Parametric and nonparametric methods of statistical process control

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F16%3A86098794" target="_blank" >RIV/61989100:27360/16:86098794 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.17973/MMSJ.2016_11_2016163" target="_blank" >http://dx.doi.org/10.17973/MMSJ.2016_11_2016163</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17973/MMSJ.2016_11_2016163" target="_blank" >10.17973/MMSJ.2016_11_2016163</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Parametric and nonparametric methods of statistical process control

Popis výsledku v původním jazyce

This paper presents the limitations of classical Shewhart control charts and some possibilities of statistical process control that can be used when the basic assumptions about data have not been fulfilled. These basic assumptions that must be met include mainly a requirement on the normality of the data, the requirement for constant mean and variance, and last but not least the requirement for mutual independence of data. In practice, those assumptions about the data are not necessarily always met. The aim of this article is to introduce the problems (such as normality failure, data dependence) that can occur when applying the classic Shewhart control charts. Additional aim of this article is to describe some non-parametric control charts and concretely introduce one of the non-parametric control charts, namely Shewhart sign control chart, including a practical example from a metallurgical process. During preparation of this article accessible pieces of knowledge on the issue were compared. Comparing the parametric and nonparametric methods it was found that nonparametric methods have many advantages and for cases where some of the basic assumptions about the data are not met they are appropriate.

Název v anglickém jazyce

Parametric and nonparametric methods of statistical process control

Popis výsledku anglicky

This paper presents the limitations of classical Shewhart control charts and some possibilities of statistical process control that can be used when the basic assumptions about data have not been fulfilled. These basic assumptions that must be met include mainly a requirement on the normality of the data, the requirement for constant mean and variance, and last but not least the requirement for mutual independence of data. In practice, those assumptions about the data are not necessarily always met. The aim of this article is to introduce the problems (such as normality failure, data dependence) that can occur when applying the classic Shewhart control charts. Additional aim of this article is to describe some non-parametric control charts and concretely introduce one of the non-parametric control charts, namely Shewhart sign control chart, including a practical example from a metallurgical process. During preparation of this article accessible pieces of knowledge on the issue were compared. Comparing the parametric and nonparametric methods it was found that nonparametric methods have many advantages and for cases where some of the basic assumptions about the data are not met they are appropriate.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JS - Řízení spolehlivosti a kvality, zkušebnictví

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MM Science Journal

ISSN

1803-1269

e-ISSN

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Svazek periodika

Neuveden

Číslo periodika v rámci svazku

Listopad 2016

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

1465-1472

Kód UT WoS článku

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EID výsledku v databázi Scopus

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