| Title |
The Development of Productivity Prediction Model for Interior Finishes of Apartment using Deep Learning Techniqeus |
| Authors |
Lee, Giryun ; Han, Choong-Hee ; Lee, Junbok |
| DOI |
http://dx.doi.org/10.6106/KJCEM.2019.20.2.003 |
| Keywords |
Productivity ; Prediction Model ; Productivity Impacting Factors ; Deep Learning ; Interior Finishes |
| Abstract |
Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures. |