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Effects of measurement errors on semicircle control chart.

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Titel: Effects of measurement errors on semicircle control chart.
Autoren: Haizhen, Zhou1,2 (AUTHOR), Khoo, Michael B. C.1 (AUTHOR) mkbc@usm.my, Babatunde, Oluwagbenga Tobi3 (AUTHOR), Saha, Sajal4 (AUTHOR)
Quelle: Quality Engineering. 2025, Vol. 37 Issue 3, p387-402. 16p.
Schlagwörter: *QUALITY control charts, MEASUREMENT errors, SIGNAL detection, STATISTICAL measurement, RESEARCH evaluation, ERRORS-in-variables models
Abstract: In recent years, the impacts of measurement errors on the performance of various control charts have been well evaluated. The existing semicircle (SC) control chart has been proposed based on the assumption that there are no measurement errors. In this paper, we investigated the effect of measurement errors using the linear covariate error model with constant variance and linearly increasing variance on the performance of the SC chart. We used simulation to evaluate the performance of the SC chart, in terms of average run length (ARL), standard deviation of the run length (SDRL), median run length (MDRL), and expected average run length (EARL) metrics. The results obtained indicate that measurement errors negatively affect the performance of the SC chart and taking multiple measurements on each item or/and increasing the slope coefficient of the covariate error model can effectively reduce the adverse impact of errors on the chart's performance. Finally, an illustrative real life example is provided to demonstrate the undesired impact of measurement errors on the detection capability of the SC chart. [ABSTRACT FROM AUTHOR]
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Datenbank: Business Source Index
Beschreibung
Abstract:In recent years, the impacts of measurement errors on the performance of various control charts have been well evaluated. The existing semicircle (SC) control chart has been proposed based on the assumption that there are no measurement errors. In this paper, we investigated the effect of measurement errors using the linear covariate error model with constant variance and linearly increasing variance on the performance of the SC chart. We used simulation to evaluate the performance of the SC chart, in terms of average run length (ARL), standard deviation of the run length (SDRL), median run length (MDRL), and expected average run length (EARL) metrics. The results obtained indicate that measurement errors negatively affect the performance of the SC chart and taking multiple measurements on each item or/and increasing the slope coefficient of the covariate error model can effectively reduce the adverse impact of errors on the chart's performance. Finally, an illustrative real life example is provided to demonstrate the undesired impact of measurement errors on the detection capability of the SC chart. [ABSTRACT FROM AUTHOR]
ISSN:08982112
DOI:10.1080/08982112.2024.2409457