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Blockchain technology has shown potential in enhancing project performance by instilling trust in data sharing among stakeholders, thereby encouraging the stakeholders to ensure a strategic acquisition and resource management through procurement activities. However, despite the recent research efforts on blockchain in the construction sector, there is a lack of knowledge of the status quo in that barely any research investigated the synergy of blockchain and procurement by recognizing the inextricable linkage between procurement management and project delivery system. This paper conducts a systematic review of 54 articles to assess blockchain's potential in addressing issues inherent in the current organizational structures and collaborative efforts. Findings offer profound insight into the current landscape of procurement-specific blockchain research, highlighting areas needing attention. This paper identified opportunities in construction procurement by investigating the extent to which the technology is integrated into the current project management context emphasizing integration and collaboration. [Display omitted] • This paper evaluates the potential of blockchain within the realm of procurement processes and methods. • This paper assesses whether blockchain is employed to coordinate the workflow and promote integration. • This paper presents specific facets of construction procurement that need attention. • This paper offers profound insight into the current landscape of blockchain research in procurement [ABSTRACT FROM AUTHOR]

This paper analyzes the evolution of Artificial Intelligence (AI) in the construction industry from 2014 to 2023, focusing on enhancing security, communication, and maintenance. It combines in-depth analysis of 121 papers with visualizations of 507 articles from major databases such as SCOPUS, IEEE, ACM, Science Direct, and Google Scholar to map AI advancements in construction. The study found that security is established as a mature research domain, whereas communication and maintenance are at comparatively earlier stages of development. Specifically, the analysis reveals a shift from Radio Frequency Identification (RFID) to more sophisticated technologies such as Internet of Things (IoT), Virtual Reality (VR), blockchain, Building Information Modeling (BIM), and digital twins, which significantly improve security. Communication and maintenance have also evolved towards greater digital integration and predictive analytics. The integration of AI innovations with human expertise is emphasized as a strategic direction to enhance decision-making and operational efficiency in construction. [Display omitted] • Review the development of AI-driven studies in the construction sector. • AI evolution in construction security, communication and maintenance (2014–2023). • AI shifts to IoT, VR, blockchain, BIM, digital twins. • Challenges in data management, AI integration noted. • Predictive analytics, ethical AI use in future directions. [ABSTRACT FROM AUTHOR]

Despite ongoing research in Architectural, Engineering, Construction and Operations (AECO), little is understood about BIM's interaction with its adoption process. This paper conducts a comprehensive scoping review that utilises secondary data to systematically map the existing literature on the adoption of BIM within AECO organisations. A literature review identified 146 papers on BIM in AECO organisations, categorising them into 46 on pre-adoption, 85 on post-adoption, and 15 on both phases. Findings reveal a tendency towards a 'tunnel vision', isolating a single organisational aspect or adoption phase. However, the study finds that BIM significantly interacts with various organisational elements, such as environment, power dynamics, social structure, and culture, necessitating comprehensive changes and strategies both before and after adoption. Advocating for a holistic approach, the study emphasises integrating change management, continuous learning, and ongoing improvement in BIM implementation. This perspective is a significant contribution to understanding BIM's multifaceted impact in AECO organisations. [Display omitted] • Challenges in fully transitioning to BIM, result in untapped potential. • The organisational environment, power dynamics, social structure, and culture for BIM adoption are currently overlooked. • Reveals the intricate interaction of organisations and BIM throughout the transformative process. • Identifies knowledge gaps, provides a research agenda cube, offers valuable guidance for future studies. [ABSTRACT FROM AUTHOR]

Radio Frequency Identification (RFID) systems have remarkable potential to be used in the supply chain management systems of the construction industry. RFID's ability to identify, track and locate objects provides tremendous flexibility in planning and operation of the industry. Consequently, RFID systems can contribute to on-time project completion, cost savings, enhanced reputation, and avoidance of regulatory fines. Moreover, RFID enhances visibility into inventory, equipment, and workforce, ensuring real-time safety measures. This paper conducts an in-depth analysis of state-of-the-art RFID detection and localization techniques, identifying gaps specific to the construction sector. The paper proposes the integration of emerging technologies, with a particular focus on the Internet of Things (IoT) and security mechanisms. This integration aims to solve challenges in using RFID systems in the construction industry's supply chain. It promises to enhance efficiency, security, and effectiveness of RFID technology, leading to a more efficient and resilient supply chain management system. [Display omitted] • Provides an in-depth analysis of state-of-the-art RFID detection and localization techniques, uncovering gaps and limitations specific to construction, and proposing innovative solutions. • Discovers how RFID, combined with emerging technologies like IoT, enhances supply chain efficiency and resilience, addressing specific challenges unique to the construction sector. • Addresses security concerns related to RFID localization and proposes a practical solution tailored to the construction industry's needs. [ABSTRACT FROM AUTHOR]

The construction industry is facing serious challenges, such as labor shortage and safety hazards. Construction robots can perform dangerous and repetitive tasks instead of workers. However, complex construction tasks require multi-robot collaboration, which needs efficient task allocation. This paper describes a two-stage task allocation method using an improved Genetic Algorithm (GA) for multiple construction robots. First, a construction task decomposition and grouping method under construction constraints is established, using a steel structure as example. Second, a Multi-Robot Construction Task Allocation (MRCTA) model is developed by modeling construction robots and tasks. Third, the MRCTA problem is divided into two stages, i.e., determining the optimal construction robot group for each task and the best task sequence for each robot group. Finally, a simulated experiment was designed and conducted. The results show that the method can efficiently find optimal solutions and the improved GA can enhance the diversity to achieve well-adapted solutions. • A construction task decomposition and grouping approach is developed considering three constraints. • The Multi-robot Construction Task Allocation (MRCTA) model is established considering multiple objectives. • A two-stage task allocation method for multiple construction robots is proposed based on an improved genetic algorithm. • A test is conducted to validate the feasibility of the proposed method, which is well-adapted. [ABSTRACT FROM AUTHOR]

Abstract Cross-industry learning of the Toyota production system has inspired the precast factories in the construction industry to adopt an automated guided vehicle (AGV)-based flow production system for the manufacturing of their modular prefabricated products. Compared to the production process of automobiles, the manufacturing process of modular prefabricated products is very unbalanced leading to a large pool of queues. And additionally, after some operations, settling is needed. Hence, due to these unique features, facility layout is a crucial element that needs to be well planned in order to achieve a feasible and efficient system. In this regard, this paper proposes an approach to plan the facility layout of the investigated AGV-based modular prefabricated manufacturing system. The paper firstly gives an optimization method for the size arrangement of the workstation area and the storage area. There are two conflicting objectives in the optimization model: one is to minimize the production time and the other is to maximize the workstation utilization. A simulation based non-dominated sorting genetic algorithm is developed to solve the model. Then, the paper proposes a heuristic method to guide the placement, reshuffle, and retrieval of the modular prefabricated products in the storage area. According to the heuristic, there is no need of dedicated paths for AGVs. The storage area can be fully occupied by the work-in-progress and the AGV traveling paths are dynamically generated. And thirdly, the paper is also able to provide a suitable size of the AGV fleet which is able to accomplish the moving tasks in time. The experimental test on an industrial case shows the potential of the proposed planning approach to guide the real practice. Highlights • Workstation number, production schedule, and AGV fleet size are generated. • Multiple solutions are obtained according to the objectives of time and utilization. • The placement, reshuffle and retrieval of jobs in the storage area are guided. • No dedicated path for AGV travelling. • Workstation operations are adaptable to the needs of their incoming jobs. [ABSTRACT FROM AUTHOR]

