Review
Construction & Building Technology
Salma Ahmed, Sameh El-Sayegh
Summary: The paper critically reviews the related literature on project delivery methods, selection methods, and criteria, concluding that project delivery methods evolve slowly compared to the construction industry. It suggests digitally integrated, people-centered, and sustainability-focused features for an evolved project delivery method, highlighting new selection criteria and the potential use of artificial intelligence. The paper also presents a framework illustrating the relationship between PDM variables and fills a gap in the literature by offering a unique perspective on project delivery methods.
Article
Green & Sustainable Science & Technology
Alessandra Montenegro, Marina Dobrota, Marija Todorovic, Teodora Slavinski, Vladimir Obradovic
Summary: The study found that the emotional intelligence of construction project managers significantly influences project success, and that internal and external stakeholder relationships play an important role as mediators. Some components of EI have a more significant influence on stakeholder relationships and project success, while internal and external relationships in different amounts affect components of project success.
Article
Green & Sustainable Science & Technology
Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi
Summary: A robust project selection process is crucial in selecting sustainable projects that meet the needs of an organization or community. The study finds that actual subject matter experts prioritize skill, experience, and technology information transfer over project maturity and uncertainty, unlike the approach of using literature as expert opinions.
Article
Construction & Building Technology
Hongyan Yan, Yuxuan Yang, Xi Lei, Qing Ye, Wenzhen Huang, Ce Gao
Summary: During the changing process of the construction industry in China, the selection of competent managers for construction program management is crucially important. This paper develops a multi-attribute model for construction program manager selection by combining regret theory and the Fuzzy-DEMATEL method. The model considers psychological characteristics of decision makers and relationships between different attributes, providing more comprehensive and scientific construction program manager selections.
Article
Construction & Building Technology
Ali RezaHoseini, Siamak Noori, Seyed Farid Ghannadpour
Summary: The study evaluates the green construction supply chain using a mathematical model while considering environmental impacts and uncertain factors. The paper also discusses the synergy between supplier selection and project planning, as well as operational challenges in the construction industry.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Engineering, Industrial
Guofeng Ma, Shan Jiang, Ding Wang
Summary: The purpose of this study is to explore how different purposes of social media use affect project performance from a project manager's perspective in the construction industry. The findings suggest that both work-oriented and socialization-oriented social media use can promote knowledge acquisition and project social capital, leading to positive impacts on project performance. Additionally, the study identifies the moderating role of information overload on the relationship between social media use and knowledge acquisition.
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
(2022)
Article
Mathematics
Bogdan Walek, Ondrej Pektor, Radim Farana
Summary: This paper presents a novel approach for evaluating suitable job applicants, specifying requirements and tools used. The system utilizes fuzzy expert systems and variant multi-criteria analysis methods, allowing for easy adjustment of selection criteria importance based on different situations. Its emphasis on an explanatory module facilitates the system's usability.
Article
Management
Shaoze Fang, Lianying Zhang
Summary: This study investigates the impact of social identification on ego depletion of project managers through interorganizational and intraorganizational tasks. Findings suggest that strong project identification leads to increased ego depletion, while strong organizational identification reduces ego depletion. Additionally, the effect of social identification on ego depletion is stronger in high project complexity situations.
INTERNATIONAL JOURNAL OF PROJECT MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Shabnam Arabpour, Gilbert Silvius
Summary: The implementation of higher standards for sustainability poses a challenge to the construction industry. This study aims to fill the gap in the literature by investigating the perceived effectiveness and ease of sustainability interventions for project managers. Through a quantitative survey-based approach, ten interventions focusing on communication, guidelines and regulations, and the supply chain were identified as a minimum baseline for developing more sustainable construction projects.
Article
Construction & Building Technology
Taylan Terzioglu, Gul Polat, Harun Turkoglu
Summary: Selecting the appropriate formwork system is crucial for the success of reinforced concrete building construction projects. This study identifies five latent factors in the selection criteria for formwork system, including FWS-FWF characteristics, structural design, local conditions, cost, and performance indicators. Structural equation modelling analysis confirms the interrelationships between these latent factors and their impacts on the project.
