Ordering Results between Two Extreme Order Statistics with Heterogeneous Linear Failure Rate Distributed Components
By: CM Revathi, Rajesh Moharana, Raju Bhakta
Potential Business Impact:
Helps engineers build stronger, more reliable machines.
Stochastic comparisons of series and parallel systems are important in many areas of engineering, operations research and reliability analysis. These comparisons allow for the evaluation of the performance and reliability of systems under different conditions, and can inform decisions related to system design, probabilities of failure, maintenance and operation. In this paper, we investigate the stochastic comparisons of the series and parallel systems under the assumption that the component lifetimes have independent heterogeneous linear failure rate distributions. The comparisons are established based on the various stochastic orders including magnitude, transform and variability orders. Several numerical examples and counterexamples are constructed to illustrate the theoretical outcomes of this paper. Finally, we summarized our findings with a real-world application and possible future scopes of the present study.
Similar Papers
Stochastic comparisons of finite mixtures with general exponentiated location-scale distributed components
Statistics Theory
Helps understand how bad data affects predictions.
Simultaneous Nonparametric Confidence Bands for Load-Sharing Systems
Methodology
Makes machines last longer by predicting failures.
Stochastic dominance for linear combinations of infinite-mean risks
Probability
Compares random numbers to predict risks better.