BIM-Integrated Construction Operation Simulation for Just-In-Time Production Management

WoonSeong Jeong, Soowon Chang, JeongWook Son and June-Seong Yi
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WoonSeong Jeong: Department of Architectural Engineering, Ewha Womans University, 52, Ewhayeodae-Gil, Seodaemun-Gu, Seoul 03760, Korea
Soowon Chang: School of Building Construction, Georgia Institute of Technology North Avenue, Atlanta, GA 30332, USA
JeongWook Son: Department of Architectural Engineering, Ewha Womans University, 52, Ewhayeodae-Gil, Seodaemun-Gu, Seoul 03760, Korea
June-Seong Yi: Department of Architectural Engineering, Ewha Womans University, 52, Ewhayeodae-Gil, Seodaemun-Gu, Seoul 03760, Korea

Sustainability, 2016, vol. 8, issue 11, 1-25

Abstract: Traditional construction planning, which depends on historical data and heuristic modification, prevents the integration of managerial details such as productivity dynamics. Specifically, the distance between planning and execution brings cost overruns and duration extensions. To minimize variations, this research presents a Building Information Modeling (BIM)-integrated simulation framework for predicting productivity dynamics at the construction planning phase. To develop this framework, we examined critical factors affecting productivity at the operational level, and then forecast the productivity dynamics. The resulting plan includes specific commands for retrieving the required information from BIM and executing operation simulations. It consists of the following steps: (1) preparing a BIM model to produce input data; (2) composing a construction simulation at the operational level; and (3) obtaining productivity dynamics from the BIM-integrated simulation. To validate our framework, we applied it to a structural steel model; this was due to the significance of steel erections. By integrating BIM with construction operation simulations, we were able to create reliable construction plans that adapted to project changes. Our results show that the developed framework facilitates the reliable prediction of productivity dynamics, and can contribute to improved schedule reliability, optimized resource allocation, cost savings associated with buffers, and reduced material waste.

Keywords: productivity dynamics; building information modeling; computer simulation; Just-In-Time; lean construction; data reuse (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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