Building Information Modelling (BIM) is now a globally recognised phenomenon, though its adoption remains inconsistent and variable between and within the construction sectors of different countries. BIM technology has enabled a wide range of functional applications, one of which, ‘4D BIM’, involves linking the tasks in a project’s construction schedule to its object-orientated 3D model to improve the logistical decision making and delivery of the project. Ideally, this can be automatically generated but in reality, this is not currently possible, and the process requires considerable manual effort. The level of maturity and expertise in the use of BIM amongst the project participants still varies considerably; adding further obstacles to the ability to derive full benefits from BIM. Reflecting these challenges, two case studies are presented in this paper. The first describes a predominantly manual approach that was used to ameliorate the implementation of 4D BIM on a project in Paris. In fact, there is scope for automating the process: a combination of BIM and Artificial Intelligence (AI) could exploit newly-available data that are increasingly obtainable from smart devices or IoT sensors. A prerequisite for doing so is the development of dedicated ontologies that enable the formalisation of the domain knowledge that is relevant to a particular project typology. Perhaps the most challenging example of this is the case of renovation projects. In the second case study, part of a large European research project, the authors propose such an ontology and demonstrate its application by developing a digital tool for application within the context of deep renovation projects.
Buildings have a significant impact on energy consumption and carbon emissions. Smart buildings are deemed to play a crucial role in improving the energy performance of buildings and cities. Managing a smart building requires the modelling of data concerning smart systems and components. While there is a significant amount of research on optimising building energy using the smart building concept, there is a dearth of studies investigating the modelling and management of smart systems’ data, which is the starting point for establishing the necessary digital environment for representing a smart building. This study aimed to develop and test a solution for modelling and managing smart building information using an industry foundation classes (IFCs)-based BIM process. A conceptual model expressed in the SysML language was proposed to define a smart building. Five BIM approaches were identified as potential ‘prototypes’ for representing and exchanging smart building information. The fidelity of each approach is checked through a BIM-based validation process using an open-source visualisation platform. The different prototypes were also assessed using a multi-criteria comparison method to identify the preferred approach for modelling and managing smart building information. The preferred approach was prototyped and tested in a use case focused on building energy consumption monitoring to evaluate its ability to manage and visualise the smart building data. The use case was applied in a real case study using a full-scale demonstrator, namely, the ‘Nanterre 3’ (N3) smart building located at the CESI campus in Paris-Nanterre. The findings demonstrated that an open BIM format in the form of IFCs could achieve adequate modelling of smart building data without information loss. Future extensions of the proposed approach were finally outlined.
Building Information Modelling (BIM) can be defined as a set of tools, processes and technologies that are enabled by a digital multi-dimensional representation of the physical and functional characteristics of a built asset. The ‘fourth’ dimension (4D BIM) incorporates time-related project information in the 3D model to simulate and optimise the project construction process. To achieve this, the 3D objects within the aggregated design model must be linked with each activity in the construction schedule. However, the levels of maturity and expertise in using BIM amongst the project participants still varies considerably. This generates collaboration problems within the project and adds further obstacles to the ability to derive full benefits from BIM. Ideally, 4D BIM can be automatically generated, but in reality, because the 3D and 4D models are created separately and at different stages of the project, this is not currently possible, and the process requires considerable manual effort. The research reported in this paper was prompted by the construction of a new training and research building: the Nanterre 2 CESI building in France. It proposes an efficient approach that minimises the effort of creating 4D BIM construction schedules. The CESI four-phase process aims to help project participants to fully exploit the potential of 4D BIM and enables: 1) a clear expression of the 4D BIM objectives; 2) the identification of information requirements and relevant workflows to achieve these objectives; 3) the implementation of a project schedule; and 4) BIM model production to suit the 4D BIM use case. Although the CESI approach was developed in the context of the French contracting system, the observations and conclusions of this study are intended to be generally applicable.
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