Estimation Study of Multicomponent Stress-Strength Reliability Using Advanced Sampling Approach

Abstract

In this study, we analyze a multicomponent system with v independent and identical strength components X1,…, Xv and each of these components is exposed to a common random stress Y. The system is considered to be operating only if at least u out of v (1 u  v) strength variables exceed the random stress. The estimate of the system reliability is investigated, assuming the strength and stress random variables follow the exponentiated exponential distribution having different shape parameters. The maximum likelihood estimator for the system reliability is derived from ranked set sampling (RSS), neoteric RSS (NRSS), and median RSS (MRSS). Some accuracy measurements, such as mean squared errors and efficiencies, are used to examine the behaviour of various estimates. Simulation studies demonstrate that the NRSS scheme's reliability estimates are chosen above those of the others under the RSS and MRSS schemes in the majority of situations. Theoretical research is explained through real data analysis.

Keywords

• Neoteric ranked set sampling
• Median ranked set sampling
• Multicomponent model
• Maximum likelihood method

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