Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution

The proposed sampling plan in this article is referred to as multiple dependent state (MDS) sampling plans, for rejecting a lot based on properties of the current and preceding lot sampled. The median life of the product for the proposed sampling plan is assured based on a time-truncated life test,...

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Autores principales:	Srinivasa Rao Gadde, Arnold K. Fulment, Josephat K. Peter
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/c3b359fdc3f24e55a507202e4d4d982b
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spelling	oai:doaj.org-article:c3b359fdc3f24e55a507202e4d4d982b2021-11-08T02:35:41ZDesign of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution1099-052610.1155/2021/2795078https://doaj.org/article/c3b359fdc3f24e55a507202e4d4d982b2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2795078https://doaj.org/toc/1099-0526The proposed sampling plan in this article is referred to as multiple dependent state (MDS) sampling plans, for rejecting a lot based on properties of the current and preceding lot sampled. The median life of the product for the proposed sampling plan is assured based on a time-truncated life test, when a lifetime of the product follows exponentiated Weibull distribution (EWD). For the proposed plan, optimal parameters such as the number of preceding lots required for deciding whether to accept or reject the current lot, sample size, and rejection and acceptance numbers are obtained by the approach of two points on the operating characteristic curve (OC curve). Tables are constructed for various combinations of consumer and producer’s risks for various shape parameters. The proposed MDS sampling plan for EWD is demonstrated using the coronavirus (COVID-19) outbreak in China. The performance of the proposed sampling plan is compared with the existing single-sampling plan (SSP) when the quality of the product follows EWD.Srinivasa Rao GaddeArnold K. FulmentJosephat K. PeterHindawi-WileyarticleElectronic computers. Computer scienceQA75.5-76.95ENComplexity, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electronic computers. Computer science QA75.5-76.95
spellingShingle	Electronic computers. Computer science QA75.5-76.95 Srinivasa Rao Gadde Arnold K. Fulment Josephat K. Peter Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
description	The proposed sampling plan in this article is referred to as multiple dependent state (MDS) sampling plans, for rejecting a lot based on properties of the current and preceding lot sampled. The median life of the product for the proposed sampling plan is assured based on a time-truncated life test, when a lifetime of the product follows exponentiated Weibull distribution (EWD). For the proposed plan, optimal parameters such as the number of preceding lots required for deciding whether to accept or reject the current lot, sample size, and rejection and acceptance numbers are obtained by the approach of two points on the operating characteristic curve (OC curve). Tables are constructed for various combinations of consumer and producer’s risks for various shape parameters. The proposed MDS sampling plan for EWD is demonstrated using the coronavirus (COVID-19) outbreak in China. The performance of the proposed sampling plan is compared with the existing single-sampling plan (SSP) when the quality of the product follows EWD.
format	article
author	Srinivasa Rao Gadde Arnold K. Fulment Josephat K. Peter
author_facet	Srinivasa Rao Gadde Arnold K. Fulment Josephat K. Peter
author_sort	Srinivasa Rao Gadde
title	Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
title_short	Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
title_full	Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
title_fullStr	Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
title_full_unstemmed	Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
title_sort	design of multiple dependent state sampling plan application for covid-19 data using exponentiated weibull distribution
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/c3b359fdc3f24e55a507202e4d4d982b
work_keys_str_mv	AT srinivasaraogadde designofmultipledependentstatesamplingplanapplicationforcovid19datausingexponentiatedweibulldistribution AT arnoldkfulment designofmultipledependentstatesamplingplanapplicationforcovid19datausingexponentiatedweibulldistribution AT josephatkpeter designofmultipledependentstatesamplingplanapplicationforcovid19datausingexponentiatedweibulldistribution
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Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution

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