Quantitative Modelling Methods for the Incorporation of Uncertainty into Construction Project Estimates
Date
2007-12
Authors
Adams, Russell John
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : University of Stellenbosch
Abstract
Most construction projects do not complete exactly as scheduled or exactly as priced.
During the implementation of a project there is almost certainly some deviation from the
original estimate. The implementation of a majority of projects has actually been shown
to cost more and take longer than originally estimated. However, the duration and cost
performance of a project’s implementation is measured against the initial estimate
produced. Thus if a project is considered to have completed late or over budget then
essentially the duration or cost estimated was insufficient.
Due to the fact that estimates are produced in a present day environment for inherently
unique projects that occur in uncertain future environments, the estimates produced will
need to incorporate uncertainty to increase their likelihood of achievability.
This study aims to derive methods to incorporate future uncertainty into project
estimates. This uncertainty is incorporated, analysed and manipulated through the use
of Probabilistic models and First Order Second Moment Reliability methods. The derived
methods provide project management professionals with tools that enable them to
design estimates that incorporate future uncertainty and are reliable to a specified
degree. Further methods are then derived to probabilistically assess the commercial
feasibility of a project in an uncertain future environment.
These derived methods then provide project managers and decision makers with more
reliable procedures and information which in turn should assist them in making correct,
project orientated decisions and ultimately increase profit reliability and client
satisfaction.
Description
Thesis (MEng (Civil Engineering))--University of Stellenbosch, 2006.
Keywords
Uncertianty modelling, Construction estimate, Quantitive methods, Relaibility, Theses -- Civil engineering, Dissertations -- Civil engineering