Article
Computer Science, Artificial Intelligence
Chong Wu, Yiqun Jia, David Barnes
Summary: In recent years, there has been an increasing awareness of environmental protection and social responsibility, which has made sustainable supply chain development and the selection of sustainable suppliers more important. This research proposes an intelligent SSS criteria system construction model that is product-category-oriented, using the random forest algorithm and recursive feature elimination cross-validation method. The model can construct the optimal SSS criteria system while considering the combination effect of the whole criteria system.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Amin Mahmoudi, Mehdi Abbasi, Xiaopeng Deng
Summary: The study proposes a framework to help project-oriented organizations select the most appropriate portfolio based on organizational resilience strategy, by identifying portfolios, clustering projects using Elbow and Fuzzy C-Means methods, scoring projects with stakeholders' opinions and Robust Ordinal Priority Approach, and selecting the best portfolio linked to the organizational resilience strategy.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Construction & Building Technology
Taylan Terzioglu, Gul Polat, Harun Turkoglu
Summary: This study examines the FWS selection criteria in building construction projects, comparing the perspectives of different construction professionals and companies, as well as investigating the impact of building structural parameters on the FWS selection criteria. The findings highlight the importance of understanding the perspectives of various groups of construction professionals and the role of structural parameters in FWS selection criteria.
Article
Construction & Building Technology
Hui Liu, Hang Zhang, Ruixiang Zhang, Hongbing Jiang, Qianqian Ju
Summary: This study constructed a competence model of CPM in the digital era, named the Diamond model, through data mining method. The Diamond model includes nine key competences, with digital capability as a newly emerging one, classified into three levels of technology, knowledge, and management. Industry requirements mainly focus on technology and knowledge levels, providing a reference for recruitment strategies, career development, and talent gap bridging. Introducing digital capability into the CPM competence system also sets a solid foundation for further research.
Article
Sport Sciences
Isabella Wiedmann, Guillaume Weerts, Klara Brixius, Anna Seemueller, Justin Mittelstaedt, Nolan Herssens, Tobias Weber
Summary: This study aims to investigate the inclusion of physical performance tests (PPTs) in future astronaut recruitments and determine which areas of physical performance should be tested. The results indicate that the majority of experts support the inclusion of PPTs for both physically impaired and unimpaired astronaut candidates.
Article
Construction & Building Technology
Amin Assadzadeh, Mehrdad Arashpour, Ioannis Brilakis, Tuan Ngo, Eirini Konstantinou
Summary: This study introduces a framework for synthetically generating large and accurately annotated images for excavator pose estimation, utilizing a game engine and domain randomization. Experimental results show that the model trained on synthetic data can achieve comparable performance to the one trained on real images.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Computer Science, Interdisciplinary Applications
Eva Agapaki, Ioannis Brilakis
Summary: This paper tackles the challenge of automatically generating object oriented geometric digital twins of industrial facilities efficiently. By using instance segmentation algorithms, the method presented in this paper is able to automatically segment industrial point cloud shapes and provide a foundation for the efficient generation of gDTs in cluttered industrial environments.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2021)
Article
Construction & Building Technology
Eva Agapaki, Ioannis Brilakis
Summary: The CLOI framework generates accurate individual labeled point clusters of the most important shapes in existing industrial facilities with minimal manual effort. It uses deep learning and geometric methods to segment points and instances, achieving 82% class segmentation accuracy and estimated time savings of 30% compared to current practices. CLOI is the first framework of its kind to achieve geometric digital twinning for important objects in industrial factories, laying the foundation for further research in semantically enriched digital twins.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2021)
Article
Environmental Sciences
Sotirios A. Argyroudis, Stergios Aristotels Mitoulis, Eleni W. Chatzi, Jack W. Baker, Ioannis Brilakis, Konstantinos Gkoumas, Michalis Vousdoukas, William Hynes, Savina Carluccio, Oceane Keou, Dan M. Frangopol, Igor Linkov
Summary: Building climate-resilient infrastructure is crucial for economic prosperity and social cohesion, and emerging digital technologies have the potential to enhance this resilience. However, there are challenges and gaps that need to be addressed.
CLIMATE RISK MANAGEMENT
(2022)
Article
Engineering, Civil
John Patrick Fitzsimmons, Ruodan Lu, Ying Hong, Ioannis Brilakis
Summary: The UK spends billions of pounds on infrastructure construction works annually, but more than half of them are delayed, causing stakeholders' interests to be compromised. This research introduces a hybrid method to improve the accuracy of risk analysis and prediction of project delays, by combining machine intelligence with a large database of completed infrastructure construction projects in the UK. The results show a 54.4% increase in accuracy in predicting project delays compared to traditional methods.
