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Strategies for implementing big data concept in the construction industry of the Dominican Republic
Full text linkThis is an accepted manuscript of an article published in the Proceedings of the 21st International Conference on Construction Applications of Virtual Reality, 8th-10th December 2021, Teeside University, Middlesborough.
The accepted version of the publication may differ from the final published version.The Big Data (BD) boom has increased exponentially in recent years, reaching even the most
traditional industries. In construction, this technology has come to be considered as the possible solution to the
challenges that the industry has been facing in recent years, with some authors even naming this technology as
the future of the construction industry. However, despite this reception, studies that explain in detail the factors
that favour the adoption of Big Data are scarce and non-existent in some cases. Understanding these influencing
factors is a key element in ensuring future technology adoption across the industry. Such is the case of the
strategies which make up an action plan for companies that seek to adopt Big Data in the future. Therefore, the
objective of this study is to identify the strategies that would allow the adoption of Big Data in the construction
industry of the Dominican Republic. To identify these strategies, qualitative research was carried out due to the
scarcity of sources that address the subject. In the data collection process, a total of 21 interviews were conducted
representing companies with undoubted presence in the construction market of the Dominican Republic. As a
result of the data analysis, four main strategies were identified which include the promotion of standardization
and popularization of the BD concept and its benefits, investment in training and development of staff skills,
support for the development of current technologies as well as the inclusion of technology in the education
curriculum of present and future professionals. These strategies identified in the study will help companies that
plan to implement Big Data in the future to carry out an action plan and identify the steps to follow to achieve a
successful adoption of the technology. Also, this study contributes to the body of knowledge of research
professionals who focus on the elements for Big Data adoption as well as possible future professionals in the area
Multi-level and Collaborative Planning and Control of Construction Sites Using BIM and Lean
No full textLa gestion efficace des projets de construction est essentielle en raison de leur complexité inhérente et des implications financières substantielles. À cet égard, la planification et le contrôle des projets jouent un rôle crucial dans la réussite de l'exécution des projets, nécessitant des décisions basées sur les données et les connaissances pour naviguer dans ces complexités et garantir des résultats positifs. Malgré la présence de divers systèmes de planification et de contrôle, une planification et un contrôle inefficaces restent des causes majeures de faible productivité, de dépassements de budget et de retards dans les projets de construction. L'intégration des systèmes de planification et de contrôle existants peut remédier à ces problèmes en agrégant les avantages de chacun. Cependant, un écart significatif subsiste en raison de l'absence d'un cadre intégré et multi-niveaux combinant différentes méthodes de planification et métriques de contrôle à travers divers niveaux d'échéancier, tirant parti des forces de chacun pour offrir une solution plus efficace. De plus, il existe une insuffisance de systèmes basés sur les données et les connaissances qui répondent aux besoins spécifiques et aux applications des équipes de projet en matière de planification et de contrôle, proposant des solutions multi-niveaux optimisées. Cette étude vise à combler cette lacune en développant d'abord un cadre intégré et multi-niveaux pour la planification et le contrôle des projets. Ensuite, elle développe et met en œuvre un système d'aide à la décision (SAD) basé sur les données et les connaissances, qui exploite une base de connaissances construite à partir des expériences des experts. Ce système propose des solutions multi-niveaux et intégrées pour la planification et le contrôle des projets de construction, améliorant à la fois les cadres théoriques et les applications pratiques. Le SAD développé simplifie le processus de prise de décision en posant des questions simples et pertinentes adaptées aux besoins de l'équipe de projet, suggérant ainsi les approches les plus appropriées pour la planification et le contrôle des projets. Le cadre et le système d'aide à la décision développés ont été validés en les appliquant à une étude de cas de rénovation et en recevant des retours positifs de la part des experts. Enfin, une directive méthodologique détaillée a été élaborée pour faciliter la mise en œuvre du système de planification et de contrôle multi-niveaux recommandé par le SAD pour les projets de rénovation. Cette directive offre des instructions claires et étape par étape pour assurer une adoption simple et une intégration efficace dans les pratiques de gestion de projet. Cet outil polyvalent peut être appliqué à divers types de projets durant la phase de préconstruction, déterminant les stratégies de planification et de contrôle les plus efficaces en fonction des exigences fonctionnelles de l'équipe de projet.The effective management of construction projects is essential due to their inherent complexity and substantial financial implications. In this regard, the project planning and control domain plays a vital role in successful project execution, which requires data-driven and knowledge-based decisions to navigate these complexities and ensure successful project outcomes. Despite the presence of various planning and control systems, ineffective planning and control remain major causes of low productivity, budget overruns, and delays in construction projects. Integrating existing planning and control systems can address these issues by aggregating the advantages of each. However, a significant gap exists due to the lack of a multi-level and integrated framework that combines different planning methods and control metrics across various schedule levels, leveraging the strengths of each to offer a more effective