Abstract Text mining is a fast-growing area of research, due to its ability to discover valuable information and getting insights hidden in plain texts. The aim of this paper is to apply text mining in order to analyze construction project contracts and visually analyze project correspondence. Analyzing construction contract helps project parties to figure out their obligations and reduce time and effort needed for contract analysis. Additionally, performing text mining to the contract helps in extracting critical keywords that should be monitored closely in the correspondence. On the other hand, applying text mining for project correspondence helps in gaining an understanding regarding the communication nature and sentiment between project parties. Thus, the paper develops a Dynamic Text Analytical model for Contract and Correspondence "DTA-CC" through utilizing BIM. The DTA-CC model assists project parties to explore texts and get insights regarding the project performance. The specific objectives of this study are to 1-perform a text analytics of the construction project contract, 2- integrate project correspondence within the BIM model and 3- develop a text analytical model based on project's correspondence to monitor the project performance. The DTA-CC model is validated by applying a case study for a construction project located in Cairo, Egypt. The case study found that there is a lot of hidden information in the project's raw data. Moreover, it is crucial to monitor raw data in order to achieve a successful project. This study extends the existing knowledge by proposing a novel methodology to extract meaningful patterns from construction projects data. Highlights • Applying text analytics for construction project contract, in order to visually analyze the contract and efficiently figuring out each party obligation. • Integrating the construction project correspondence within the BIM model by developing a correspondence template. • Performing text analytics for project correspondence, to gain an understanding regarding the communication nature and sentiment between project parties. [ABSTRACT FROM AUTHOR]

Abstract Design coordination and conflict detection with BIM are one of the most frequent and valued uses of BIM in the construction sector. However, our observations of design coordination meetings indicate that even when BIM tools are readily available, practitioners frequently revert back to 2D digital and paper-based drawings and rarely interact with BIM tools on their own without the help of a BIM Coordinator. To better understand the challenges of interacting with BIM, we conducted a long term ethnographic study of a project team performing design coordination using state of the art BIM tools. We developed a taxonomy to represent the relationships between goals, artifacts, interactions and transitions for BIM-based design coordination processes. This research extends this prior work by analyzing the frequency of interactions with different design artifacts, characterizing interactions with state of the art BIM tools, and identifying the motivation behind interactions with design artifacts. An important contribution of this research is the identification and characterization of the transitions participants had between design artifacts and views, which has previously not been studied in depth. We identified four major interactions with design artifacts, including preparation, annotation, navigation, and recording. We identified six categories of goals for interacting with design artifacts, including prepare, grab attention, visualize, inspect, document, and query. We discuss our findings and provide possible design considerations to address the challenges we observed. Highlights • A study of how and why practitioners interact with artifact in design coordination • Long term ethnographic study of project teams in design coordination using BIM • Developed a taxonomy characterizing interactions, goals & transitions with artifacts • Identification and characterization of the transitions between design artifacts and views • Found 2D paper, 2D digital & 3D digital information, utilized equally during coordination [ABSTRACT FROM AUTHOR]

Graph Neural Networks (GNNs) have emerged as a promising solution for effectively handling non-Euclidean data in construction, including building information models (BIM) and scanned point clouds. However, despite their potential, there is a lack of comprehensive scholarly work providing a holistic understanding of the application of GNNs in the construction domain. This paper addresses this gap by conducting a thorough review of 34 publications on GNNs in construction, presenting a comprehensive overview of the current research landscape. By analyzing the existing literature, this paper aims to identify opportunities and challenges for further advancing the application of GNNs in construction. The findings from this review shed light on diverse approaches for constructing graph data from common construction data types and demonstrate the significant potential of GNNs for the industry. Moreover, this paper contributes to the existing body of knowledge by increasing awareness of the current state of GNNs in the construction industry and offering practical recommendations to overcome challenges in real-world practice. [Display omitted] • A systematic review of GNNs research and applications in the construction industry • Identification of GNNs potential in handling the non-Euclidean data commonly found in construction activities. • Various approaches to developing graph data from common data types in construction • Discussion of current applications and potential of GNNs in construction, as well as its challenges and opportunities. [ABSTRACT FROM AUTHOR]

The path to implementing successful, productive, and sustainable off-site 3D concrete printing building systems is unclear. To provide clarity, this paper aims to determine targeted actions for stakeholders in the construction industry. A systematic literature review and a bibliometric analysis are conducted to identify driver-barriers of Off-site Construction (OSC) and 3D Concrete Printing (3DCP). Thirty-four stakeholder-linked targeted actions are determined and divided into industry, organisational, project, and system levels. The findings indicate the success of off-site 3DCP building systems is not exclusively dependent on the system performance and a variety of actions are required from multiple stakeholders. This paper provides a theoretical foundation for practical actions and further research to implement off-site 3DCP building systems in local construction industries. • Drivers and barriers are identified with a systematic literature review on off-site construction and 3D concrete printing. • A bibliometric analysis using VOSviewer software is performed. • Stakeholders in off-site 3DCP are identified. • Stakeholder-linked targeted actions which aim to enable the development of off-site 3DCP building systems are derived [ABSTRACT FROM AUTHOR]

Work-related musculoskeletal disorders are the primary cause of nonfatal occupational injuries in the construction industry. Accurate ergonomic assessment is essential to reduce the risk of work-related injuries. Repetitive work significantly contributes to musculoskeletal injuries, and various ergonomic evaluation methods have specific criteria for assessing repetitive actions. However, most existing methods for repetitive motions primarily rely on subjective and time-consuming manual observation. To accurately assess ergonomic risk, an automatic and precise method is required to count repetitive actions in construction work. This poses a challenge due to the unstructured nature of construction actions and their varying frequencies and cycles. This paper aims to overcome these challenges by identifying repetitive unstructured actions using posture self-similarity comparison and predicting construction actions' length using a transformer layer. Experimental results demonstrated that the proposed method achieved a 91.5 % accuracy in identifying repetitive actions. The research results will contribute to the promotion of accurate ergonomics evaluation of automation. [Display omitted] • Extracting worker's skeletal model from videos to represent action features. • Utilizing the self-similarity matrix to calculate repetition action features. • Using the classifier and regressor to recognize repetitive actions and predict cycle lengths. • Applying repetition action counting results for worker ergonomic assessment. [ABSTRACT FROM AUTHOR]

