2018
DOI: 10.1108/tqm-10-2017-0118
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Fuzzy U control chart based on fuzzy rules and evaluating its performance using fuzzy OC curve

Abstract: Purpose The purpose of this paper is to apply fuzzy spectrum in order to collect the vague and imprecise data and to employ the fuzzy U control chart in variable sample size using fuzzy rules. This approach is improved and developed by providing some new rules. Design/methodology/approach The fuzzy operating characteristic (FOC) curve is applied to investigate the performance of the fuzzy U control chart. The application of FOC presents fuzzy bounds of operating characteristic (OC) curve whose width depends … Show more

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Cited by 17 publications
(10 citation statements)
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“…The traditional control chart based on the assumption that all observations should be determined cannot be applied for the process monitoring when some values are fuzzy. Several authors contributed in this area by designing a fuzzy control chart for various situations, see for example, [26][27][28][29][30][31][32][33][34]35]. More details can be seen in [36].…”
Section: Introductionmentioning
confidence: 99%
“…The traditional control chart based on the assumption that all observations should be determined cannot be applied for the process monitoring when some values are fuzzy. Several authors contributed in this area by designing a fuzzy control chart for various situations, see for example, [26][27][28][29][30][31][32][33][34]35]. More details can be seen in [36].…”
Section: Introductionmentioning
confidence: 99%
“…Hsieh Ting and Wang [7] created a fuzzy c chart through two approaches: the number of nonconformities, and an index grouping of nonconformities. Fadaei and Pooya [8] introduced a fuzzy u chart based on fuzzy rule, and evaluated its performance using an operating characteristics (OC) curve. Furthermore, Truong et al [9] developed a fuzzy u chart with a classification mechanism.…”
Section: Introductionmentioning
confidence: 99%
“…Afshari and Gildeh [16] designed a fuzzy control chart using the multiple dependent state (MDS) sampling. Fadaei and Pooya [17] proposed the fuzzy U control chart. More detail on the control charts using the fuzzy approach can be seen in references [15,18].…”
Section: Introductionmentioning
confidence: 99%