Abstract
Offsite construction offers improved quality control, faster project completion, and reduced on-site disruptions compared to traditional onsite construction methods. Steel fabrication plays a pivotal role in offsite construction, as it enables the precise manufacturing of structural components in a controlled environment, ensuring enhanced accuracy and efficiency during assembly at the construction site. In steel fabrication plants, low productivity estimates lead to cost overruns, project delays, resource allocation problems, and reputational damage. To mitigate these consequences, this study aims to develop an accurate estimation model to predict production time in a steel fabrication plant. This study involves three main parts: (1) time studies in steel fabrication plant stations and fitting Linear Regression (LR) models to estimate productivity. (2) Extraction of project complexity from 3D models using application programming interfaces (API). (3) Estimating projects productivity using the LR model and extracted features. This research focuses on six stations on a production line. Using industrial project productivity reports, the results of this study show an average correlation of 95% with actual duration at each station. Cost control, timely project completion, and client satisfaction are the significance of precise productivity estimates.
Original language | English |
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Number of pages | 10 |
Publication status | Accepted/In press - 9 May 2024 |
Event | CSCE Annual Conference - Sheraton Fallsview Hotel, Niagara Falls, Canada Duration: 5 Jun 2024 → 7 Jun 2024 https://www.csce2024niagara.ca/ |
Conference
Conference | CSCE Annual Conference |
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Abbreviated title | CSCE 2024 |
Country/Territory | Canada |
City | Niagara Falls |
Period | 5/06/24 → 7/06/24 |
Internet address |
Keywords
- Off-site construction
- Steel Fabrication
- Building Information Modeling
- Productivity Modeling