Development of a Quantitative Maintenance Model

Maria Del Carmen Garcia Lizarraga, Jyoti Sinha

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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The availability of any productive system within an industry is strongly
related to the quality and efficiency of its maintenance management system. It
is through maintenance, that the highest asset reliability can be achieved. Though,
it also interests industry the optimisation of maintenance costs in contrast to the
safety implications of not performing any maintenance activity. In order to accomplish
this, every industry designs its own philosophy for planning and executing
maintenance activities. However, the times at which an asset is to be maintained,
have traditionally been selected based on operational experience and
original equipment manufacturer (OEM) recommendations. This kind of generic
and qualitative information may not be the adequate technical support for preventing
equipment downtime. In the interest of making a more informed decision on
when a piece of equipment needs to be maintained, it is necessary to count on a
quantitative maintenance model. Such an approach is able to provide the asset data
that is essential to identify any deviation from its expected performance. Hence,
maintenance is executed only when such deviations are found. Through this only
when required maintenance philosophy, downtimes can be reduced and resources
can be more efficiently utilised, without compromising safety. Then, a quantitative
approach is a more effective way to achieve the desired plant availability through
the asset reliability improvement. This paper describes the development of a quantitative
maintenance model. The model has been derived from the critical analysis
of current maintenance practices in industry as well as from a case study selected
from the power generation industry.
Original languageEnglish
Title of host publicationProceedings of 1st International Conference on Maintenance Engineering
EditorsJyoti Sinha
Place of PublicationUK
Publication statusPublished - 1 Aug 2016


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