Enhancing reliability of thermal power plant by implementing RCM policy and developing reliability prediction model: a case study

Navneet Singh Bhangu (), G. L. Pahuja () and Rupinder Singh ()
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Navneet Singh Bhangu: N.I.T., Kurukshetra
G. L. Pahuja: N.I.T., Kurukshetra
Rupinder Singh: G.N.D.E.C., Ludhiana

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 106, 1923-1936

Abstract: Abstract This paper presents the implementation of RCM policy in thermal power plant as a case study for strategic planning of maintenance schedules to resolve the problem of forced outages, long downtimes and poor reliability. Development of a model has also been done using ANN technique to predict the enhanced value of reliability. RCM has been proved to be beneficial in various industrial sectors but power generation sector lacks in exploring its use especially in the region where case study has been performed. RCM is a seven step criteria which has been grouped into three major structured steps—define, analyze and act. Justifying the define step, outage data acquisition has been done and Pareto analysis has been performed to prioritize the few vital components prone to failures. This is unique innovative aspect of this case study. Reliability evaluation and failure mode and effects analysis has been performed to validate the analysis step. Poor reliability of the units indicates urgent need of appropriate maintenance policy. As per the act step, structural decision logics have been designed for the components using RCM++ software. The benefit of application of RCM in terms of enhanced reliability has been shown by developing an ANN model. The verification of this model has been done using F-test, the results of which reveal that the differences in variance of actual and ANN outputs are not significant. The predicted values of reliability have shown vast improvement.

Keywords: RCM; Thermal power plant; MTBF; Reliability; Pareto analysis; FMEA; Condenser; ANN (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-016-0542-z

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