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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 7042453, 11 pages
Research Article

Parameter Estimation of a Reliability Model of Demand-Caused and Standby-Related Failures of Safety Components Exposed to Degradation by Demand Stress and Ageing That Undergo Imperfect Maintenance

1Department of Chemical and Nuclear Engineering, Universitat Politècnica de València, Valencia, Spain
2MEDASEGI, Valencia, Spain
3Department of Statistics and Operational Research, Universitat Politècnica de València, Valencia, Spain
4Department of Mathematics, Universidad de Alicante, Alicante, Spain

Correspondence should be addressed to S. Martorell

Received 7 August 2017; Accepted 5 November 2017; Published 18 December 2017

Academic Editor: Giovanni Falsone

Copyright © 2017 S. Martorell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One can find many reliability, availability, and maintainability (RAM) models proposed in the literature. However, such models become more complex day after day, as there is an attempt to capture equipment performance in a more realistic way, such as, explicitly addressing the effect of component ageing and degradation, surveillance activities, and corrective and preventive maintenance policies. Then, there is a need to fit the best model to real data by estimating the model parameters using an appropriate tool. This problem is not easy to solve in some cases since the number of parameters is large and the available data is scarce. This paper considers two main failure models commonly adopted to represent the probability of failure on demand (PFD) of safety equipment: by demand-caused and standby-related failures. It proposes a maximum likelihood estimation (MLE) approach for parameter estimation of a reliability model of demand-caused and standby-related failures of safety components exposed to degradation by demand stress and ageing that undergo imperfect maintenance. The case study considers real failure, test, and maintenance data for a typical motor-operated valve in a nuclear power plant. The results of the parameters estimation and the adoption of the best model are discussed.