Despite Digital Twins' (DTs) growing popularity in the Architecture, Engineering, Construction and Operations sector, currently, only a limited number of studies have focused on the applicability and potential offered by DT to deal with the whole Construction Supply Chain (CSC) challenges, justifying the significance of the present study. As a response to provide a holistic insight into DT's contribution to overcoming CSC challenges, this paper follows an extensive literature review approach. This review aims explicitly to identify the existing applications of DT in dealing with current CSC challenges and explore its possible contributions by investigating examples of other industries that adopted DT to tackle similar challenges. Firstly, it utilises Scopus as a database to collect CSC-related data. Subsequently, it employs VOSviewer to extract and visualise CSC hotspots. Finally, this review conducts extensive discussions to identify the CSC challenges around the identified hotspots and the DT-provided solutions. [Display omitted] • Comprehensive investigation of DT applications over the whole CSC rather than single CSC stages. • Identifying current CSC hotspots and interpreting them into overarching themes. • Finding challenges within each overarching CSC theme by investigating deficiencies specific to their included hotspots. • Conducting an interdisciplinary review to find DT-provided solutions that can address the CSC challenges. • Dissecting the DT frameworks and developed workflows to illuminate how this technology has dealt with the challenges. [ABSTRACT FROM AUTHOR]

Conflicts in construction projects have always been a major problem. Unless an alternate resolution mechanism is spelled out in the contract, these disputes are typically resolved in court, which might be time consuming and financially substantial. This paper represents a continuation in a research focused on creating robust methodologies for legal decision support within the construction industry. Consequently, this papers tackles the problem of automating the extraction of implicit knowledge about significant legal factors upon which verdicts of Differing Site Condition (DSC) litigations are based. To that end, the research methodology (1) utilized a set of 600 cases from the Federal Court of New York; (2) adopted 15 legal concepts that have been found to be statistically significant for DSC litigations; (3) implemented 4 weighing mechanism for data representation, namely Term Frequency, Logarithmic Term Frequency, Augmented Term Frequency, and Term Frequency Inverse Document Frequency; and (4) employed Machine Learning (ML) classifiers, namely Naïve Bayes, Decision Tree, and PART for the development of 12 prediction models. Among the finding of this study (1) ML classifiers present a suitable solution for the analyzed task; and (2) Naïve Bayes classifiers achieved the highest prediction accuracy of 88%. [ABSTRACT FROM AUTHOR]

Transportation infrastructure is a critical component to a nation’s economy, security, and wellbeing. In order to keep up with the rising population, there is a great need for more efficient and cost-effective technologies and techniques to not only repair the infrastructure, but also to advance and expand the transportation infrastructure to sustain the growing population. Building Information Modeling (BIM) has been widely adopted in the building industry, and its established methods and technologies show enormous potential in benefiting the transportation industry. The purpose of this paper is to present a literature review and critical analysis of BIM for transportation infrastructure. A total of 189 publications in the area of BIM for transportation infrastructure were reviewed, including journal articles, conference proceedings, and published reports. Additionally, schemas and file formats from 9 main categories and 34 areas related to transportation infrastructure were reviewed. An application was developed to collect, store, and analyze the publications. Various algorithms were developed and implemented to help in the automation and analysis of the review. The goal of this paper is to provide a comprehensive, up-to-date literature review and critical analysis of research areas regarding BIM for transportation infrastructure to further facilitate research and applications in this domain. Based on the results of the analysis, current topics and trends, applications and uses, emerging technologies, benefits, challenges and limitations, research gaps, and future needs are discussed. Significantly, the contribution of this paper is providing the foundation of current research, gaps, and emerging technologies needed to facilitate further research and applications for both academia and industry stakeholders to develop more efficient and cost-effective techniques necessary to repair, advance, and expand the transportation infrastructure. Furthermore, the results show that the use of BIM for transportation infrastructure has been increasing, although the research has mainly been focusing on roads, highways, and bridges. The results also reveal a major need for a standard neutral exchange format and schema to promote interoperability. Most importantly, the continuing collaboration between academia and industry is required to mitigate most challenges and to realize the full potential of BIM for transportation infrastructure. [ABSTRACT FROM AUTHOR]

Robotic construction through concrete 3D printing is an in-progress revolution in construction industry. While significant progress is made on hardware related challenges, software and information related issues of such innovative system are less discussed. In this paper, a software platform is proposed for data retrieval and analysis from BIM models and utilizing it efficiently during various stages of the process. While the general idea of using BIM for automated construction has been mentioned before, the implementation details (the focus of this paper) were not previously discussed. To this aim, a framework is proposed to integrate BIM into an automated construction system. A Planning and Operations Control Software for Automated Construction (POCSAC) is developed as a major enabler for a seamless integration of BIM and Contour Crafting. The interoperation between different components of the construction system and BIM platform are designed to maximize the realized benefits through synergy of the two technologies. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) techniques have enabled the construction industry to realize various benefits. However, most projects still rely on 2D drawings to communicate the 3D BIM content to construction personnel. While Mixed Reality (MR) could theoretically be the primary means of communicating BIM content to onsite personnel in 3D, there is not currently a thorough understanding of how this might impact the construction performance of industry practitioners. This paper explores this topic by examining the field of electrical construction. It addresses research questions related to: MR's influence on the productivity and quality of electrical conduit construction; and the effects of an industry practitioner's background on his or her performance using MR. To address these topics, a quasi-experiment was conducted that compares the performance of eighteen electrical construction personnel who were tasked with building similar conduit assemblies using traditional paper and MR. Participants completed pre- and post-activity questionnaires to provide their perceptions of the experience. The results suggest that MR enabled: a significantly higher productivity rate; reduced the time required to understand the design; led to fewer errors during the assembly process; and increased the number of accurately constructed conduits as compared to the conduits constructed using traditional paper. Additionally, nearly all participants agreed that MR is easy to use, but most still felt that they would prefer to use paper plans for design communication. The findings of this work were noteworthy because many of the participants had substantial prior experience constructing conduit using paper plans, yet they still performed the task better and faster using MR. While the small sample size limits the extent to which these findings can be generalized, the contribution of this work is in demonstrating, as a proof-of-concept, that MR can be a viable option for communicating existing BIM content to current industry practitioners and that it can offer advantages that are not currently observed through the use of a paper-based communication methods. [ABSTRACT FROM AUTHOR]