solution. Furthermore, there is a deficiency in data-driven and knowledge-based systems that address the specific needs and applications of project teams regarding a planning and control system, proposing optimized multi-level solutions. This study aims to bridge this gap by first developing a multi-level and integrated framework for project planning and control. Subsequently, it develops and implements a data-driven and knowledge-based decision support system (DSS) that leverages a knowledge database built from experts' experiences. This system proposes multi-level and integrated solutions for the planning and control of construction projects, enhancing both theoretical frameworks and practical applications. The developed DSS simplifies the decision-making process by posing straightforward and relevant questions tailored to the project team's requirements, thereby suggesting the most suitable approaches for project planning and control. The developed framework and decision support system were validated by applying them to a renovation case study and receiving positive feedback from experts. Eventually, a detailed methodological guideline was crafted to facilitate the implementation of the DSS-recommended multi-level planning and control system for renovation projects. This guideline offers clear, step-by-step instructions to ensure straightforward adoption and effective integration into project management practices. This versatile tool can be applied across various project types during the preconstruction phase, determining the most effective planning and control strategies based on the functional requirements of the project team
Planification et contrôle multi-niveaux et collaboratifs des chantiers de construction à l’aide de la BIM et du Lean
No full textThe effective management of construction projects is essential due to their inherent complexity and substantial financial implications. In this regard, the project planning and control domain plays a vital role in successful project execution, which requires data-driven and knowledge-based decisions to navigate these complexities and ensure successful project outcomes. Despite the presence of various planning and control systems, ineffective planning and control remain major causes of low productivity, budget overruns, and delays in construction projects. Integrating existing planning and control systems can address these issues by aggregating the advantages of each. However, a significant gap exists due to the lack of a multi-level and integrated framework that combines different planning methods and control metrics across various schedule levels, leveraging the strengths of each to offer a more effective solution. Furthermore, there is a deficiency in data-driven and knowledge-based systems that address the specific needs and applications of project teams regarding a planning and control system, proposing optimized multi-level solutions. This study aims to bridge this gap by first developing a multi-level and integrated framework for project planning and control. Subsequently, it develops and implements a data-driven and knowledge-based decision support system (DSS) that leverages a knowledge database built from experts' experiences. This system proposes multi-level and integrated solutions for the planning and control of construction projects, enhancing both theoretical frameworks and practical applications. The developed DSS simplifies the decision-making process by posing straightforward and relevant questions tailored to the project team's requirements, thereby suggesting the most suitable approaches for project planning and control. The developed framework and decision support system were validated by applying them to a renovation case study and receiving positive feedback from experts. Eventually, a detailed methodological guideline was crafted to facilitate the implementation of the DSS-recommended multi-level planning and control system for renovation projects. This guideline offers clear, step-by-step instructions to ensure straightforward adoption and effective integration into project management practices. This versatile tool can be applied across various project types during the preconstruction phase, determining the most effective planning and control strategies based on the functional requirements of the project team.La gestion efficace des projets de construction est essentielle en raison de leur complexité inhérente et des implications financières substantielles. À cet égard, la planification et le contrôle des projets jouent un rôle crucial dans la réussite de l'exécution des projets, nécessitant des décisions basées sur les données et les connaissances pour naviguer dans ces complexités et garantir des résultats positifs. Malgré la présence de divers systèmes de planification et de contrôle, une planification et un contrôle inefficaces restent des causes majeures de faible productivité, de dépassements de budget et de retards dans les projets de construction. L'intégration des systèmes de planification et de contrôle existants peut remédier à ces problèmes en agrégant les avantages de chacun. Cependant, un écart significatif subsiste en raison de l'absence d'un cadre intégré et multi-niveaux combinant différentes méthodes de planification et métriques de contrôle à travers divers niveaux d'échéancier, tirant parti des forces de chacun pour offrir une solution plus efficace. De plus, il existe une insuffisance de systèmes basés sur les données et les connaissances qui répondent aux besoins spécifiques et aux applications des équipes de projet en matière de planification et de contrôle, proposant des solutions multi-niveaux optimisées. Cette étude vise à combler cette lacune en développant d'abord un cadre intégré et multi-niveaux pour la planification et le contrôle des projets. Ensuite, elle développe et met en œuvre un système d'aide à la décision (SAD) basé sur les données et les connaissances, qui exploite une base de connaissances construite à partir des expériences des experts. Ce système propose des solutions multi-niveaux et intégrées pour la planification et le contrôle des projets de construction, améliorant à la fois les cadres théoriques et les applications pratiques. Le SAD développé simplifie le processus de prise de décision en posant des questions simples et pertinentes adaptées aux besoins de l'équipe de projet, suggérant ainsi les approches les plus appropriées pour la planification et le contrôle des projets. Le cadre et le système d'aide à la décision développés ont été validés en les appliquant à une étude de cas de rénovation et en recevant des retours positifs de la part des experts. Enfin, une directive méthodologique détaillée a été élaborée pour faciliter la mise en œuvre du système de planification et de contrôle multi-niveaux recommandé par le SAD pour les projets de rénovation. Cette directive offre des instructions claires et étape par étape pour assurer une adoption simple et une intégration efficace dans les pratiques de gestion de projet. Cet outil polyvalent peut être appliqué à divers types de projets durant la phase de préconstruction, déterminant les stratégies de planification et de contrôle les plus efficaces en fonction des exigences fonctionnelles de l'équipe de projet
