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Permanent link (DOI): https://doi.org/10.7939/R3W669H4N

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BIM-Based Data Mining Approach to Estimating Job Man-Hour Requirements in Structural Steel Fabrication Open Access

Descriptions

Other title
Subject/Keyword
Structural Steel Fabrication
Quantity Takeoff
Linear Regression
BIM
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Hu, Xiaolin
Supervisor and department
Lu, Ming (Civil and Environmental)
Abourizk, Simaan (Civil and Environmental)
Examining committee member and department
Abourizk, Simaan (Civil and Environmental)
Al-Hussein, Mohamed (Civil and Environmental)
Lu, Ming (Civil and Environmental)
Davies, Evan (Civil and Environmental)
Department
Department of Civil and Environmental Engineering
Specialization
Construction Engineering and Management
Date accepted
2014-10-24T08:54:18Z
Graduation date
2015-06
Degree
Master of Science
Degree level
Master's
Abstract
In a steel fabrication shop, jobs from different clients and projects are generally processed simultaneously in order to streamline production processes, improve resource utilization, and achieve cost-effectiveness in serving multiple concurrent steel-erection sites. Reliable quantity takeoff on each job and accurate estimation of shop fabrication man-hour requirements are crucial to plan and control fabrication operations and resource allocation on the shop floor. Building information modeling (BIM) is intended to integrate multifaceted characteristics of a building facility, but finds its application in structural steel fabrication largely limited to design and drafting. This research focuses on extending BIM’s usage further to the planning and control phases in steel fabrication. Using data extracted from BIM-based models, a linear regression model is developed to provide the man-hour requirement estimate for a particular job. Actual data collected from a steel fabrication company was used to train and validate the model. Two Excel macro-enabled workbooks were also developed to provide decision-making support in fabrication planning.
Language
English
DOI
doi:10.7939/R3W669H4N
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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