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Article type: Research Article
Authors: Khan, Zahida | Gulistan, Muhammada | Hashim, Rabiyaa | Yaqoob, Naveedb | Chammam, Wathekc; *
Affiliations: [a] Department of Mathematics and Statisitcs, Hazara University Mansehra, Pakistan | [b] Department of Mathematics and Statistics, Riphah International University, Islamabad, Pakistan | [c] Department of Mathematics, College of Science Al-Zulfi, Majmaah University, Majmaah, Saudi Arabia
Correspondence: [*] Corresponding author. Wathek Chammam, Department of Mathematics and Statisitcs, Hazara University Mansehra, Pakistan. E-mail: [email protected].
Abstract: The Shewart S-control chart is commonly used as one of the statistical tools for monitoring the process variability. The existing design of S-control is based on the assumption that inspected quality of the observed process is, an exact and clearly specified quantitative quantity. If however, measured data involve some vague and imprecise observations, the conventional approach of the S-control, cannot be practiced. Designing of a generalized neutrosophic S-control chart which could support the indeterminate values in the processing data is originally developed in this article. The associated properties of proposed design under neutrosophic environment have been established in this study. The proposed chart represents a general design of the existence structure of the S-chart. Using neutrosophic average run length (ARLn) as a performance measure, a comparative study of the proposed chart with the conventional approach of S-control under vague parameter values is evaluated. Findings both from analytical and simulation studies indicate that proposed design of S-control leads to efficient and more flexible approach over the traditional S-control. A real data example has been provided for demonstrating the implementation procedure of the proposed design.
Keywords: Quality control, fuzzy charts, neutrosophic measures, S-control chart
DOI: 10.3233/JIFS-191439
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4743-4751, 2020
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