Various projects in different disciplines undergo multiple stages before completion. Due to diversity and specialization, all the development stages of such projects are managed and developed by various people whose objectives are to complete their specific tasks after which they merge their work with others to fully complete such particular projects. Unlike many years back, today more and more projects are becoming more complicated thanks to rapid advancement in technology, meaning more people from different fields have to work together.
However, the primary challenge has always been how to effectively communicate and share information among the stakeholders handling such big and complex projects. For instance, in the building and construction industries, a variety of expertise comprises the design architects, structural engineers, electrical engineers, contractors among others depending on the nature of the project are required. In all the areas mentioned, different software is needed for the design, creation, analyzing and manipulation of the various data concerning the project. For the project to be achieved within the stipulated time duration, the data has to be maintained and observed throughout the development phases of the project.
However, considering the different scopes and nature of the projects, the vast set of data involved has become a problem to handle in the industries. For example, as the project development is underway, a particular group of the participants may realize some critical changes, which may be affected without consulting the others hence leading to design problems that may hinder the proper development of the project.
To enhance the collaboration, cooperation and communication among the projects managers, professionals and other relevant stakeholders, a more comprehensive way of sharing the project information and data need to be put in place.
Professor Yong-Cheol Lee at Louisiana State University in collaboration with Professor Charles Eastman and Wawan Solihin at the Georgia Institute of Technology in the United States identified different logic that will ensure effective data exchange as well as the integrity of building information models among the various project builders and managers. The research work is published in the journal, Automation in Construction.
The research team successfully identified the neutral formats that have been widely used for sharing data and information, especially in the architecture, engineering and construction industries. Industry foundation classes (IFC) and its subset, model views definition (MVD) are very diverse and capable of supporting exportation and importation of building model data hence ensuring accuracy and integrity.
The authors acknowledge a high level of quality in the building models attributed to the ability to detect correctness and accuracy of the IFC file in line with the provided model view automatically. The validation process is also simple hence time-saving as it does not require much effort input from the software developers and industrial professionals charged with the management and development of the project.
Generally, this application framework will advance building and construction industries by supporting continuous sharing of the BIM data while at the same time confirming their accuracy, validity, and quality. This will eliminate unseen errors that may be costly in the long run hence leading to effectively and professionally managing the projects throughout its development phases to completion.
Based on the IfcDoc platform, to implement the identified rule logic, the rule types are coded for execution on the IfcDoc tool and used for addressing diverse scenarios of model view specifications. The logical expressions that contain types of rules and the composition order of rules were used to manually develop rule checking features and compose them for MVD checking according to logic. Each rule type identified in the PCI MVD was developed as checking features and added on IfcDoc. The rule types include two broad categories: value and type checking. The value checking includes the accuracy of an attribute value, the existence of attributes, entities, and references, and the number of instances for an attribute. The type checking deals with the super/subtype checking, relationships, data aggregation, enumeration, and the ratio of the cardinality. Implementation of additional rule sets can be achieved by combining data correctness, relationships, and conditional checking. Figure 1 shows the architecture of identifying the rule types of the PCI MVD and implementing them on the IfcDoc tool. Figure 2 is the checking report in the user interface of the IfcDoc tool.
Lee, Y., Eastman, C., & Solihin, W. (2018). Logic for ensuring the data exchange integrity of building information models. Automation in Construction, 85, 249-262.
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