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Risk analysis in mangement planning and project control. (Probabilistic techniques are applied to the estimation, planning, forecasting and control of large capital projects to ascertain and reduce the degree of inherent risk and uncertainty)

Effective estimation, planning, and control of the functions,
operations, and resources of a project are among the most challenging
tasks faced by the management of today's engineering and construction
organisations. The increase in size and complexity of modern projects
demand a sound organisational structure and a rational approach.
The main objectives of the present study are two-fold. Firstly
to report and critically review theoretical and practical developments
of different aspects of the management of engineering and construction
projects. Secondly to further develop conceptual, practical techniques
and processes; also to provide Guidelines to make more effective use. of
resources and systems. To achieve these objectives the present research
was carried out in close collaboration with various indurtrial organisations.
The current literature on project management is critically examined
from the point of View of project cost estimation, planning and control.
Various existing and recommended procedures, approaches and techniques are reviewed with particular emphasis on using probabilistic techniques.
As the problems of scale are increasing, progressively more
industries are adopting systems and project management approaches.
Problems, deficiencies and gaps in the existing systems are identified.
An analysis of a questionnaire survey on Systems-Caps is carried out and
the results of the analysis are reported. .
S-curves (or progress curves) are widely used in the plauaing
and control of cost, time and resources. A mathematical model for the
S-curve is adopted for this purpose. Expenditure data on a number of
ii
recent projects is analysed and fitted to two S-curve models suggested
by Keller-Singh and the Department of Health and Social Security
(D. H. S. S. ). A comparative study of the models is carried out. A set
of standard parameters for the models is obtained and the predicting
accuracy of these models for forecasting expenditure for future similar
projects investigated.
Quantification aspects of risk involved with the completion time
of a project are studied. 'A number of stochastic distributions arc
fitted for this purpose to the programed and actual durations for the
different activities of a housing project. The maximum likelihood
method is used for the estimation of parameters of the fitted
distributions.
Due to the increasing use of indices in the construction industry,
building cost and tender price indices, their application, limitations
and methods of formation are discussed. Box-Jenkins models are
employed to study past behaviour and to forecast future trends for labour,
materials and building cost indices.
Finally, general conclusions derived from the present regearch are
sunmarised and areas requiring further research are proposed.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/3572
Date January 1981
CreatorsAshrafi, Rafi A.
ContributorsKeller, A.Z.
PublisherUniversity of Bradford, Industrial Technology
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeThesis, doctoral, PhD
Rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.

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