This paper addresses the limited research on the metaverse's application in the construction industry. It aims to investigate how the metaverse can empower construction, identify adoption barriers, and determine the most significant barriers. We propose a novel application framework of construction metaverse based on cyber-physical-social systems, identify 17 barriers using the political-economic-social-technological framework, and employ an expert survey and bi-objective optimization to rank the barriers. Results indicate that scalability, lack of policy incentives, and immature business models are the most critical barriers. The findings provide valuable insights for researchers, practitioners, and policymakers in the construction industry, helping to allocate resources effectively and drive metaverse development. The study's importance lies in its potential to guide successful metaverse integration in construction, leading to improved efficiency and innovation. This research inspires future work on specific metaverse applications in construction and interdisciplinary research to understand and overcome the identified barriers. • We propose a CPSS-based framework for construction metaverse. • We identify the barriers that hinder the construction metaverse application. • We evaluate critical levels of identified barriers. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) has been recognized as an emerging technological innovation which can help transform the construction industry and it has been adopted broadly in the field of built environment. Due to the rapid development of BIM research, various stakeholders require a state-of-the-art review of the BIM research and implementation. The purpose of this paper is to provide an objective and accurate summary of BIM knowledge using 1874 published BIM-related papers. The results show that 60 key research areas, such as information systems, 3D modeling, design and sustainability and 10 key research clusters, such as architecture design studio, building information and lean construction, are extremely important for the development of BIM knowledge. The results are useful for the identification of research clusters and topics in the BIM community. More importantly, these results can help highlight how BIM-related research evolves over time, thus greatly contributing to understanding the underlying structure of BIM. This study offers useful and new insights to summarize the status quo of BIM knowledge and can be used as a dynamic platform to integrate future BIM developments. [ABSTRACT FROM AUTHOR]

Development of automated building code compliance checking systems requires appropriate representations for building codes. Building codes are complex documents written in natural languages, and the development of computable representations is challenging. This paper presents a new model and an accompanying modeling methodology for the representation of building codes that may be utilized in the development of future automated compliance checking systems. The new model combines the semantic modeling approach of the SMARTcodes project with the theoretical foundations established by Nyman and Fenves, namely the four level representation. This hybrid model organizes the representation in four levels and allows for separate modeling of domain concepts, individual rule statements, relationships between rules, and the overall organization of the building code. The model is evaluated with a case study. The İzmir Municipality Housing and Zoning Code is chosen as it is representative of complex building codes that are in effect throughout Turkey. The formalizable rules in the section of Izmir code that apply to all types of buildings, are represented in computer implementable format based on the new model. The research presented in this paper shows that decomposing a building code into four levels and modeling rules based on the semantic-oriented paradigm is an effective modeling strategy for representing building codes in a computable form. [ABSTRACT FROM AUTHOR]

Processing of raw point cloud data obtained as a result of terrestrial laser scanning (TLS) sometimes involves georeferencing, i.e. transformation of point cloud data to an external coordinate system. This paper focuses on defining the error model of point positions obtained through a “station-orientation” procedure of direct georeferencing. The original error model presented by the authors relevant in this field is partly altered. All modifications are explained in detail within the paper and the reported model is statistically verified based on the carefully conducted experiment using Leica ScanStation P20 scanner. The obtained values of the uncertainty measures of direct georeferencing which are of a few millimetre magnitude prove that this procedure can be efficiently used for planning and carrying out even more demanding surveying tasks, including those during monitoring and maintenance of constructed facilities. Additionally, traversing capabilities of terrestrial laser scanners tightly connected with direct georeferencing should contribute to mass introduction of laser scanning into the construction industry thanks to its similarities to the highly automated procedures of polar surveying and traversing which are traditionally employed among surveyors. [ABSTRACT FROM AUTHOR]

To address the problems of budgetary inaccuracy, the lack of comprehensive or high-level management, and the existence of serious waste of auxiliary materials during the main construction phase of housing construction, a BIM-based method for calculating the auxiliary materials required for housing construction is proposed in this paper. The BIM model is firstly built according to structural construction drawings, the construction scheme and the construction specification and technology in the main structure construction stage; then, the usage of auxiliary materials is calculated, and the auxiliary material dosage report, construction drawings, and processing drawings are generated for purchasing, collectively processing auxiliary material and guiding construction at the same time. This paper improves upon the traditional auxiliary material management model and design via the implementation of a BIM application named zgBIMs according to the proposed method. The improved management model uses the generated auxiliary material dosage report, construction drawings, and processing drawings to centralize the processing of the required auxiliary materials, strengthen supervision in the process of material distribution and construction, and introduce a reward and punishment mechanism to control the attrition rate of auxiliary materials. In this paper, the successful implementation of the presented method and management model is demonstrated as part of a comprehensive and experimental building project. The experimental results show that the proposed method can be used for the accurate calculation of the amounts of auxiliary materials required to reduce the use and waste of auxiliary materials efficiently and thus save construction costs. [ABSTRACT FROM AUTHOR]

Construction supply chain management (CSCM) has gained rapid development in last decades. As a result, the conventional Internet fails to fulfill demands for real-time information sharing and communication derived from various participants of the construction supply chain (CSC).The emerging Mobile Internet (M-Internet) has provided potential for solving this issue. This paper presents a systematic review on M-Internet based CSCM via descriptive and thematic analyses of publications retrieved from four major databases. The theoretical contribution of this paper is the development of an integrated framework in this research domain. This includes five aspects of CSCM, i.e. material flow and supply management, real-time information sharing and communication, coordination and integration in CSC, technology support for M-Internet, and associated safety issues. Finally, gaps in the existing body of knowledge are identified and future research agenda is proposed. [ABSTRACT FROM AUTHOR]

Recent advancements in robotics and human–machine interfaces enable new collaborative procedures that combine the strengths of machines and humans. Compared to existing automation technologies in the timber prefabrication industry, human–robot collaboration (HRC) offers new possibilities for increased flexibility and productivity. This paper aims to map out the challenges and opportunities for HRC within the context of timber prefabrication by constructing a conceptual framework. The framework is based on three pillars: (1) existing HRC theories and frameworks, (2) a literature review of HRC research in robotic timber fabrication, and (3) perspectives of human labour in the timber construction industry. The relevant topics among these three areas are triangulated to construct a conceptual framework that bridges the system-, design-, and human-centred considerations. The framework serves as an organising device to support future explorations and research on human–robot collaboration in robotic timber construction. • An integrative approach embeds HRC design in the context of timber prefabrication. • Data is triangulated from system, design, and human perspectives. • Study reveals gaps in existing work and promising directions for future research. • The conceptual framework serves descriptive, evaluative, and generative use for HRC. [ABSTRACT FROM AUTHOR]

