BackgroundA review of the performance of power plants reveals that boiler and turbine auxiliaries are responsible for approximatley 9.0 and 3.0 per cent of power plant unavailability respectively. Availability of the power plant is enhanced if the failure of auxiliaries and their downtime is minimized. A systematic maintenance programme for coal-based power plants auxiliaries ensures failure-free operation in most cases.Reliability of a piece of equipment enables us to decide on the quality and frequency of maintenace that will be required. Many tools are available for improvements in efficieny and long-term costs of maintenance. Reliabilitycentred maintenance (RCM) is a recent technique [1]. It has proved to be an effective technique in development of preventive maintenance programmes in the areas of aviation, defence and nuclear power plants [2].RCM has been developed with the emphasis on safety and no "tool" exists for deciding optimal maintenance intervals[3]. To date, the quantitative approach to RCM has taken a back seat to the qualitative approach[4]. This is because of the unavailability of plant-specific historical data and appropriate statistical methods to interpret the data.This paper presents a mainenance methodology for coal-based power plant auxiliaries based on the RCM approach. The emphasis of the methodology is on maximum availability of the equipment at an optimum maintenance cost. MethodologyAs shown in Figure 1, the essential activities of the developed methodology are: selection of critical auxiliaries; data collection; selection of significant maintenance items; the maintenance decision process; and selection of maintenance periodicity. Selection of critical auxiliariesThe effect of failure of an auxiliary may affect the power generation and in some cases results in higher maintenance costs. Analysis of the operation and maintenance data reveals the criticality of an auxiliary in terms of generation loss, maintenance cost, availability and forced outage of the plant for which it is responsible. One such analysis is shown in Table I, which shows the auxiliary equipment and the effects of its failure in terms of percentage of forced outage
In this paper, the classical semi-Markov model in discrete time is extended to semi-Markov model with fuzzy transitions and fuzzy states. The definition and the basic equation for interval transitions of a semi-Markov model with fuzzy transitions are provided. Also the interval transitions for the above model with fuzzy states is provided for the homogeneous case and we apply this fuzzy technique to web based application and show this model gives the accessibility assessment that are based on uncertainties/imprecise. The definitions and results for the fuzzy model are provided by means of the fuzzy probabilities and are modeled by triangular fuzzy numbers.
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