Automated BCF Data Extraction For BIM QC Communication
Romero, Antonio (2019)
2019
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2019110620717
https://urn.fi/URN:NBN:fi:amk-2019110620717
Tiivistelmä
According to multiple studies, communication in the AEC industry is a large, evident problem that should be addressed in order to minimize errors and maximize overall quality. Simultaneously, the AEC industry is taking a disruptive step by highly integrating Information Technologies and Automatization in its workflows to accelerate efficiency and provide better suited solutions. How industry members adopt and change to integrate this new work approach, will define how the industry will develop and who will emerge as leader in the next decades.
BIM coordination is now an essential part of the modern construction process, both consuming and generating large amounts of information that result in the digital model that will be used to physically build and maintain the object. These large amounts of data result in an “information overload” situation, leading to dense fragmented data, lack of accountability, and failure to address problems among other, being this problem particularly acute as multiple disciplines join the model.
This thesis tries to solve this problem by developing the implementation for an automated issue (topic) tracking and quality control dashboard reporting system that would, if not necessarily solve, help to mitigate this problem by turning the current issue tracking trough single files into a more manageable and integrated way of storing, sharing and presenting BCF information.
BIM coordination is now an essential part of the modern construction process, both consuming and generating large amounts of information that result in the digital model that will be used to physically build and maintain the object. These large amounts of data result in an “information overload” situation, leading to dense fragmented data, lack of accountability, and failure to address problems among other, being this problem particularly acute as multiple disciplines join the model.
This thesis tries to solve this problem by developing the implementation for an automated issue (topic) tracking and quality control dashboard reporting system that would, if not necessarily solve, help to mitigate this problem by turning the current issue tracking trough single files into a more manageable and integrated way of storing, sharing and presenting BCF information.