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Advances in Digital Construction Management
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Advances in Digital Construction Management

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 3428

Special Issue Editors

Dr. Silvia Mastrolembo Ventura

E-Mail Website
Guest Editor
Department of Civil, Environmental, Architectural Engineering and Mathematics (DICATAM), University of Brescia, 25123 Brescia, Italy
Interests: process management; digital innovation; design management; construction management
Prof. Dr. Angelo Luigi Camillo Ciribini

E-Mail Website
Guest Editor
Department of Civil, Environmental, Architectural Engineering and Mathematics (DICATAM), University of Brescia, 25123 Brescia, Italy
Interests: process management; digital innovation; design management; construction management

Special Issue Information

Dear Colleagues,

Relevant developments within the field of digital construction management have been proposed in recent years to solve the industry’s challenges regarding the effectiveness of project planning, monitoring and controlling activities, as well as resource management, timely data collection, communication, and the distribution of readily and reliable information.

Some of the critical nodes regarding adopting digital solutions have been recognised as a lack of digital culture and maturity of organisations—from both the demand and supply sides—and the scalability of digital transition; for example, construction SMEs could face barriers when innovating their processes due to budget constraints and the complexity of available digital solutions. At the same time, various sources in the construction phase (including both off-site and on-site construction) provide data from different structured and unstructured formats, including building information modelling, project management applications, sensing technologies, wearable devices, mobile technologies, and so forth. Although significant efforts have been made to digitise construction management, there are still unresolved problems and associated difficulties, such as those in relation to data management.

Therefore, it is evident that the topics dealing with digital construction management entail several challenges and provide the opportunity to research multidisciplinary issues in relation to both technical and process-related factors. Journal articles could cover research topics including construction scheduling, construction work progress monitoring and forecasting, cost analysis, construction quality management, and digital change management. A further domain to be investigated could deal with the role to be played by digital construction management in front of the sustainable and circular economy, also comprehending the compliance with the ESG criteria. For such cases, articles could also discuss the application of solutions and approaches such as, though not limited to, building information modelling, advanced data analytics, linked data, digital twins, extended reality, and sensing technologies.

The Special Issue aims to represent the latest developments in relation to digital construction management and identify potential areas for future research.

Dr. Silvia Mastrolembo Ventura
Prof. Dr. Angelo Luigi Camillo Ciribini
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. Buildings is an international peer-reviewed open access monthly 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 2600 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

  • digital construction management
  • digital change management
  • construction scheduling
  • construction work progress monitoring and forecasting
  • quality management
  • building information modelling
  • digital twins in construction
  • extended reality
  • Internet of Things
  • data analytics
  • linked data approaches
  • digital surveying and mapping technology

Published Papers (5 papers)

