Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart

Quality control, particularly through the use of control charts, has become essential in industry to ensure that processes free from special causes of variability. Many processes are subject to instrument uncertainty, human subjectivity, and operator hesitation at the time of measurement. In such ca...

Full description

Saved in:
Bibliographic Details
Main Authors: Amanda Dos Santos Mendes, Tulio S. Almeida, Marcela A. G. Machado, Paloma Maria Silva Rocha Rizol
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10994758/
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849736924268331008
author Amanda Dos Santos Mendes
Tulio S. Almeida
Marcela A. G. Machado
Paloma Maria Silva Rocha Rizol
author_facet Amanda Dos Santos Mendes
Tulio S. Almeida
Marcela A. G. Machado
Paloma Maria Silva Rocha Rizol
author_sort Amanda Dos Santos Mendes
collection DOAJ
description Quality control, particularly through the use of control charts, has become essential in industry to ensure that processes free from special causes of variability. Many processes are subject to instrument uncertainty, human subjectivity, and operator hesitation at the time of measurement. In such cases, traditional control charts may not be as viable, so intuitionistic fuzzy control charts should be used, as they are able to represent the uncertainty and hesitation of the process. This study evaluates the performance of the <inline-formula> <tex-math notation="LaTeX">$\bar {X}$ </tex-math></inline-formula>-R intuitionistic fuzzy control charts was measured by the Average Run Length (ARL), Standard Deviation Run Length (SDRL) and Run Length Percentiles. Additionally, computational interface was developed in the R programming language, using the Shiny package, capable of facilitating the user&#x2019;s experience in combining the concepts presented. Different combinations of the <inline-formula> <tex-math notation="LaTeX">$c_{L}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$c_{R}$ </tex-math></inline-formula> coefficients in the IF-WABL (Intuitionistic Fuzzy - Weigthed Average Based on Level) defuzzification method were considered, resulting in 17 scenarios. As these coefficients can be adjusted by the user, it is recommended that scenarios 4 to 7 be used for the general performance of the intuitionistic fuzzy <inline-formula> <tex-math notation="LaTeX">$\bar {X}$ </tex-math></inline-formula>-R control chart, as they lead to reductions in ARL and SDRL values and percentiles close to those of the traditional control chart. A maximum reduction of 5.88% in ARL and 5.45% in SDRL was observed, both in scenario 4. This work showed that intuitionistic fuzzy control charts are efficient at detecting special causes, and that the computer interface developed is capable of performing the proposed functions.
format Article
id doaj-art-cf8e8c23e5fe4aa59a466db0416f5ec4
institution DOAJ
issn 2169-3536
language English
publishDate 2025-01-01
publisher IEEE
record_format Article
series IEEE Access
spelling doaj-art-cf8e8c23e5fe4aa59a466db0416f5ec42025-08-20T03:07:06ZengIEEEIEEE Access2169-35362025-01-0113832858329610.1109/ACCESS.2025.356877410994758Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control ChartAmanda Dos Santos Mendes0https://orcid.org/0000-0002-8995-2977Tulio S. Almeida1https://orcid.org/0009-0006-9295-9826Marcela A. G. Machado2https://orcid.org/0000-0002-0621-6932Paloma Maria Silva Rocha Rizol3https://orcid.org/0000-0001-5246-4438Department of Administration and Public Administration, Institute of Humanities and Social Sciences, Federal Fluminense University, Volta Redonda, Rio de Janeiro, BrazilDepartment of Administration and Public Administration, Institute of Humanities and Social Sciences, Federal Fluminense University, Volta Redonda, Rio de Janeiro, BrazilDepartment of Production Engineering, Faculty of Engineering and Science, S&#x00E3;o Paulo State University &#x201C;J&#x00FA;lio de Mesquita Filho,&#x201D; Guaratinguet&#x00E1;, S&#x00E3;o Paulo, BrazilElectrical Engineering Department, Faculty of Engineering and Science, S&#x00E3;o Paulo State University &#x201C;J&#x00FA;lio de Mesquita Filho,&#x201D; Guaratinguet&#x00E1;, S&#x00E3;o Paulo, BrazilQuality control, particularly through the use of control charts, has become essential in industry to ensure that processes free from special causes of variability. Many processes are subject to instrument uncertainty, human subjectivity, and operator hesitation at the time of measurement. In such cases, traditional control charts may not be as viable, so intuitionistic fuzzy control charts should be used, as they are able to represent the uncertainty and hesitation of the process. This study evaluates the performance of the <inline-formula> <tex-math notation="LaTeX">$\bar {X}$ </tex-math></inline-formula>-R intuitionistic fuzzy control charts was measured by the Average Run Length (ARL), Standard Deviation Run Length (SDRL) and Run Length Percentiles. Additionally, computational interface was developed in the R programming language, using the Shiny package, capable of facilitating the user&#x2019;s experience in combining the concepts presented. Different combinations of the <inline-formula> <tex-math notation="LaTeX">$c_{L}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$c_{R}$ </tex-math></inline-formula> coefficients in the IF-WABL (Intuitionistic Fuzzy - Weigthed Average Based on Level) defuzzification method were considered, resulting in 17 scenarios. As these coefficients can be adjusted by the user, it is recommended that scenarios 4 to 7 be used for the general performance of the intuitionistic fuzzy <inline-formula> <tex-math notation="LaTeX">$\bar {X}$ </tex-math></inline-formula>-R control chart, as they lead to reductions in ARL and SDRL values and percentiles close to those of the traditional control chart. A maximum reduction of 5.88% in ARL and 5.45% in SDRL was observed, both in scenario 4. This work showed that intuitionistic fuzzy control charts are efficient at detecting special causes, and that the computer interface developed is capable of performing the proposed functions.https://ieeexplore.ieee.org/document/10994758/Computational interfacecontrol charthesitationintuitionistic fuzzy logicperformanceuncertainty
spellingShingle Amanda Dos Santos Mendes
Tulio S. Almeida
Marcela A. G. Machado
Paloma Maria Silva Rocha Rizol
Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart
IEEE Access
Computational interface
control chart
hesitation
intuitionistic fuzzy logic
performance
uncertainty
title Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart
title_full Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart
title_fullStr Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart
title_full_unstemmed Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart
title_short Performance Analysis and Computational Interface for <italic>X &#x2013; R</italic> Intuitionistic Fuzzy Control Chart
title_sort performance analysis and computational interface for italic x x2013 r italic intuitionistic fuzzy control chart
topic Computational interface
control chart
hesitation
intuitionistic fuzzy logic
performance
uncertainty
url https://ieeexplore.ieee.org/document/10994758/
work_keys_str_mv AT amandadossantosmendes performanceanalysisandcomputationalinterfaceforitalicxx2013ritalicintuitionisticfuzzycontrolchart
AT tuliosalmeida performanceanalysisandcomputationalinterfaceforitalicxx2013ritalicintuitionisticfuzzycontrolchart
AT marcelaagmachado performanceanalysisandcomputationalinterfaceforitalicxx2013ritalicintuitionisticfuzzycontrolchart
AT palomamariasilvarocharizol performanceanalysisandcomputationalinterfaceforitalicxx2013ritalicintuitionisticfuzzycontrolchart