Facilitating information exchange for 3D retrofit models of existing assets using Semantic Web technologies
Full text linkBuilding Information Modelling (BIM) has gained a lot of momentum in new building projects in Architecture, Engineering, and Construction (AEC) for varying purposes like design, construction as well as Asset/Facilities Management (AM/FM). However, its use in existing buildings has been hampered by the challenges surrounding the limitations of available technologies used for generating retrofit models. In recent years, 3D laser scanning technology, as a remote sensing technique, has been extensively used to collect geometrical data from existing buildings. The output of this technology is a set of three-dimensional point measurements, also known as Point Cloud Data (PCD). In current practice, PCD is analysed and processed manually to generate BIM models utilising commercial BIM-driven platforms. Accordingly, several studies have been undertaken, proposing semi-automated approaches for generating parametric models by using PCD as the primary geometrical data source. An appropriate 3D model that is fit for purpose for a BIM-based process of design, construction, as well as operation and maintenance (O&M) of assets should incorporate geometrical and non-geometrical data. While the geometrical data can be extracted from the collected data, non-geometrical data may need to be appended to this for generating a genuinely semantically rich BIM model. On the other hand, a reliable data exchange framework could be beneficial within the AEC industry for O&M purposes. In this regard, a data exchange framework structured based on the Linked Data principles could be promising for creating a unified data format that would enhance the process of data exchange accordingly. This paper first outlines a framework proposed for generating semantically enriched 3D retrofit models for existing buildings by utilising the Resource Description Framework (RDF). RDF is utilised as a unified data format in the proposed framework to aggregate data captured from distributed offline and online data sources. The model, containing geometrical and non-geometrical data, is then generated through the conversion of RDF into IFC data model. However, the main focus of this paper is to propose a data exchange framework for populating the RDF data generated through the previously mentioned approach by using existing linked data schemas and vocabularies, such as Web Ontology Language for ifc (ifcOWL), Building Ontology Topology (BOT), Ontology for Managing Geometry (OMG),etc
Superimposing Building Information Models in Augmented Reality
Full text linkAugmented Reality (AR) can enhance Building Information Modelling (BIM) by allowing architecture, engineering, and construction (AEC) professionals to visualise and refine building models. The possibility of integrating BIM model in AR environment provides an effective solution to all phases of a building’s lifecycle. To visualise digital information in the actual physical environment, BIM models are superimposed to the structure. The techniques used to superimpose the BIM models are either based on reference markers or QR codes, which are occasionally inaccurate. This paper reviews and analyses the BIM model superimposing techniques in AR. To describe and discuss different methods, a BIM model of an office room was generated in Revit and superimposed to the actual physical space using two different AR devices and four different AR applications. From the results obtained, it can be concluded that presented superimposing methods allow for overlaying of digital information, but model positioning can be slightly inaccurate depending on the superimposing method used and AR device. Any inaccuracy while positioning the BIM model reference markers or QR code can lead to inaccurate superimposing of the model. The recommended process and method for superimposing BIM in AR environment is documented
BIM applications toward key performance indicators of construction projects in Iran
No full textBuilding Information Modeling (BIM) has recently emerged as a novel technology worldwide however literature review reveals a salient gap in the identification of BIM capabilities in Key Performance Indicators (KPI) of construction projects in Iran. Therefore, the aim of this research is to identify and prioritize the BIM applications toward KPIs in light of the construction stage of projects life cycle in Iran. To do this, a review of literature was performed on the KPIs and associated BIM contributions and the resultants were customized for Iranian context through a two-round Delphi study. An advanced Fuzzy-AHP approach was then applied in the prioritizations of KPIs and associated BIM capabilities via collecting data from construction practitioners. It was identified that quality improvement, sustainable construction and construction cost reduction are the top three KPIs that can be benefitted from BIM applications in the construction stage of building projects. It was also concluded that project coordination, clash detection, 4D and 5D BIM are the subsequent beneficial effects of BIM on the construction project KPIs in Iran. This study is a point of departure for BIM-based research and its managerial perspectives outlining an insight toward the application of BIM in the construction projects of Iran
Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality
Full text linkWelcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants
Specifying the information requirements for forensic delay analysis.