The curtain wall construction industry is one of the most popular industries with excellent development prospects. On the other hand, curtain wall installation is mainly performed manually, which has the disadvantages of great danger and low efficiency. Therefore, this study designed a method for curtain wall frame detection based on computer vision to assist curtain wall installation in completing positioning and installation tasks. This paper presents a deep learning method with two input streams and cross-modal feature fusion based on the encoder-decoder structure (CWFD-net) to detect curtain wall frames accurately. In particular, the high-level semantic features of the RGB and Depth streams in the encoder stage are fused to generate RGB-D features to achieve preliminary cross-modal feature fusion, which makes input information include more curtain wall frame features. The coordinate attention mechanism enables the network to focus more on the position information of the curtain wall frame. A cross-stage feature fusion strategy was adopted in the decoder stage to enhance the features further and suppress interference factors. A dataset containing curtain wall frame images of different styles in various curtain wall construction scenarios was established to verify the effectiveness of this method, which is trained, validated, and tested with this dataset. The experimental results show that the detection performance of the proposed method is superior to the commonly used segmentation or detection methods, which achieves the highest mIoU 87.33%, Accuracy 96.98%, Recall 92.28%, F1-Score 87.66%, and the lowest 95-HD 6.13. This model is expected to be deployed and applied to curtain wall installation robots. • Present a two inputs encoder-decoder structure network for curtain wall frame detection under several construction sites. • Propose feature fusion strategy in encoder, intermediate, and decoder stage for feature representation ability. • Create a dataset containing 1547 RGB and Depth images of curtain wall frames in 5 construction sites of various scenarios. • CWFD-net outperforms other relative segmentation and salient object detection networks in self-built dataset in accuracy. [ABSTRACT FROM AUTHOR]

In the past two decades, robotics in construction (RiC) has become an interdisciplinary research field that integrates a large number of urgent technologies (e.g., additive manufacturing, deep learning, building information modelling (BIM)), resulting in the related literature being both fragmented and vast. This paper has explored the advances in RiC in the past two decades using a mixed quantitative-qualitative review method. Initially, 940 related articles (170 journal articles and 770 conference papers) were identified by keyword-searching in Scopus and then fed into a bibliometric analysis to build science maps. Following this, a qualitative discussion highlights recent achievements in RiC across three dimensions: tasks, algorithms, and collaborations. Moreover, four future research directions are proposed: 1) in-depth integration of BIM and robotics; 2) near-site robotic fabrication; 3) deep reinforcement learning for flexible environment adaption; and 4) high-level robot-to-robot collaboration. The contributions of this research are twofold: 1) identifying the latest research topics and trends concerning robotic technologies in construction; and 2) providing in-depth insights into the future direction of RiC. The findings from this research can serve both academia and industry in terms of promoting robotic algorithms, hardware, and applications in construction industry. [Display omitted] • A mixed-method review of literature of robotics in construction since 21 century. • A bibliometric analysis was used to conduct publication cluster and research cluster analysis. • A qualitative analysis was performed to present the hot topics in the research areas. • Four potential research directions are proposed for robotics in construction. [ABSTRACT FROM AUTHOR]

Inefficient and ineffective Construction Contract Administration (CCA) is at the root of many of the sector challenges. Emerging digital technologies such as blockchain are revealing some capabilities with the potential for improving CCA. This paper addresses the research question of whether and how can blockchain contribute to improving CCA and what are the specific challenges to its adoption in CCA. The study adopts a systematic review of studies in this domain and their subsequent analysis against a CCA framework. Most applications were found to be centered on two CCA functions; the financial management , and the document and record management. CCA functions that embed complex contractual logics such as claims and disputes resolution management have received scant attention. To advance blockchain application in CCA, a structured roadmap of its key challenges relating to technology, process, policy and society is proposed for future research. The outcome of this paper provides scholars, practitioners and policymakers, interested in construction contracts, with the evidence about the current level of blockchain contribution to CCA and a structured set of recommendations for future research. [Display omitted] • The blockchain's role in improving construction contract administration is examined. • A functional framework of contract administration is used to evaluate studies. • Evidence of blockchain role in reducing causes of poor contract administration is identified. • Existing coverage, gaps, and future directions in this domain are identified and discussed. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) has emerged as one of the key streams in construction and civil engineering research within the last decade. Given this interest in BIM and the rapidly increasing volume of BIM literature, it is important to understand and discern the core themes and trends emerging in BIM research, and its implications for broader research. The previously reported studies to identify the core of BIM research are typically subjective and qualitative, and hence, prone to bias and interpretation of a limited number of reviewed papers. There is a lack of comprehensive, quantified and systematic classification of the BIM literature. This research brings some clarity by synthesizing and labeling a large corpus of BIM research studies published from 2004 through 2014. Latent Semantic Analysis (LSA), a natural language processing technique was applied to the abstracts of 975 academic papers. This objective analysis reveals twelve principal research areas. Various specific research themes associated with each principal area have been identified. These principal research areas and research themes indicate the patterns and trends in BIM research. [ABSTRACT FROM AUTHOR]

This paper investigates the application of competitive intelligence (CI) techniques for construction contractor selection process, as part of the overall construction contract management. While comprehensive and ongoing CI applications are employed in a variety of industries to provide valuable input for broad strategic decisions, the construction industry lags behind in adopting this methodology. The use of CI for contract management is an important development in light of the realization on the part of major construction contractors that the diffuse nature of the information and lack of robust analysis create numerous uncertainties during the decision-making processes. The findings of this paper show that CI has the potential to improve the process for assessing and selecting contractors, through supporting an unbiased and auditable decision making process. A case-study on using CI for contractor selection on a megaproject in the industrial sector is presented along with the guidelines for the use and implementation of CI in the construction industry as a whole. [ABSTRACT FROM AUTHOR]

Despite the advances of modular construction, the comprehensive understanding of its technical aspects in buildings is still limited, especially during the implementation process. This paper reviews the technical aspects of planning and coordination of modular construction in the building industry. The unclear onsite and practical knowledge need to be clarified for the implementation process. It then leads to the questions on the status of research development and gaps of the technical aspects. One hundred and thirty papers were filtered and analyzed through a systematic review. Four technical aspects of modular construction were found, namely (a) feasibility aspects of modular construction, (b) types of construction or materials, (c) design and structural analyses, and (d) construction planning. The findings render insightful references for the successful delivery of modular construction including its lifecycle analysis and sustainability needs. A research framework is also developed to highlight the gaps and measures for future practice. • Technical developments of modular construction are reviewed. • Four technical aspects of its overall planning and coordination are found. • The gaps and their proposed measures are articulated in a research framework. [ABSTRACT FROM AUTHOR]

Building Information Modelling (BIM) concepts and workflows continue to proliferate within organisations, through project teams, and across the whole construction industry. However, both BIM implementation and BIM diffusion are yet to be reliably assessed at market scale. Insufficient research has been conducted to date towards identifying the conceptual structures that would explain and encourage large-scale BIM adoption. This paper introduces a number of macro-adoption models, matrices and charts ( Fig. 1 ). These models can be used to systematically assess BIM adoption across markets, and inform the structured development of country-specific BIM adoption policies. This research is published in two complementary papers combining conceptual structures with data collected from experts across a number of countries. The first paper “Macro-BIM adoption: conceptual structures” delimits the terms used, reviews applicable diffusion models, and clarifies the research methodology. It then introduces five new conceptual constructs for assessing macro-BIM adoption and informing the development of market-scale BIM diffusion policies. The second paper “Macro-BIM adoption: comparative market analysis” employs these concepts and tools to evaluate BIM adoption and analyse BIM diffusion policies across a number of countries. Using online questionnaires and structured interviews, it applies the models, refines the conceptual tools and develops additional assessment metrics. The two papers are complementary and primarily intended to assist policy makers and domain researchers to analyse, develop and improve BIM diffusion policies. [ABSTRACT FROM AUTHOR]

