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June 20, 2026Journal of Applied MathematicsOpen Access

Employing the Inverse Weibull Failure Time Model to Estimate Some of the Reliability Metrics of k‐Out‐of‐n Systems

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Authors

FHF. HameedHAHussein K. Asker

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Overview

Randomized trial evaluates system reliability and failure metrics in k-out-of-n systems, suggesting enhanced estimation methods.

Key Points

  • This research aims to estimate the mean time to system failure and reliability function of k-out-of-n systems using the inverse Weibull distribution.
  • Developed estimation procedures using maximum likelihood estimation (MLE) and Bayesian MCMC approach.
  • Established confidence intervals for reliability function utilizing the Fisher information matrix.
  • Conducted Monte Carlo simulations to assess the performance of different estimation techniques.
  • Bayesian MCMC method yielded the lowest mean squared error (MSE).
  • For k = 3 components, MLE method outperformed least squares (LS) method.
  • General superiority of LS over MLE observed only in higher redundancy scenarios (k > 3).

Cite This Study

Hameed et al. (2026) studied this question.

synapsesocial.com/papers/6a36300ddb0793dc1a5375dfhttps://doi.org/10.1155/jama/2802965
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