Decision‐Making for the Lifetime Performance Index | Zendy

Basim S. O. Alsaedi | Zendy; M. M. Abd ElRaouf | Zendy; E. H. Hafez | Zendy; Zahra Almaspoor | Zendy; Osama Abdulaziz Alamri | Zendy; Kamel Atallah Alanazi | Zendy; Saima K. Khosa | Zendy

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Decision‐Making for the Lifetime Performance Index

Author(s) -

Basim S. O. Alsaedi,

M. M. Abd ElRaouf,

E. H. Hafez,

Zahra Almaspoor,

Osama Abdulaziz Alamri,

Kamel Atallah Alanazi,

Saima K. Khosa

Publication year - 2021

Publication title -

computational intelligence and neuroscience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.605

H-Index - 52

eISSN - 1687-5273

pISSN - 1687-5265

DOI - 10.1155/2021/3005067

Subject(s) - index (typography) , computer science , world wide web

The purpose of this research is to develop a maximum likelihood estimator (MLE) for lifetime performance index C L for the parameter of mixture Rayleigh-Half Normal distribution (RHN) under progressively type-II right-censored samples under the constraint of knowing the lower specification limit ( L ). Additionally, we suggest an asymptotic normal distribution for the MLE for C L in order to construct a mechanism for evaluating products' lifespan efficiency. We have specified all the steps to carry out the test. Additionally, not only does hypothesis testing successfully assess the lifetime performance of items, but it also functions as a supplier selection criterion for the consumer. Finally, we have added two real data examples as illustration examples. These two applications are provided to demonstrate how the results can be applied.

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