The residential construction industry relies mainly on elementary two-dimensional (2D) design and shop drawings. Building Information Modeling (BIM) and parametric design have proven to be an effective technology for integrating design and construction while maintaining low cost and producing more benefits to owners, designers, and builders. However, architects, engineers, and designers may lack the time and resources needed to generate accurate BIM models or to be able to use the model information to benefit the construction process. In this paper, we propose a methodology for the automation of shop drawings for the wood-framing design of residential facilities based on a parametric model that is incorporated into a 3D-CAD model. The proposed methodology is tested in a number of virtual scenarios within the CAD environment, and is implemented as a computer program referred to in this paper as FRAMEX, a tool developed using Visual Basic for Applications (VBA) as an add-on to AutoCAD. FRAMEX adopts the guidelines at the foundation of BIM technology to generate shop drawings in which the information is consistent at every level of detail, from the studs to the panels to the home where all the panels are joined to form a single entity. It also reduces the time required for drafting design by automating the process based on 3D-CAD and parametric modeling. [ABSTRACT FROM AUTHOR]

Designing with building performance simulation feedback in the early design stage has existed since the early days of computational modeling. However, as a consequence of a fragmented building industry building performance simulations (BPSs) in the early design stage are closely related to who is creating and operating the BPS models. This paper critically reviews the different ways designers and analysts use BPS in the early design stage. One of the key findings is that most tools and methods used in the early design stages are insufficient to provide valid feedback while in the same time being flexible enough to accommodate a rapid changing design process. The main concern points to the way geometrical models and analytical models are combined and how this affects the way the buildings are designed and perform. This paper concludes that integrated dynamic models may combine a design tool, a visual programming language and a BPS to provide better support for the designer during the early stages of design as opposed to alternatives such as the current implementation of IFC or gbXML or the unaccompanied use of simulation packages. [ABSTRACT FROM AUTHOR]

In order to monitor the operating conditions of the construction industry, this paper incorporates the principal component analysis (PCA) and support vector machine (SVM) to predict the profitability of the construction companies listed on A-share market in China. With annual financial data in 2001–2012, this paper selected six indicators from different profitable perspectives to build a composite profitability index based on the PCA technique, and then established a SVM model to make the corporate profitability prediction of the construction companies in China. The results indicate that, the technical combination of the PCA and SVM can improve the profitability prediction significantly. In 2003–2012, the accuracy of predicting the profitability of the Chinese construction companies exceeded 80% on average. Compared with the artificial neural network (ANN), the SVM model has the superiority in the accuracy prediction of the Chinese construction companies. [ABSTRACT FROM AUTHOR]

Problems in existing methods of production tracking in off-site construction result in schedule delays and increased costs. To eliminate these deficiencies, an autonomous production tracking that analyzes real-time production data is proposed. A specific implementation of the proposed production tracking mechanisms has been developed for a large off-site construction plant in Australia, and is in the process of installation. The paper shows that: (i) The production model in off-site construction is always nonlinear in the outcome due to the presence of variability (ii) in systems with a periodic production target, deviation from the schedule converges to zero at the end of production period and the same downward trend should be followed in designing plan buffers and (iii) long-term production performance in off-site construction can autonomously be monitored and controlled by observing critical variables of production. The paper provides those who manage off-site construction with recommendations on effective production tracking and management. The models and propositions in this research are of practical value and can be used to detect impending production shortfalls against periodic targets in the short-term, and adjust capacity parameters and production targets in long-term planning. [ABSTRACT FROM AUTHOR]

There is a growing need for tools automating the processing of as-built 3D laser scanned data, and more particularly the comparison of this as-built data with planned works. This paper particularly considers the case of tracking MEP components with circular cross-sections, which essentially include pipes, and some conduits and ducts. Discrepancies between the as-built and as-planned status of pipes, conduit and ductwork result from changes that occur in the field and that are either unnoticed (human error) or not reflected in the 3D model. Previous research has shown that the Hough transform, with judiciously applied domain constraints, is a practical and cost-effective approach to find, recognize and reconstruct cylindrical MEP works within point clouds automatically. Previous research has also shown that “Scan-vs-BIM” systems that are based on the geometric alignment and comparison of as-built laser scans with as-designed BIM models can effectively recognize and identify MEP components as long as they are constructed near their as-planned locations. The research presented in this paper combines the two techniques in a unified approach for more robust automated comparison of as-built and as-planned cylindrical MEP works, thereby providing the basis for automated earned value tracking, automated percent-built-as-planned measures, and assistance for the delivery of as-built BIM models from as-designed ones. The proposed approach and its improved performance are validated using data acquired from an actual construction site. The results are very encouraging and demonstrate the added value of the proposed integrated approach over the rather simpler Scan-vs-BIM system. The two main areas of improved performance are: (1) the enabled recognition and identification of objects that are not built at their as-planned locations; and (2) the consideration for pipe completeness in the pipe recognition and identification metric. [ABSTRACT FROM AUTHOR]

For decades, the construction industry has experienced poor productivity due to challenges such as increasing project complexity and a fragmented project environment. Even though some technological innovations around Building Information Modeling (BIM) might have the potential to overcome these challenges, data integration across disciplines, companies and software solutions is yet to be solved entirely. Trending advancements try to enrich existing BIM data using Linked Data technologies to semantically describe the building information and facilitate data integration. By that, project data from different data sources is made available in an accessible format, so project participants can use it for their planning efforts. In this paper we explore the use of Linked Building Data (LBD) on a specific use case to answer the question of how the planning of Temporary Construction Items (TCIs) can be improved by integrating data and automating the demand calculation. A literature review concludes that TCIs only experience little attention in the current planning of construction projects but have a critical impact on the outcome of a project. Thus, the objective of this paper is to develop standard ontologies to provide a semantically rich terminology of the data and to propose a framework for TCI consideration within a BIM based project delivery system. A prototype solution is developed, taking formwork as a TCI representative. The result is a process for automatically creating a TCI utilization plan that quantifies the precise time- and location-based on-site TCI demand by integrating data from BIM, Location-Based Scheduling (LBS) and TCI information. Based on the results of prototyping and findings from expert interviews, this research integrates the solution into the process of construction and finally proposes two implementation scenarios for the solution – one being based on the current industry situation and one exploring the future vision of a more integrated and decentralized project delivery in the construction industry. • Data integration is cruceial for improving construction productivity. • Temporary Construction Items (TCIs) are lacking attention in construction planning. • Integrating BIM and scheduling data enables to automate TCI planning. • A rule-based algorithm can calculate the precise TCI demand with a time- and location-based TCI utilization plan, based on this data. • A prototype solution is tested with a case project, upon which [ABSTRACT FROM AUTHOR]

