Fuzzy Systems and its Applications

Fuzzy Systems and its Applications

$\bar{X}$ and $R$ control charts for fuzzy quality

Document Type : Original Article

Authors
Fateme Ghaderi
َAbbas Parchami
Hamideh Iranmanesh
Vahid Amirzadeh
Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
10.22034/jfsa.2025.506576.1260
Abstract
Control charts are important tools for statistical process control and play an important role in promoting and improving process quality. Recently, the design of control charts based on flexible triangular fuzzy quality has been proposed instead of using interval-value quality. In this paper, the latest parametric and nonparametric approaches for designing $\bar{X}$ and $R$ control charts based on triangular fuzzy quality are reviewed. All approaches for designing $\bar{X}$ and $R$ control charts are based on triangular fuzzy quality and do not require any initial assumptions about the distribution of quality characteristics, in other words, decision-making is based on the fuzzy quality membership function, which is more flexible than conventional/non-fuzzy quality. In order to better understand the proposed approaches, a case study based on real data from the automotive industry is presented. Also, the performance of these approaches is compared with each other using simulation.
Keywords
Quality control chart
Triangular fuzzy quality
Kernel estimation
Moment estimation
Maximum likelihood estimation
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Fuzzy Systems and its Applications
Volume 8, Issue 1 - Serial Number 16
Open Access Statement
June 2025
Pages 39-59

  • Receive Date 14 February 2025
  • Revise Date 06 May 2025
  • Accept Date 04 June 2025