https://doi.org/10.24928/2019/0250
Predicting Performance Indicators Using BIM and Simulation for a Wall Assembly Line
Ryan Brown1, Beda Barkokebas2, Chelsea Ritter3 & Mohamed Al-Hussein4
1M.Sc. Student, Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada, [email protected]2PhD Student, Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada, [email protected]
3PhD Student, Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada, [email protected]
4Professor, Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada, [email protected]
Abstract
Off-site home construction allows for the construction of building components to be completed in an off-site facility. The floors, walls, and roof are constructed on separate production lines, then shipped together to site for installation. This type of home construction presents a good opportunity to utilize lean manufacturing principles allied with simulation methods to better industrialize the home building process. This paper presents a case study of a well-known panelized residential home manufacturer, where the focus is the wall assembly line. Multiple key performance indicators (KPIs) are calculated in order to forecast production for each project and key result indicators (KRIs) are used to predict the outcomes of multiple projects. The predicted performance indicators are found through a simulation model of the production line using quantity take-offs extracted from BIM models. The analysis of these performance indicators will be used to evaluate project feasibility when the project is built in an off-site construction facility.
Keywords
Lean construction, off-site construction, performance indicators, computer simulation, variability.
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Reference
Brown, R. , Barkokebas, B. , Ritter, C. & Al-Hussein, M. 2019. Predicting Performance Indicators Using BIM and Simulation for a Wall Assembly Line, Proc. 27th Annual Conference of the International Group for Lean Construction (IGLC) , 853-862. doi.org/10.24928/2019/0250
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