Date of Award

Spring 1-1-2014

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

First Advisor

Paul M. Goodrum

Second Advisor

Keith R. Molenaar

Third Advisor

Matthew R. Hallowell

Fourth Advisor

Rajagopalan Balaji

Fifth Advisor

Tom Yeh

Abstract

Construction productivity is of essence to the construction industry, since it directly or indirectly relates to the cost and schedule performance of a project. Construction projects are typically undertaken in an intricate and dynamic environment. Numerous factors, such as information, equipment, tools, materials, weather, supervision, safety, sequencing, congestion, can affect the productivity of a project's craft workers. A better understanding of how these and other factors impact a project can help practitioners better predict the performance of a project's outcomes. Currently, the lack of a robust framework to model and simulate the factors on a construction project's productivity compromises the ability to accurately assess the factors' impact on a project's performance. However, Building Information Modeling (BIM) is a sophisticated platform that offers the potential to fulfill this need. BIM not only contains 3D graphical information of the various objects but also the objects' attributes, such as cost, schedule, specification, and other information. The objective of this research is to develop a proof of concept of a framework to model productivity factors with an assistance of BIM and lower level critical path scheduling. As a starting point, this research focuses on structural steel erection projects only, employing model projects, computer simulation, and quantitative analysis to test and validate the framework. This research contributes to the overall body of knowledge by providing a framework to develop prototypical models on which various factors affecting construction productivity, new construction methods, and materials can be tested and their impact can be simulated and assessed.

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