4 research outputs found

    Leveraging Quantity Surveying Data and BIM to Automate Mechanical and Electrical (M & E) Construction Planning

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    Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings’ data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept

    Interaction Lean-BIM en phase exécution de projet de construction : Développement d’un outil de planification automatique basé sur les informations du bâtiment pour soutenir la démarche LPS®

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    In recent years, the construction sector has experienced a decline in productivity compared to other industries. This decrease is primarily due to the delayed and slow adoption of lean production methods and new technologies. To enhance its productivity, the construction sector must expedite its adoption of Lean Construction (LC) techniques and Building Information Modeling (BIM). These solutions have proven to be effective in improving collaboration among project stakeholders, optimizing design and construction processes, and consequently enabling faster, better, and more cost-effective construction. Despite the separate development and implementation of these solutions, research has shown a strong interest in their combined application.In order to contribute to the co-application of LC and BIM, based on a state-of-the-art review, our research has led to the identification of a promising interaction between these two approaches. This connection links the Last Planner System® (a collaborative planning method of LC) with the visualization functions of BIM. Furthermore, a detailed analysis of tools combining LPS® and BIM has shown that the utilization of data generated by these two approaches is not yet fully integrated. To enhance the integration between LPS® and BIM, we propose, through this thesis, to automate the generation of tasks in the collaborative planning of the LPS® approach using operational data from a construction project, including data from the BIM digital model. Automating the planning process allows decision-makers to eliminate tedious manual work, resulting in time and cost savings. Moreover, it leverages the project's operational data to create added value, demonstrating a leaner management approach to building information, known as "Lean Building Information Management."On a technological level, our work has allowed us to implement a tool (a web application) that automatically generates a spatio-temporal schedule using real construction project data of the HVAC (heating, ventilation, and air conditioning) discipline. These pieces of information include project estimation data generated during the tendering phase, data from the digital model created during the detailed design stage, the client’s milestones, as well as standards of equipments’ installation operations. The implementation of this solution required a preliminary analysis of user needs and input data, meticulous work to define and standardize the equipments’ installation operations as well as several developments, including software development.Finally, functional and analytical evaluations were conducted to verify the coherence of the results generated by the solution, as well as to assess to what extent its functionalities meet the needs of end users.The results obtained in this thesis pave the way for several future works, particularly in the field of continuous management of construction projects data throughout their life cycles, through the use of data warehouses.Ces dernières années, le secteur de la construction a connu une baisse de productivité par rapport aux autres secteurs d'activité. Cette chute est principalement due à l’adoption tardive et ralentie des méthodes de production allégées et des nouvelles technologies. Pour améliorer sa productivité, le secteur de la construction doit accélérer son adoption des techniques du Lean Construction (LC) et du BIM. Ces solutions s’avèrent être efficaces pour améliorer la collaboration entre les acteurs d’un projet, optimiser les processus de conception et de construction et par voie de conséquence construire vite, mieux et moins cher. Malgré le développement et la mise en œuvre séparés de ces solutions, des travaux de recherche ont montré un fort intérêt quant à leur application conjointe.Afin de contribuer à la co-application du LC et du BIM, et en se basant sur un état de l’art, nos travaux de recherche ont conduit à l’identification d’une interaction prometteuse entre ces deux approches. Celle-ci relie la méthode Last Planner System® (méthode de planification collaborative du LC) aux fonctions de visualisation du BIM. Par ailleurs, une analyse détaillée des outils combinant le LPS® et le BIM a montré que l’exploitation des données générées par ces deux approches ne fait pas encore l’objet d’une intégration complète. Pour améliorer l’intégration entre le LPS® et le BIM, nous proposons à travers cette thèse d’automatiser la génération des tâches du planning collaboratif de l’approche LPS® à partir des données opérationnelles d’un projet de construction, y compris les données de la maquette numérique BIM. L’automatisation de la planification permet aux décideurs de s’affranchir du travail manuel fastidieux, ce qui se traduit par un gain de temps et économique. De plus, elle capitalise sur les données opérationnelles du projet pour créer de la valeur ajoutée, ce qui témoigne d’une gestion plus légère des informations du bâtiment, c’est-à-dire d’une approche « Lean Building Information Management ».Sur le plan technologique, nos travaux ont permis de mettre en place un outil (une application Web) permettant de générer automatiquement un planning spatio-temporel en utilisant les données du génie climatique d’un projet de construction réel. Ces informations incluent les données de chiffrage du projet produites en phase avant-vente, les données de la maquette numérique modélisées en phase d’études d’exécution, les jalons imposés par le client ainsi que les données standards des opérations de mises en œuvre des équipements. La mise en œuvre de cette solution a nécessité une analyse préalable des besoins des utilisateurs, des données d’entrées, un travail rigoureux pour rédiger et standardiser les opérations de mise en œuvre des équipements, ainsi que plusieurs développements notamment informatiques.Enfin, des évaluations fonctionnelles et analytiques ont été menées afin de vérifier la cohérence des résultats générés par la solution, ainsi que pour évaluer dans quelle mesure ses fonctionnalités répondent aux besoins des utilisateurs finaux.Les résultats obtenus dans le cadre de cette thèse ouvrent la voie à plusieurs travaux futurs, notamment en matière de gestion continue des données des projets de construction tout au long de leurs cycles de vie, grâce à l’utilisation des entrepôts de données (DataWarehouse)

    Leveraging Quantity Surveying Data and BIM to Automate Mechanical and Electrical (M & E) Construction Planning

    No full text
    Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings’ data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept

    Toward BIM and LPS Data Integration for Lean Site Project Management: A State-of-the-Art Review and Recommendations

    No full text
    Over recent years, the independent adoption of lean construction and building information modeling (BIM) has shown improvements in construction industry efficiency. Because these approaches have overlapping concepts, it is thought that their synergistic adoption can bring many more benefits. Today, implementing the lean–BIM theoretical framework is still challenging for many companies. This paper conducts a comprehensive review with the intent to identify prevailing interconnected lean and BIM areas. To this end, 77 papers published in AEC journals and conferences over the last decade were reviewed. The proposed weighting matrix showed the most promising interactions, namely those related to 4D BIM-based visualization of construction schedules produced and updated by last planners. The authors also show evidence of the lack of a sufficiently integrated BIM–Last Planner System® framework and technologies. Thus, we propose a new theoretical framework considering all BIM and LPS interactions. In our model, we suggest automating the generation of phase schedule using joint BIM data and a work breakdown structure database. Thereafter, the lookahead planning and weekly work plan is supported by a field application that must be able to exchange data with the enterprise resource planning system, document management systems, and report progress to the BIM model
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