z-logo
open-access-imgOpen Access
Automatic Selection Tool of Quality Control Specifications for Off-site Construction Manufacturing Products: A BIM-based Ontology Model Approach
Author(s) -
Pablo Martı́nez,
Rafiq Ahmad,
Mohamed AlHussein
Publication year - 2019
Publication title -
modular and offsite construction (moc) summit proceedings
Language(s) - English
Resource type - Journals
ISSN - 2562-5438
DOI - 10.29173/mocs87
Subject(s) - building information modeling , ontology , information model , quality (philosophy) , computer science , quality assurance , frame (networking) , product (mathematics) , control (management) , systems engineering , engineering , software engineering , artificial intelligence , telecommunications , philosophy , operations management , external quality assessment , geometry , mathematics , epistemology , compatibility (geochemistry) , chemical engineering
Construction manufacturing specifications play an important role in assessing quality requirements on a construction project. However, working with these specifications can be overly complicated and error prone to the large amount of regulations and codes that need to be considered and their inter-dependencies. In building information modelling (BIM), the model is a digital representation of a complex construction product and contains precise product information data. The data is currently embedded into the model as properties for parametric building objects that are exchangeable among project operators. Some effort has been previously done to enhance the BIM model to obtain construction-oriented data and linking information that is crucial to manufacturing and quality control and assurance with BIM modelling still remains a challenge. This study proposes an extension to the current BIM-based product-oriented ontology model to include manufacturing processes and inspection, and quality control specifications. By automatically identifying which specifications are applicable to certain products and to extract the requirements imposed, this approach can support and enable automatic decision making in quality inspection and control tasks, which solely depend on information and knowledge from construction specifications. This approach is tested and validated using a light-gauge steel frame wall under Canadian construction standards and regulations.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom