Quantitative Modelling Methods for the Incorporation of Uncertainty into Construction Project Estimates

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dc.contributor.advisor Retief, J. V.
dc.contributor.author Adams, Russell John en_ZA
dc.contributor.other University of Stellenbosch. Faculty of Engineering. Dept. of Civil Engineering.
dc.date.accessioned 2008-06-30T09:00:51Z en_ZA
dc.date.accessioned 2010-06-01T08:46:13Z
dc.date.available 2008-06-30T09:00:51Z en_ZA
dc.date.available 2010-06-01T08:46:13Z
dc.date.issued 2007-12
dc.identifier.uri http://hdl.handle.net/10019.1/2329
dc.description Thesis (MEng (Civil Engineering))--University of Stellenbosch, 2006.
dc.description.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. en_ZA
dc.language.iso en en_ZA
dc.publisher Stellenbosch : University of Stellenbosch
dc.subject Uncertianty modelling en_ZA
dc.subject Construction estimate en_ZA
dc.subject Quantitive methods en_ZA
dc.subject Relaibility en_ZA
dc.subject Theses -- Civil engineering en_ZA
dc.subject Dissertations -- Civil engineering en_ZA
dc.subject.lcsh Project management en_ZA
dc.subject.lcsh Building -- Estimates en_ZA
dc.subject.lcsh Construction industry en_ZA
dc.subject.lcsh Construction projects en_ZA
dc.subject.other Civil engineering en_ZA
dc.title Quantitative Modelling Methods for the Incorporation of Uncertainty into Construction Project Estimates en_ZA
dc.type Thesis en_ZA
dc.rights.holder University of Stellenbosch


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