Modified BIM Processes Considering Safety–Quality Index for Precast Concrete Construction
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 1
Abstract
Precast concrete construction (PCC) is one of the most innovative and efficient methods in construction, but the separate processes involved in this method are one of its disadvantages. Therefore, the project owners considered quality management of PCC based on the Building information modelling (BIM) technique as a key factor to achieving desired tolerances, combining the separated process, and decreasing errors. This study was conducted to modify BIM processes based on dimensionless indices of PCC. The Fuzzy-decision-making trial and evaluation laboratory (DEMATEL) method was used to obtain the weight of variables. Genetic expression programming (GEP) was then used to estimate the modified BIM index () in the PCC according to other important indicators as input data. The statistical results comparing the predicted and calculated values of show that there is a low root-mean-square-error (RMSE) of 0.027, low MAE of 0.019, and high of 0.95 in the testing process. Thus, there is good agreement between the relationship of and the calculated values that the proposed algorithm in this study can predict with high accuracy. The sensitivity analysis illustrates that the index of system quality () has the most significant effect on in comparison with other indices.
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Data Availability Statement
All data, models, or developed codes that support the findings of this study are available from the corresponding author upon reasonable request.
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Information & Authors
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 1 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Nov 30, 2021
Accepted: Jul 19, 2022
Published online: Nov 25, 2022
Published in print: Mar 1, 2023
Discussion open until: Apr 25, 2023
ASCE Technical Topics:
- Analysis (by type)
- Architectural engineering
- Artificial intelligence and machine learning
- Building information modeling
- Building management
- Business management
- Computer programming
- Computing in civil engineering
- Concrete
- Concrete construction
- Construction (by type)
- Construction engineering
- Construction methods
- Engineering fundamentals
- Engineering materials (by type)
- Errors (statistics)
- Fuzzy logic
- Management methods
- Materials engineering
- Mathematics
- Practice and Profession
- Precast concrete
- Quality control
- Sensitivity analysis
- Statistics
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