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RESEARCH PAPER
Statistical Insights: Analyzing Shock Models, Reliability Operations and Testing Exponentiality for NBRUmgf Class of Life Distributions
 
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1
Department of Statistics and Operation Research, Faculty of Science, King Saud University, Saudi Arabia
 
2
Department of Mathematics, College of Science for (girls), Al-Azhar University, Egypt
 
3
Department of Computing, University of Eastern Finland, Finland
 
4
Department of Basic Sciences, Thebes Higher Institute for Engineering, Thebes Academy,, Egypt
 
 
Submission date: 2023-11-28
 
 
Final revision date: 2024-01-08
 
 
Acceptance date: 2024-02-16
 
 
Online publication date: 2024-02-25
 
 
Publication date: 2024-02-25
 
 
Corresponding author
alaa Gadallah A. M. Gadallah   

Department of Basic Sciences, Thebes Higher Institute for Engineering, Thebes Academy,, Egypt
 
 
Eksploatacja i Niezawodność – Maintenance and Reliability 2024;26(2):184185
 
HIGHLIGHTS
  • Testing exponentiality Classes of life distributions, Reliability operations
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TOPICS
ABSTRACT
This study deals with a novel category of life distributions called the new better than renewal used in moment generating function (NBRUmgf) class. It delves into the connections between this form of aging and established aging categories, along with its relevance in a shock model. Additionally, it explores how this aging concept remains consistent through certain reliability operations which is consider a very important tool in reliability engineering. The research computes Pitman's asymptotic efficiencies for this testing procedure, comparing them with alternative methods. Furthermore, the study furnishes a comprehensive table of percentiles for the test statistic associated with this proposed method. Furthermore, in order to showcase the relevance of the study's conclusions, we utilize distinct real-world datasets, which illustrate the effectiveness of our test across various types of real data.
ACKNOWLEDGEMENTS
This study was funded by Researchers Supporting Project number (RSP 202 4R488 ), King Saud University, Riyadh, Saudi
 
CITATIONS (1):
1.
Reliability Analysis for Unknown Age Class of Lifetime Distribution with Real Applications in Medical Science
Mahmoud E. Bakr, Oluwafemi Samson Balogun, Asmaa A. El-Toony, Alaa. M. Gadallah
Symmetry
 
eISSN:2956-3860
ISSN:1507-2711
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