Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F22%3A10251594" target="_blank" >RIV/61989100:27360/22:10251594 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2076-3417/12/11/5410" target="_blank" >https://www.mdpi.com/2076-3417/12/11/5410</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app12115410" target="_blank" >10.3390/app12115410</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes

Popis výsledku v původním jazyce

Nonparametric control charts (NPCC) have shown great potential for monitoring processes in conditions of smart manufacturing with complex structures, various monitored characteristics and the need to process big data. Practical applications of NPCCs are very rare. The main reasons for this situation are a deficiency in software support and a lack of simple but complete instructions for their application. The introduction of such manual, which is based on the authors&apos; own simulations of performance of wide spectrum of NPCCs in conditions of different violations of data prerequisites, leading to recommendations for the selection of the most effective NPCC in various practical situations, is the main goal of this paper. Compared to other similar studies, this approach covers a wider range of control charts, and it was applied to a wider spectrum of data assumption violations. As an integral part of these analyses, an examination of various control chart performance indicators such as ARL, MRL, x(5) and x(95) was performed using simulations to select the best of them. The designed methodology was verified using real data.

Název v anglickém jazyce

Analysis and Application of Selected Control Charts Suitable for Smart Manufacturing Processes

Popis výsledku anglicky

Nonparametric control charts (NPCC) have shown great potential for monitoring processes in conditions of smart manufacturing with complex structures, various monitored characteristics and the need to process big data. Practical applications of NPCCs are very rare. The main reasons for this situation are a deficiency in software support and a lack of simple but complete instructions for their application. The introduction of such manual, which is based on the authors&apos; own simulations of performance of wide spectrum of NPCCs in conditions of different violations of data prerequisites, leading to recommendations for the selection of the most effective NPCC in various practical situations, is the main goal of this paper. Compared to other similar studies, this approach covers a wider range of control charts, and it was applied to a wider spectrum of data assumption violations. As an integral part of these analyses, an examination of various control chart performance indicators such as ARL, MRL, x(5) and x(95) was performed using simulations to select the best of them. The designed methodology was verified using real data.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20306 - Audio engineering, reliability analysis

Projekt

<a href="/cs/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: Platforma pro výzkum orientovaný na Průmysl 4.0 a robotiku v ostravské aglomeraci</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Applied Sciences

ISSN

2076-3417

e-ISSN

2076-3417

Svazek periodika

12

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

26

Strana od-do

nestrankovano

Kód UT WoS článku

000808797400001

EID výsledku v databázi Scopus

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