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Paper w78-2001-29:
Tendering process model for application of reliability analysis

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Bester A, Huhnt W

Tendering process model for application of reliability analysis

Abstract:Construction data is a useful source of information for construction project management. The sources of data for various aspects of construction management is, in addition to the current project information and the engineer’s professional experience, also historical data from previous projects. An example of the use of historical cost data is in the application of the Limit State Cost Function (LSCF) model to perform construction project risk modelling. The LSCF-method was developed for assisting the consulting civil engineer to make a quantifiable judgement in the selection of a project tender. It is based on the reliability of estimating the outcome of the cost for a specific tender in terms of the risks involved in a project, by using construction cost data. The way in which this data have been captured has shown deficiencies which limits the utility of it if the scope of the data captured and the processes of both capturing and applying the results are not carefully planned. The application of the data can therefore not be seen without the process in which it is generated. The process is characterised by the generation and processing of data by the co-operation of several groups of persons at the different stages of the project. These groups of persons execute different tasks, for which appropriate subsets of information at different levels of detail are needed. The paper is focused on the specific requirements that have to be supported to model such processes. Tools are presented to support the specification of the process model. These tools enable the investigation of the model with respect to completeness and correctness. In addition, the tools support the implementation of an information system that is used in the execution of tasks during the tender process.


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Series:w78:2001 (browse)
Cluster:papers of the same cluster (result of machine made clusters)
Class:class.processing (0.052641) class.economic (0.016156) class.impact (0.011672)
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Permission to reproduce these documents have been graciously provided by CSIR Building and Construction Technology. The assistance of the editors, Mr. Gustav Coetzee and Mr. Frances Boshoff, is gratefully appreciated.


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