Assessment and Prediction Planning of R.C Structures Using BIM Technology | ||||
Engineering Research Journal | ||||
Article 23, Volume 167, Issue 0, September 2020, Page 394-403 PDF (1.3 MB) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/erj.2020.145845 | ||||
View on SCiNiTO | ||||
Authors | ||||
Nahla Ali Mohamed* 1; Ahmed Mohammed Abdel-Alim2; Hatem Hamdy Ghith3; Alaa Gamal Sherif4 | ||||
1Assistant Lecturer at Housing and Building National Research Center, Cairo, Egypt. | ||||
2Associate Professor of Project Management, faculty of engineering at Mataria , Helwan University, Cairo, Egypt. | ||||
3Professor of R.C Structure Housing and Building National Research Center, Cairo, Egypt | ||||
4Professor of R.C Structures , faculty of engineering at Mataria, Helwan University, Cairo, Egypt. | ||||
Abstract | ||||
Using Building information modeling (BIM) is very useful to facilitate the condition assessment of the building and record all rehabilitation work that has taken place during its life cycle through the building life cycle. The asset owners can receive the benefit of using BIM by incorporating the principles of BIM into the operation and maintenance of buildings. The main focus is on the integration of maintenance data by using building information modeling (BIM) to facilitate efficient inspection planning and to improve the condition assessment process for building elements. This paper presents a framework based on BIM for buildings condition assessment. The framework consists of two models: Condition Assessment Model and deterioration Predictive Model. The Condition Assessment Model manages the condition data that are collected during visual inspection. Integrated with failure records and life cycle prediction models, the deterioration predictive Model integrates with the Condition Assessment Model and forecasts elements failure. The results provide a basis for predictive maintenance of building elements. BIM is also adapted to manage and visualize not only the inspection data but also the predictive maintenance data. | ||||
Keywords | ||||
Condition Assessment; Building Information Modeling; surface condition; deterioration predictive model; Life cycle prediction; Maintenance action; Failure prediction | ||||
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