Full text linkDelays and late completion are familiar features of construction projects and are commonly accompanied by contractual claims and counter-claims as the parties concerned seek to protect their positions and mitigate their losses. In doing so, the organisations involved will often have recourse to consultants who specialise in the field of Forensic Delay Analysis (FDA). The FDA specialists then perform the analysis, and if required to, act as experts in presenting the results to dispute resolution or judicial hearings. The use of computer scheduling software, has for some time, been integral to the work of FD analysts. Despite this, typical FDA workflows have been heavily reliant upon imperfect, unstructured, manual information that requires a considerable time to collect and validate. This paper reports part of a project to develop a data-driven digital system for optimising the workflows and outputs a company already active in the field of FDA. It explores how FDA practitioners might exploit the growing availability of structured information within building information models to improve the efficiency and effectiveness of their work. The project comprised three stages: (I) to understand the workflows, technologies and operating context of the company; (II) to design a data-driven digital system for optimising workflows; and (III) to validate and refine that tool for market-testing. The results of Stages II and III will be made available in future publications. In Stage I of the study two main phases in the FDA process were identified, each with sub-phases. These begin with the FD analyst first establishing when and where a delay has occurred and quantifying its impact on completion. Next, the analyst must seek to determine why the delay occurred. This involves extensive audits of multiple information sources generated throughout the construction process. These sources typically exist in a variety of formats, included manually-generated material, and can be sparse, irregular, incomplete and sometimes contradictory. As a result, their extraction and validation take up a considerable part of the whole FDA process. The next stage involves the exercise of judgment as to which delay assessment methodology might be applicable to the information available and the current trends in judicial decisions. Finally, there is the production of a detailed report to the client and a presentation of the findings. The development of data-driven digital systems in FDA offers the prospect of enhanced visualization (hence, credibility) of these presentations. It also evokes the possibility of automating some of the time-consuming tasks associated with the process of claims preparation involving both quantitative and qualitative data that can be then subjected to numerical and non-numerical analysis. The requisite technologies are already available and could be integrated into a fully interoperable digitally-driven FDA system. However, the value of such a system would rely upon the collection and retrieval of adequate and credible information in a form that can be processed digitally: a situation that is currently rare. Following guidance such as that provided by the PAS documentation, there is an increased awareness amongst users of digital project models of their information requirements and how to specify them. A similar understanding and specification of the information requirements concerning the project delivery process would provide a basis for a data-driven progress monitoring system which could also, should the need arise, facilitate the extraction of evidence for the FDA process
Superimposing Building Information Models in Augmented Reality
Full text linkAugmented Reality (AR) can enhance Building Information Modelling (BIM) by allowing architecture, engineering, and construction (AEC) professionals to visualise and refine building models. The possibility of integrating BIM model in AR environment provides an effective solution to all phases of a building’s lifecycle. To visualise digital information in the actual physical environment, BIM models are superimposed to the structure. The techniques used to superimpose the BIM models are either based on reference markers or QR codes, which are occasionally inaccurate. This paper reviews and analyses the BIM model superimposing techniques in AR. To describe and discuss different methods, a BIM model of an office room was generated in Revit and superimposed to the actual physical space using two different AR devices and four different AR applications. From the results obtained, it can be concluded that presented superimposing methods allow for overlaying of digital information, but model positioning can be slightly inaccurate depending on the superimposing method used and AR device. Any inaccuracy while positioning the BIM model reference markers or QR code can lead to inaccurate superimposing of the model. The recommended process and method for superimposing BIM in AR environment is documented
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