JOURNAL OF INFORMATION TECHNOLOGY IN CONSTRUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Ying Hong, Haiyan Xie, Vahan Hovhannisyan, Ioannis Brilakis
Summary: Construction schedules are crucial for project success, but they often require experienced schedulers. This study proposes a graph-based method to find the most time-efficient construction sequence from historic projects, improving scheduling productivity and accuracy. Results indicate that earthwork sequences are the least time-efficient and frequent sequences learned from past projects are closer to the actual schedule.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Construction & Building Technology
Haiyan Xie, Ying Hong, Ioannis Brilakis
Summary: This research investigates the obstacles in project execution and proposes a decision tree model to map user needs and trace workflows. The results show that the most urgent needs in time-related risk management are decision support tools, preparation assistance for risk communication, and generation of risk mitigation scenarios.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Ying Hong, Haiyan Xie, Gary Bhumbra, Ioannis Brilakis
Summary: This study proposes an ontology-based Recurrent Neural Network approach to bi-directionally translate between human written language and machinery ontological language. Experimental results show that the proposed approach has good performance in text generation accuracy, machine readability, and human understandability.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Construction & Building Technology
Yuandong Pan, Alexander Braun, Ioannis Brilakis
Summary: This paper introduces a novel method to enrich geometric digital twins of buildings by capturing important entities from the electrical and fire-safety domain. The method fuses laser scanning and photogrammetry to capture relevant objects, recognize them in 2D images, and map them to a 3D space. The resulting digital twin contains geometric information, semantic information, and useful text information, and can be used for condition monitoring, facility maintenance, and management.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Construction & Building Technology
Mershack O. Tetteh, Amos Darko, Albert P. C. Chan, Amirhosein Jafari, Ioannis Brilakis, Weiwei Chen, Gabriel Nani, Sitsofe Kwame Yevu
Summary: Green retrofitting of existing buildings (GREB) is an effective approach to reduce energy consumption and carbon emissions and improve people's well-being. However, there is a lack of comprehensive investigation into the value of research in this field. This study uses a scientometric review technique to analyze global research on GREB and provides insights for future research. The findings reveal the focus on energy efficiency retrofitting and the declining importance of occupant behavior and indoor environmental quality in current GREB practices.
ENERGY AND BUILDINGS
(2022)
Article
Construction & Building Technology
Ying Hong, Haiyan Xie, Eva Agapaki, Ioannis Brilakis
Summary: The construction industry has long struggled with delays and cost overruns. This paper proposes a graph-based automated scheduling (GAS) method to capture, store, and reuse the tacit knowledge in construction schedules. The GAS method was validated on two case studies and proved to be more accurate in generating construction schedules compared to planned schedules.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Maciej Trzeciak, Kacper Pluta, Yasmin Fathy, Lucio Alcalde, Stanley Chee, Antony Bromley, Ioannis Brilakis, Pierre Alliez
Summary: This paper introduces a periodically collected data set on a construction site, aiming to evaluate the performance of SLAM algorithms used by mobile scanners or autonomous robots. The data set includes ground-truth scans, spatially registered and time-synchronized images, lidar scans, and inertial data. The paper also demonstrates how to measure the accuracy of SLAM algorithms against the ground-truth trajectory using a popular software package. This is the first publicly accessible data set of sequentially collected data on a construction site.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2023)
Review
Chemistry, Analytical
Viktor Drobnyi, Zhiqi Hu, Yasmin Fathy, Ioannis Brilakis
Summary: Most existing buildings were built based on 2D drawings, but building information models have become prevalent in recent years. However, it will take a long time for these models to be widely adopted in all existing buildings. This paper reviews the state-of-the-art practice and research for constructing and maintaining geometric digital twins, and proposes a new geometry-based object class hierarchy to prioritize automation.
Article
Computer Science, Interdisciplinary Applications
Maciej Trzeciak, Ioannis Brilakis
Summary: In this paper, a dense 3D reconstruction pipeline is proposed to improve the resolution of point clouds captured by handheld scanners. Time-synchronized and spatially registered images and lidar sweeps are fused using spatial AI methods to generate higher resolution dense scans for progressive reconstruction. The results showed a reduction of 11% in overall point cloud noise and an increase in density by approximately six times.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Eva Agapaki, Ioannis Brilakis
Summary: This paper presents a framework called CLOI, which accurately generates labeled point clusters of important shapes in existing industrial facilities with minimal manual effort. CLOI combines deep learning and geometric methods to segment points into classes and individual instances. Experimental results show that CLOI can reliably segment complex and incomplete point clouds of industrial facilities, achieving 82% class segmentation accuracy. Compared to current practices, the proposed framework can save an estimated 30% of time on average.
COMPUTING IN CIVIL ENGINEERING 2021
(2022)
