4.6 Article

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

Journal

SUSTAINABILITY
Volume 8, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/su8111106

Keywords

productivity dynamics; building information modeling; computer simulation; Just-In-Time; lean construction; data reuse

Funding

  1. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Science, ICT and Future Planning [NRF-2016R1A2B4015977]
  2. National Research Foundation of Korea [2016R1A2B4015977] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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.

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