Estimate Stress-Strength Reliability Model Using Rayleigh and Half-Normal Distribution

• Published in: Computational intelligence and neuroscience Vol. 2021; no. 1; p. 7653581
• Main Authors: Alamri, Osama Abdulaziz, El-Raouf, M. M. Abd, Ismail, Eman Ahmed, Almaspoor, Zahra, Alsaedi, Basim S. O., Khosa, Saima Khan, Yusuf, M.
• Format: Journal Article
• Language: English
• Published: New York Hindawi 2021; John Wiley & Sons, Inc
• Subjects: Component reliability; Maximum likelihood estimation; Normal distribution; Parameter estimation; Probability distribution functions; Random variables; Rayleigh distribution; Reliability analysis; Statistical analysis; Stress concentration
• ISSN: 1687-5265; 1687-5273; 1687-5273
• DOI: 10.1155/2021/7653581

In the field of life testing, it is very important to study the reliability of any component under testing. One of the most important subjects is the “stress-strength reliability” term which always refers to the quantity P X>Y in any statistical literature. It resamples a system with random strength (X) that is subjected to a random strength (Y) such that a system fails in case the stress exceeds the strength. In this study, we consider stress-strength reliability where the strength (X) follows Rayleigh-half-normal distribution and stress (Y1,Y2,Y3, and Y4) follows Rayleigh-half-normal distribution, exponential distribution, Rayleigh distribution, and half-normal distribution, respectively. This effort comprises determining the general formulations of the reliabilities of a system. Also, the maximum likelihood estimation approach and method of moment (MOM) will be utilized to estimate the parameters. Finally, reliability has been attained utilizing various values of stress and strength parameters.