Abstract
The purpose of this research is to develop a maximum likelihood estimator (MLE) for lifetime performance index CL 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 CL 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.
Highlights
Process capability analysis is an efficient method for determining a production process’s performance and prospective capabilities
Process capability analysis aids in the following ways: continuously monitoring process quality using process capability indices (PCIs) to ensure produced goods adhere to requirements, giving information on product development to manufacturers and specialists, and establishing a foundation for lowering item failures. e PCIs are classified into three categories: the first is used to quantify the target-the-better quality feature, the second is used to quantify the larger-the-better quality characteristic, and the third is used to quantify the smallerthe-better quality characteristic
A procedure is proposed in the presented study of the test, which is based on a one-sided confidence interval under Rayleigh-Half Normal distribution (RHN) distribution and increasingly type-II right-censored sample. e following two examples will be applied to demonstrate the use of these hypothesis testing procedures
Summary
Process capability analysis is an efficient method for determining a production process’s performance and prospective capabilities. Process capability analysis aids in the following ways: continuously monitoring process quality using PCI to ensure produced goods adhere to requirements, giving information on product development to manufacturers and specialists, and establishing a foundation for lowering item failures. A high sample size is required in practice to evaluate the product’s effectiveness under nonnormal distributions, and this study used a large sample size and an increasing proportion of type-II right-censored samples. Using a large sample size and an increasing proportion of type-II right-censored samples, this study created a novel method for assessing a product’s performance improvement when the distribution is nonnormal. We use confidence intervals to construct a unique hypothesis testing approach for evaluating items’ lifetime performance. E novel hypothesis testing approach may be used to evaluate the quality performance of items with nonnormal distribution using large sample size and an increased role of type-II right-censored items. Vendors can leverage the unique hypothesis testing approach to enhance the capability of their processes
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