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Okoroh, M.I.

This thesis describes the results of research analysing the sub-contractor's risk elements
in refurbishment projects. One of the main characteristics of refurbishment projects is
that work is usually in small packages and scattered throughout the building making it
unprofitable for one contractor to undertake. It is argued that the selection and
appointment of the most suitable sub-contractors is very important in refurbishment
projects as all other control measures have little effect once a totally unsuitable subcontractor
has been appointed.
The research methodology involved the extensive collaboration of a retired chief
estimator with over thirty years experience in one of Britain's biggest construction firms
with extensive knowledge in the management of sub-contractors and several other
refurbishment contractors' senior management staff who were involved in choosing subcontractors
for their contracts.
Knowledge acquisition and representation and the evaluation of expert system shells are
extensively reviewed.
One of the important features of knowledge based systems is its ability to handle
uncertain knowledge. Fuzzy set theory is shown to have certain advantages over other
methods of dealing with uncertainty and has been employed in developing this
knowledge based system.
The research began with an evaluation of sub-contractors' selection and appointment as
it is currently performed by refurbishment contractors. This exercise consisted of a wide
range of criteria of which information is both qualitative and subjective in an
unstructured intuitive manner with considerable reliance on the judgement of the
evaluee. Thus, the research focused on a more formalised approach to the subcontractor's
appointment. An adaptation of the Repertory Grid knowledge elicitation
technique and subsequent grid analysis provides a methodology for organising logically
related propositions into a hierarchical structure.
A prototype knowledge based decision support system SSARC, for the selection and
appointment of the most suitable sub-contractors for refurbishment projects, has been
developed. This system represents a contribution in this area of research into
refurbishment contracts which has been largely neglected to date

Michael I. Okoroh (7182176)

Loughborough University Institutional Repository

English

Knowledge based decision support system for the selection and appointment of sub-contractors for building refurbishment contracts

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https://repository.lboro.ac.uk/articles/Knowledge_based_decision_support_system_for_the_selection_and_appointment_of_sub-contractors_for_building_refurbishment_contracts/9455597/files/17078627.pdf

Knowledge based decision support system for the selection and appointment of sub-contractors for building refurbishment contracts

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