Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data

This article introduces a generalized version of the multiple dependent state sampling plan based on the measurement data, that is, when the quality characteristic is measured in a numerical scale. The conditions of application and the operating procedures of the proposed plan are discussed sequenti...

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Main Authors: Ritwik Bhattacharya, Muhammad Aslam
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9186020/
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spelling doaj-955e506c3c7547a784aaf7adae3d4f6d2021-03-30T03:22:04ZengIEEEIEEE Access2169-35362020-01-01816277516278410.1109/ACCESS.2020.30215049186020Generalized Multiple Dependent State Sampling Plans in Presence of Measurement DataRitwik Bhattacharya0https://orcid.org/0000-0003-4732-7994Muhammad Aslam1https://orcid.org/0000-0003-0644-1950School of Engineering and Science, Tecnológico de Monterrey, Monterrey, MexicoDepartment of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi ArabiaThis article introduces a generalized version of the multiple dependent state sampling plan based on the measurement data, that is, when the quality characteristic is measured in a numerical scale. The conditions of application and the operating procedures of the proposed plan are discussed sequentially. A few important performance measures, such as operating characteristic curve, average total inspection and average sample number, are developed. The advantage of the proposed plan over the multiple dependent state sampling and single sampling plan is demonstrated through numerical example. Finally, one real-life data set is analyzed to illustrate the application of the proposed sampling plan.https://ieeexplore.ieee.org/document/9186020/Consumer’s riskhybrid censoringlife-testingproducer’s riskquality controlreliability sampling plan
collection DOAJ
language English
format Article
sources DOAJ
author Ritwik Bhattacharya
Muhammad Aslam
spellingShingle Ritwik Bhattacharya
Muhammad Aslam
Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data
IEEE Access
Consumer’s risk
hybrid censoring
life-testing
producer’s risk
quality control
reliability sampling plan
author_facet Ritwik Bhattacharya
Muhammad Aslam
author_sort Ritwik Bhattacharya
title Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data
title_short Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data
title_full Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data
title_fullStr Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data
title_full_unstemmed Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data
title_sort generalized multiple dependent state sampling plans in presence of measurement data
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description This article introduces a generalized version of the multiple dependent state sampling plan based on the measurement data, that is, when the quality characteristic is measured in a numerical scale. The conditions of application and the operating procedures of the proposed plan are discussed sequentially. A few important performance measures, such as operating characteristic curve, average total inspection and average sample number, are developed. The advantage of the proposed plan over the multiple dependent state sampling and single sampling plan is demonstrated through numerical example. Finally, one real-life data set is analyzed to illustrate the application of the proposed sampling plan.
topic Consumer’s risk
hybrid censoring
life-testing
producer’s risk
quality control
reliability sampling plan
url https://ieeexplore.ieee.org/document/9186020/
work_keys_str_mv AT ritwikbhattacharya generalizedmultipledependentstatesamplingplansinpresenceofmeasurementdata
AT muhammadaslam generalizedmultipledependentstatesamplingplansinpresenceofmeasurementdata
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