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Research

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16 pages, 1636 KiB  
Article
Semantic Enrichment of BIM: The Role of Machine Learning-Based Image Recognition
by Claudio Mirarchi, Maryam Gholamzadehmir, Bruno Daniotti and Alberto Pavan
Buildings 2024, 14(4), 1122; https://doi.org/10.3390/buildings14041122 - 17 Apr 2024
Viewed by 429
Abstract
Building Information Modelling (BIM) revolutionizes the construction industry by digitally simulating real-world entities through a defined and shared semantic structure. However, graphical information included in BIM models often contains more detailed data compared to the corresponding semantic or computable data. This inconsistency creates [...] Read more.
Building Information Modelling (BIM) revolutionizes the construction industry by digitally simulating real-world entities through a defined and shared semantic structure. However, graphical information included in BIM models often contains more detailed data compared to the corresponding semantic or computable data. This inconsistency creates an asymmetry, where valuable details present in the graphical renderings are absent from the semantic description of the model. Such an issue limits the accuracy and comprehensiveness of BIM models, constraining their full utilization for efficient decision-making and collaboration in the construction process. To tackle this challenge, this paper presents a novel approach that utilizes Machine Learning (ML) to mediate the disparity between graphical and semantic information. The proposed methodology operates by automatically extracting relevant details from graphical information and transforming them into semantically meaningful and computable data. A comprehensive empirical evaluation shows that the presented approach effectively bridges the gap between graphical and computable information with an accuracy of over 80% on average, unlocking the potential for a more accurate representation of information within BIM models and enhancing decision-making and collaboration/utility in construction processes. Full article
(This article belongs to the Special Issue Advances in Digital Construction Management)
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29 pages, 3137 KiB  
Article
A Work Breakdown Structure for Estimating Building Life Cycle Cost Aligned with Sustainable Assessment—Application to Functional Costs
by Eduardo Vázquez-López, Jaime Solís-Guzmán and Madelyn Marrero
Buildings 2024, 14(4), 1119; https://doi.org/10.3390/buildings14041119 - 16 Apr 2024
Viewed by 401
Abstract
The tools used for budgeting in the building design phase are still insufficient to address the life cycle of the building in terms of environmental and cost impacts. The main objective of this research is to define a model for extending existing cost [...] Read more.
The tools used for budgeting in the building design phase are still insufficient to address the life cycle of the building in terms of environmental and cost impacts. The main objective of this research is to define a model for extending existing cost databases to accommodate life cycle sustainability assessment. For this, current classification systems are reviewed and a case study has been analysed using the new approach. To this end, a new system of classification of construction information is proposed for the evaluation of early design costs, when data are scarce and the only information available refers to the gross interior area and the plot. The classification organizes the costs in a similar way to the sustainability assessment in EN-15643. A subcategory has been added for revenue, developer costs, and taxes at all stages of the lifecycle. The resulting classification is applied to the functional elements of a secondary school project. In the case study, construction costs represent 21% while the use stage accounts for 72% in a 100-year lifespan. The results show that, starting from generic cost bases, more complex costs and functional costs can be defined at different stages of the life cycle and adjusted to sustainability assessment standards. Full article
(This article belongs to the Special Issue Advances in Digital Construction Management)
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20 pages, 4747 KiB  
Article
An Integrated Data-Driven System for Digital Bridge Management
by Luigi Pallante, Pietro Meriggi, Fabrizio D’Amico, Valerio Gagliardi, Antonio Napolitano, Fabrizio Paolacci, Gianluca Quinci, Mario Lorello and Gianmarco de Felice
Buildings 2024, 14(1), 253; https://doi.org/10.3390/buildings14010253 - 17 Jan 2024
Viewed by 1215
Abstract
Relational databases are established and widespread tools for storing and managing information. The efficient collection of information in a database appears to be a promising solution for bridge management (BM), thus facilitating the digital transition. The Italian regulatory framework on infrastructure operation and [...] Read more.
Relational databases are established and widespread tools for storing and managing information. The efficient collection of information in a database appears to be a promising solution for bridge management (BM), thus facilitating the digital transition. The Italian regulatory framework on infrastructure operation and maintenance (O&M) is complex and is constantly being updated. The current plan for implementing its guidelines envisages that infrastructure managers, also on a regional scale, equip themselves with their own digital database for BM. Within this context, this research proposes an integrated methodology that collects information derived from project documentation, in situ inspections, digital surveys, and monitoring and field tests in a queryable database for digitalising, georeferencing, and creating models of many bridges. Structured query language (SQL) statements are used to efficiently export specific shared information, enabling network cross-analysis. Furthermore, the database represents the source of a geographic information system (GIS) catalogue and the basis for deriving models for building information modelling (BIM). The methodology focuses on the infrastructural context of the Lazio region, Italy, the first beneficiary of the research. Full article
(This article belongs to the Special Issue Advances in Digital Construction Management)
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21 pages, 3189 KiB  
Article
Effective Factors for Implementing Building Information Modeling Using Fuzzy Method to Manage Buildings on Mars
by Amirhossein Javaherikhah and Mercedes Valiente Lopez
Buildings 2023, 13(12), 2991; https://doi.org/10.3390/buildings13122991 - 30 Nov 2023
Cited by 1 | Viewed by 748
Abstract
Ever since mankind has known the world around him and space, he has been trying to find a suitable alternative for his current residence, the Earth. In this research, two main criteria for buildings on Mars and their information management were extracted by [...] Read more.
Ever since mankind has known the world around him and space, he has been trying to find a suitable alternative for his current residence, the Earth. In this research, two main criteria for buildings on Mars and their information management were extracted by checking the library of studies on Mars. These two main criteria are the components of the building and the internal components of the building. The criteria for building components include the health of walls, the health of roofs, meteor protection, the health of facilities, and the health of windows (air exchange), and the internal components of the building, including air temperature, air pressure, ambient oxygen, ambient carbon dioxide, humidity, and the amount of light. These criteria, which were extracted from the library materials, were screened using the fuzzy Delphi method, which is one of the most accurate criteria screening methods and is completed by experts. After the opinions of experts, the criteria of health of walls, health of roofs, health of facilities, rejection, air exchange, ambient temperature, and oxygen content were extracted as final criteria. The results of the experts’ paired questionnaire were analyzed using the fuzzy AHP method, and the health criteria of the walls, the health of the ceilings, and air exchange have the first priority; the criteria of the ambient temperature and oxygen level are the second priority; and the criteria of the facilities are the last priority. These were placed as a suggestion, and it can be stated to the researchers that these priorities should be implemented in the blockchain platform so that the building information management system (BIM) works well in buildings on Mars and against any intrusion or damage. Being resistant, but it seems that the experts considered the components of the building separately from its protective components and put components such as the health of the window as a guarantee of the architecture of Martian buildings and did not include them as part of the main criteria of the research. Also, this research can be used as background for other research in this field. Full article
(This article belongs to the Special Issue Advances in Digital Construction Management)
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Review

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18 pages, 1743 KiB  
Review
Analysis of Digital Twins in the Construction Industry: Practical Applications, Purpose, and Parallel with other Industries
by Vanessa Saback, Cosmin Popescu, Thomas Blanksvärd and Björn Täljsten
Buildings 2024, 14(5), 1361; https://doi.org/10.3390/buildings14051361 (registering DOI) - 10 May 2024
Viewed by 159
Abstract
Digital twins (DTs) have become a widely discussed subject, believed to have the potential to solve various problems across different industries, including Engineering & Construction (E&C). However, there is still significant misconception concerning the definition of DTs and their purpose within E&C. This [...] Read more.
Digital twins (DTs) have become a widely discussed subject, believed to have the potential to solve various problems across different industries, including Engineering & Construction (E&C). However, there is still significant misconception concerning the definition of DTs and their purpose within E&C. This study dives deep into identifying DT applications within E&C and the other prominent industries, i.e., Aerospace & Aviation, Manufacturing, Energy & Utilities, Automotive, Healthcare, Smart Cities, Oil & Gas, and Retail. The main challenges to the evolution of DT practical applications are also analyzed. A combination of a literature review, multi-case study analysis, and comparative analysis compose the deployed methodology. Standardization and a maturity level classification are proposed to drive progress of the adoption of DTs. The distinct aspects of the different industries and their assets are evaluated to the conclusion that DTs are better employed for maintenance of structures within E&C. DTs have become a well-worn topic, but the abundance of complex theoretical frameworks is met with simple or inexistent practical applications. Therefore, the novelty of this study lays in its comprehensive analysis of DT applications and real-world implementations—a departure from the often-theoretical discussions surrounding DTs. Full article
(This article belongs to the Special Issue Advances in Digital Construction Management)
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