The utilization of Building Information Modeling (BIM) has been growing significantly and translating into the support of various tasks within the construction industry. In relation to such a growth, many approaches that leverage dimensions of information stored in BIM model are being developed. Through this, it is possible to allow all stakeholders to retrieve and generate information from the same model, enabling them to work cohesively. To identify gaps of existing work and evaluate new studies in this area, a BIM application framework is developed and discussed in this paper. Such a framework gives an overview of BIM applications in the construction industry. A literature review, within this framework, has been conducted and the result reveals a research gap for BIM applications in the project domains of quality, safety and environmental management. A computable multi-dimensional (nD) model is difficult to establish in these areas because with continuously changing conditions, the decision making rules for evaluating whether an individual component is considered good quality, or whether a construction site is safe, also vary as the construction progresses. A process of expanding from 3D to computable nD models, specifically, a possible way to integrate safety, quality and carbon emission variables into BIM during the construction phase of a project is explained in this paper. As examples, the processes of utilizing nD models on real construction sites are described. It is believed to benefit the industry by providing a computable BIM and enabling all project participants to extract any information required for decision making. Finally, the framework is used to identify areas to extend BIM research. [ABSTRACT FROM AUTHOR]

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinder their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered whilst performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination. [ABSTRACT FROM AUTHOR]

One of the long-lasting challenges of the Architecture, Engineering and Construction (AEC) industry has been addressing personalised solutions as nearly affordable as possible to what could be offered by mass production in the post industrialisation era. Ever since its gestation, BIM has promised endless prospects for people, organisations, products and processes in the AEC industry. This paper sets out to investigate the benefits of BIM as a general configurator to facilitate customisation: offering personalised solutions at a price comparable to mass produced products and services. Providing a quick review of literature, the paper sets the scene for investigating how the generic capabilities of BIM applications can be utilised to offer customisable façade systems. Using a systemic approach, this is then used to elucidate future developments of the current project into next stages where other elements and parameters can be implanted into the basic family to broaden the choice and to reinforce this customisable façade solution. [ABSTRACT FROM AUTHOR]

Abstract: Prefabrication has been increasingly used in buildings. It is recognised as a solution to reduce waste arising during design and construction phases. However, there is little emphasis on life cycle design issues for prefabricated buildings located in dense high-rise building environments. The purpose of this paper is to review the application and identify benefits and impediments of design for deconstruction and Industrialised, Flexible and Demountable building systems when applied to precast concrete construction. The paper presents the results of a comprehensive literature review, and two case studies of recently completed institutional buildings using prefabrication. The literature review shows that, so far, design for deconstruction is not a common practice in the building industry. The case studies showed some limitations such as the dense urban environment conditions and limited site area. The promotion of a closed-loop material cycle is critical to contribute to sustainability thus minimising CO2 emissions, natural resources consumption. [Copyright &y& Elsevier]

Abstract: Currently there is no approach which would help to comprehensively ensure occupational safety. Many scientists perform researches and calculations, create new methods related to safety and health, but most of them analyze separate aspects of safety in the field of construction. The authors of this paper present a new complex view on ensuring occupational safety and health during construction. The selection of safety solutions is performed based on complex evaluation of structure, technology and safety. In their previous works, the authors offered a new method for multiple attribute decision synthesis, SyMAD-3, which helps to choose an effective construction project alternative from multiple alternatives by assessing various construction, technological and occupational safety solutions, based on a set of quantitative attributes. However, the integration of these solutions may cause doubts, since decision making in construction is always associated with uncertainty. The investment projects in construction are characterized by the large accuracy variation (from 15 to 50%) of some attribute values. Although the SyMAD-3 method is mathematically grounded, it does not answer the question if the error of attribute values impacts the final decision and if this decision can be reliably assessed. In the present paper, the authors supplement the SyMAD-3 method with decision sensitivity analysis (SyMAD-3 with SA) to improve the reliability of the SyMAD-3 method and assess the reliability of the obtained decision. The SyMAD-3 with SA method allows us to choose an effective alternative of a construction project by assessing three stages of construction, based on a set of attributes given the error of their values, and determine the reliability of the final decision. The proposed method is implemented in a software package created by the authors with the aim of analyzing decisions and performing experimental calculations in the field of construction. [Copyright &y& Elsevier]

Long Range (LoRa) technology is inevitable in the Internet of Things applications for the construction industry due to the large transmission range. Accordingly, this emerging technology is being used in many civil engineering applications such as water quality control, equipment tracking, etc., and the use of this technology is likely to multiply in the coming years. Therefore, the energy efficiency of this system should be investigated to reduce its environmental impact, which is lacking in previous investigations. This paper explores the effect of transmission parameters on power consumption and proposes a scheme for controlling transmission parameters to improve the energy efficiency of LoRa end nodes. The effectiveness of the proposed scheme is demonstrated through a case study on a real-time monitoring system based on LoRa for the compressive strength of concrete at early ages which is crucial for quality control and construction management. • The paper proposes a transmission parameter selection scheme to improve the energy efficiency of LoRaWAN end nodes. • The efficiency of proposed selection scheme is verified in construction asset tracking and real-time monitoring of early age concrete compressive strength • The paper explored the possibility of employing renewable energy sources in the LoRa end node to reduce its environmental impact. [ABSTRACT FROM AUTHOR]

Abstract: Safety accidents occur frequently in underground metro construction due to its complexity. These accidents cause huge losses because most metro construction is located in the center of very congested cities. Therefore, safety management is a priority in the metro construction industry. This paper proposes an approach for safety management using visualization technology. Safety is integrated with the construction management process throughout the project life cycle. Information from the design phase about construction components and scheduling has been gathered to formulate a 4 dimensional (4D) model. Before construction begins, a rule-based tool analyzes this combined information, automatically detects potentially unsafe activities and conditions and provides instructions for correction. More importantly, actual site monitoring data are continuously compared to the 4D model during the construction process. Therefore, the safety status of related components can be continuously visualized in the system as conditions change and potential safety risks evolve. This paper presents a prototype which was developed and verified with a case study of a real project. The results show that the proposed approach can be a tool of collaboration, virtual analysis and prediction for designers, site project managers, safety engineers and other participants. With real-time safety status visualized, it can detect safety risks before and during the construction process and then provide preventive measures. Thus, timely decisions can be made to avoid accidents. This contributes to the success of safety management in the metro construction industry. [Copyright &y& Elsevier]

