Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution
A multicomponent system of k components with independent and identically distributed random strengths, with each component undergoing random stress, is in working condition if and only if at least s out of k strengths exceed the subjected stress. Reliability is measured while strength and stress are...
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doaj-4c65c127228243ec8a4ad00eb3c1b0532020-11-24T21:50:05ZengMDPI AGAlgorithms1999-48932019-11-01121224610.3390/a12120246a12120246Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential DistributionG. Srinivasa Rao0Fiaz Ahmad Bhatti1Muhammad Aslam2Mohammed Albassam3Department of Statistics, School of Mathematical Sciences, CNMS, The University of Dodoma, P.O. Box: 259, 41000 Dodoma, TanzaniaNational College of Business Administration and Economics, 54000 Lahore, PakistanDepartment of Statistics, Faculty of Science, King Abdulaziz University, 21551 Jeddah, Saudi ArabiaDepartment of Statistics, Faculty of Science, King Abdulaziz University, 21551 Jeddah, Saudi ArabiaA multicomponent system of k components with independent and identically distributed random strengths, with each component undergoing random stress, is in working condition if and only if at least s out of k strengths exceed the subjected stress. Reliability is measured while strength and stress are obtained through a process following an exponentiated moment-based exponential distribution with different shape parameters. Reliability is gauged from the samples using maximum likelihood (ML) on the computed distributions of strength and stress. Asymptotic estimates of reliability are compared using Monte Carlo simulation. Application to forest data and to breaking strengths of jute fiber shows the usefulness of the model.https://www.mdpi.com/1999-4893/12/12/246exponentiated moment-based exponential distributionreliabilitystressstrengthmaximum likelihoodmonte carlo simulation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. Srinivasa Rao Fiaz Ahmad Bhatti Muhammad Aslam Mohammed Albassam |
spellingShingle |
G. Srinivasa Rao Fiaz Ahmad Bhatti Muhammad Aslam Mohammed Albassam Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution Algorithms exponentiated moment-based exponential distribution reliability stress strength maximum likelihood monte carlo simulation |
author_facet |
G. Srinivasa Rao Fiaz Ahmad Bhatti Muhammad Aslam Mohammed Albassam |
author_sort |
G. Srinivasa Rao |
title |
Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution |
title_short |
Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution |
title_full |
Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution |
title_fullStr |
Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution |
title_full_unstemmed |
Estimation of Reliability in a Multicomponent Stress–Strength System for the Exponentiated Moment-Based Exponential Distribution |
title_sort |
estimation of reliability in a multicomponent stress–strength system for the exponentiated moment-based exponential distribution |
publisher |
MDPI AG |
series |
Algorithms |
issn |
1999-4893 |
publishDate |
2019-11-01 |
description |
A multicomponent system of k components with independent and identically distributed random strengths, with each component undergoing random stress, is in working condition if and only if at least s out of k strengths exceed the subjected stress. Reliability is measured while strength and stress are obtained through a process following an exponentiated moment-based exponential distribution with different shape parameters. Reliability is gauged from the samples using maximum likelihood (ML) on the computed distributions of strength and stress. Asymptotic estimates of reliability are compared using Monte Carlo simulation. Application to forest data and to breaking strengths of jute fiber shows the usefulness of the model. |
topic |
exponentiated moment-based exponential distribution reliability stress strength maximum likelihood monte carlo simulation |
url |
https://www.mdpi.com/1999-4893/12/12/246 |
work_keys_str_mv |
AT gsrinivasarao estimationofreliabilityinamulticomponentstressstrengthsystemfortheexponentiatedmomentbasedexponentialdistribution AT fiazahmadbhatti estimationofreliabilityinamulticomponentstressstrengthsystemfortheexponentiatedmomentbasedexponentialdistribution AT muhammadaslam estimationofreliabilityinamulticomponentstressstrengthsystemfortheexponentiatedmomentbasedexponentialdistribution AT mohammedalbassam estimationofreliabilityinamulticomponentstressstrengthsystemfortheexponentiatedmomentbasedexponentialdistribution |
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