of various agents involved in the MiC process to improve operational efficiency and reduce costs. Results demonstrate that using three vehicles per supplier minimizes total transport costs, effectively balancing fixed and variable expenses while eliminating penalties for project delays. The findings highlight the cost efficiency of MiC, showing potential savings due to centralized assembly and optimized logistics. These significantly reduce material transportation and related costs, contributing to the overall efficiency and sustainability of construction projects. These insights underscore the value of multi-agent simulation in addressing the complexities of MiC supply chains. Full article
(This article belongs to the Special Issue Application of Building Information Modeling in Construction Management)
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15 pages, 10632 KiB  
Article
Strategic Integration of Drone Technology and Digital Twins for Optimal Construction Project Management
by Tareq Salem, Mihai Dragomir and Eric Chatelet
Appl. Sci. 2024, 14(11), 4787; https://doi.org/10.3390/app14114787 - 31 May 2024
Cited by 1 | Viewed by 1968
Abstract
This research aims to develop an integrated approach to construction project management by integrating digital technology into monitoring and surveillance operations. Through the use of drones and image processing software, data can be updated regularly and accurately about the progress at the construction [...] Read more.
This research aims to develop an integrated approach to construction project management by integrating digital technology into monitoring and surveillance operations. Through the use of drones and image processing software, data can be updated regularly and accurately about the progress at the construction site, allowing managers and decision makers to have a clear view of the current situation and make effective decisions based on accurate. In addition, this approach contributes to improving communication and coordination among project team members, as data and images can be easily and effectively shared, reducing opportunities for error and enhancing effective interaction among different parties. Using digital twin technologies, planning and forecasting processes can also be improved, as comprehensive analysis of digital data provides a deeper understanding of project dynamics, identifies potential risks, and enables appropriate preventive measures to be taken. In conclusion, the integration of digital twins and the use of drones in construction projects represent a significant step towards achieving smarter and more efficient management, and successfully achieving the defined goals with greater effectiveness. Full article
(This article belongs to the Special Issue Application of Building Information Modeling in Construction Management)
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23 pages, 5144 KiB  
Article
Building an Information Modeling-Based System for Automatically Generating the Assembly Sequence of Precast Concrete Components Using a Genetic Algorithm
by Subin Bae, Heesung Cha and Shaohua Jiang
Appl. Sci. 2024, 14(4), 1358; https://doi.org/10.3390/app14041358 - 7 Feb 2024
Viewed by 1305
Abstract
Facing a significant decrease in economic working processes, Off-Site Construction (OSC) methods have been frequently adopted in response to challenges such as declining productivity and labor shortages in the construction industry. Currently, in most OSC applications, the assembly phase is traditionally managed based [...] Read more.
Facing a significant decrease in economic working processes, Off-Site Construction (OSC) methods have been frequently adopted in response to challenges such as declining productivity and labor shortages in the construction industry. Currently, in most OSC applications, the assembly phase is traditionally managed based on the personal experience and judgment of the site managers. This approach can lead to inaccuracies or omissions, particularly when dealing with a large amount of information on large, complex construction sites. Additionally, there are limitations in exploring more efficient and productive alternatives for rapidly adapting to changing on-site conditions. Given that the assembly phase significantly affects the OSC productivity, a systematic management approach is crucial for expanding OSC methods. Some initial studies used computer algorithms to determine the optimal assembly sequences. However, these studies often focused on geometrical characteristics, such as component weight or spatial occupancy, neglecting crucial factors in actual site planning, such as the work radius and component installation status. Moreover, these studies tended to prioritize the generation of initial assembly sequences rather than providing alternatives for adapting to evolving on-site conditions. In response to these limitations, this study presents a systematic framework utilizing a Building Information Modeling (BIM)–Genetic Algorithm (GA) approach to generate Precast Concrete (PC) component installation sequences. The developed system employs Genetic Algorithms to objectively explore diverse assembly plans, emphasizing the flexibility of accommodating evolving on-site conditions. Real on-site scenarios were simulated using this framework to explore multiple assembly plan alternatives and validate their applicability. Comprehensive interviews were conducted to validate the research and confirm the system’s potential contributions, especially at just-in-time-focused PC sites. Acknowledging a broader range of variables such as equipment and manpower, this study anticipates fostering more systematic on-site management within the context of a digitized construction environment. The proposed algorithm contributes to improving both productivity and sustainability of the construction industry by optimizing the management process of the off-site construction projects. Full article
(This article belongs to the Special Issue Application of Building Information Modeling in Construction Management)
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