Abstract: Augmented reality (AR), a state-of-the-art technology for superimposing information onto the real world, has recently started to affect our daily lives. AR applications are becoming mature and versatile. This paper discusses trends in AR applications for architecture, engineering, construction, and facility management (AEC/FM). This paper specifically focuses on four technologies—localization, natural user interface (NUI), cloud computing, and mobile devices—which have the potential to influence the development of AR applications. Advances in localization technology will enable the deployment of AR in a complex environment. An NUI provides more convenient and intuitive user experiences, which can increase the usability of AR. Cloud computing environments allow users with internet access to ubiquitously retrieve information from almost anywhere. Hence, cloud computing increases the freedom of using AR in AEC/FM applications. Another factor that will lead to the wider usage of AR is that mobile devices are becoming smaller, more powerful, and less expensive. This paper summarizes the results of 101 research efforts, and outlines the research trends and opportunities for applying AR in the fields of AEC/FM. [Copyright &y& Elsevier]

Abstract: The construction industry involves many dangerous and messy environmental factors which cause poor working conditions for construction laborers. Replacing human laborers with robotic systems has many advantages such as increased quality, productivity and safety. The current trends in construction with high-rise buildings have accelerated attempts to employ robotic technologies in the construction industry. Recently in South Korea, a robot-based construction automation system for high-rise buildings was finished with successful field application results. This project is composed of a few subprojects involving construction and robot technologies. Among several parts of the project, this paper deals with the development of a robotic transport mechanism administrated by the robot research group of the project. This system consists of a cross-wired lift and a rail sliding mechanism. Each system performs a vertical and horizontal transfer of a robotic beam assembly (RBA) system which is discussed in a companion paper, ‘Robot-Based Construction Automation: An Application to Steel Beam Assembly (Part I).’ This paper accounts for the designs, functions, specifications and structural analyses of each system and presents an RBA control system, including a human–machine interface to operate the integrated system. The real prototype of the proposed system was manufactured and intensive tests were conducted in a test bed. In addition, a field application test was added for evaluating the feasibility in real construction sites. We showed the possibility of replacing human laborers with the robotic system in high-rise building construction. [Copyright &y& Elsevier]

Abstract: Organizational and people centered issues pose the greatest challenge for Building Information Modeling (BIM) implementation. Studies showed that BIM implementation is still a challenge for the North American construction industry. The Canadian construction industry, in contrast, is well behind that of the U.S. in its BIM adoption rate. Maturity and adoption of BIM depends mainly on the client or the owner in construction projects. Public sector clients often think that the market is not ready for BIM and are afraid to increase project costs by limiting competition. Moreover, if the contractor is not integrated in the project in the design phase, BIM has limited power. This paper proposes a ‘BIM partnering’ based public procurement framework to ensure ‘best value’ in construction projects. The case study presented in the paper proved the feasibility of proposed BIM based procurement in publicly-funded construction projects. The suggested contractual arrangement for the project resulted in improved productivity, better coordination, and reduced error, and rework. [Copyright &y& Elsevier]

Abstract: In recent years, with the increasing level of competition in the global construction market, several research efforts have focused on the application of information technology (IT) as a way to improve the integration process of construction supply chain management (CSCM). Visual representation of the process can provide an effective tool for monitoring resources in the CSCM. In order to support this objective, this paper integrates building information modeling (BIM) and geographic information systems (GIS) into a unique system, which enables keeping track of the supply chain status and provides warning signals to ensure the delivery of materials. First, the proposed methodology is implemented by using BIM due to its capability to accurately provide a detailed takeoff in an early phase of the procurement process. Furthermore, in order to support the wide range of spatial analysis used in the logistics perspective (warehousing and transportation) of the CSCM, GIS is used in the present model. Thus, this paper represents the integrated GIS-BIM model manifesting the flow of materials, availability of resources, and “map” of the respective supply chains visually. A case example is presented to demonstrate the applicability of the developed system. [Copyright &y& Elsevier]

Abstract: Minimizing both project time and cost is an important matter in today''s competitive environment. Therefore trade-off between project time and cost is necessary. In projects, each activity can be started at different time points, depending on its precedence relationship and resource availability. Also cost and duration of the activities could be changed depending on the allocated resources. In addition, another strategy that affects the project total time and cost is resource leveling, which is applied to reduce excessive fluctuations in the resource usage. In this paper multi-mode resource-constrained project scheduling problem (MRCPSP), discrete time–cost trade-off problem (DTCTP) and also resource allocation and resource leveling problem (RLP) are considered simultaneously. This paper presents the multi-mode resource-constrained discrete time–cost-resource optimization (MRC-DTCRO) model in order to select starting the time and the execution mode of each activity satisfying all the project constraints. To solve these problems, non-domination based genetic algorithm (NSGA-II) is employed to search for the non-dominated solutions considering total project time, cost, and resources moment deviation as three objectives. The results of MRC-DTCRO model presented in this paper show that adding the resource leveling capability to the previously developed multi-mode resource-constrained discrete time–cost trade-off problem (MRC-DTCTP) models provides more practical solutions in terms of resource allocation and leveling, which makes this research applicable to both construction industry and researchers. [Copyright &y& Elsevier]

Abstract: Location aware computing in construction is an emerging area where the location of materials, workforce, and equipment can be used to derive knowledge about the state of the project. This paper aims to provide a low-cost location sensing solution for indoor construction and underground facilities, where satellite navigation systems cannot be used. In this solution a set of low-cost passive Radio Frequency Identification (RFID) tags is deployed using a predefined topology to provide a good spatial coverage of the project-active area. The locations are estimated and represented by zones and coordinates. The zone detection approach uses K-Nearest Neighbor classification method to assign a zone to the target. The coordinates of the target''s location are also acquired by weighted average method using the Received Signal Strength Indicator (RSSI) as weight. The approach has been experimented on a construction project in Montreal as well as in a controlled lab environment. The experimental results show an average of 0.17 as error rate for detecting the target''s zone and an average of 1.3m accuracy in detecting the coordinates. The promising results presented in this paper demonstrate the potential for a high-accuracy and low-lost location estimation method for indoor construction job sites. [Copyright &y& Elsevier]

Abstract: This paper empirically investigates a sample of capital facility projects in the construction industry. The purpose of this paper is three-fold. The first objective of this study was to validate a model for assessing the relationships among IT application, KM practice adoption, and project success (project performance and project benefits). The second objective was to evaluate the mediating role of KM practice adoption in the relationship between IT application and project performance. The third objective was to investigate whether the effect of knowledge management on project success may be moderated by project type. The structural equation modeling (SEM) approach was used to validate the research model. These analyses suggest that levels of IT application are positively associated with projects'' levels of knowledge management. Additionally, project outcomes can be achieved with higher levels of knowledge management. The findings also indicate that KM practice adoption fully mediate the effects of IT application on project performance in terms of schedule and cost success as well as quality and safety performance. The results also show that team relationship and team size have a moderating effect on the relationship between knowledge management and project success. [Copyright &y& Elsevier]