Identification and rectification of errors in BIM models using dynamo

Abstract:

The productivity of facility managers in delivering healthy and energy efficient buildings can be determined by the information available for managing the building. Incomplete, inaccurate, and irrelevant information can compromise productivity. In a digitalized architecture, engineering, and construction (AEC) industry, facility managers are required to use building information modelling (BIM) models for their facility management operations. It is not uncommon for facility managers to submit incomplete, inaccurate, and irrelevant as-built BIM models to facility managers, leading to low productivity due to non-usage or usage of the BIM model with errors. Unfortunately, many facility managers do not have automated solutions for identifying and rectifying BIM errors. This study aims to provide automated programming solutions that could help facility managers identify and rectify errors in BIM models with the complexity level of a high rise building and transform the BIM model to a facility management ready model. The investigation on the validation of the developed automated programming solution with built environment professionals suggests that the solutions can considerably reduce the time taken and accuracy for correcting the BIM model and make it facility management ready. The participants’ feedback also suggests that the developed solution is satisfying to use, user friendly, and could improve the work process.  Lessons and ideas of the developed automated programming solution reported in this paper can help develop solutions that will aid the adoption of BIM models for facility management operations.  

Keywords: Facility management, Building information modelling, Computational BIM, Productivity, Dynamo

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Cite as: “Chua C and Fadeyi MO (2021).”Identification and rectification of errors in BIM models using dynamo. Built Environment Applied Research Sharing #04.  ISSUU Digital Publishing.”

Published by Moshood Fadeyi

Dr. Moshood Olawale Fadeyi, a creative professor, is an Associate Professor of Sustainable Building Value Delivery at the Singapore Institute of Technology. Dr. Fadeyi holds four university degrees, including a Ph.D. in Indoor Environment and Energy from the National University of Singapore and Technical University of Denmark. Dr. Fadeyi is architecture (BSc Arch and M.Arch.), building science (MSc.), and engineering (Ph.D.) trained. Dr. Fadeyi is an architect, an indoor air quality expert, chartered engineer (UK) – building services, chartered construction manager (UK), and specialist adult educator. Dr. Fadeyi is a member of the Chartered Institution of Building Services Engineers (UK), Chartered Institute of Building (UK), and American Society of Heating, Refrigerating, and Air-conditioning Engineers. Currently, Dr. Fadeyi research aims to enhance applied learning pedagogy to make students job-ready upon graduation and improve industry and community practices. His applied learning pedagogy enhancement is informed by applied research, artistic research, and case study research grounded in design, critical, reflective, scientific, and lean thinking and digital solutions adoption. He has written more than 180 published scholarly and peer-reviewed articles in line with applied learning pedagogy enhancement and basic research. Dr. Fadeyi research and scholarship domain are in (i) value-oriented productivity in healthy and energy-efficient indoor air delivery, (ii) value-oriented productivity in design, construction, and facility management practices, and (iii) problem-based learning. Dr. Fadeyi researches to educate and solve industry and community-related problems. Dr. Fadeyi expertise and leadership are highly sought after by companies and government agencies. Dr. Fadeyi is the Editor, Author, and Cartoonist of Indoor Air Cartoon Journal – an online learning resource providing applied learning on IAQ with audiences from over 100 countries. Dr. Fadeyi is a former National Taekwondo Champion in Singapore - Black Belt Middle-Heavy Weight category, 2006.

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