Paper
19 December 2023 The effect of measurement error on the performance of the s chart
Ming Ha Lee, Zhi Yau Lee, Wei Lin Teoh, Vie Ming Tan, Melinda Kong, XinYing Chew
Author Affiliations +
Proceedings Volume 12936, International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023); 129361M (2023) https://doi.org/10.1117/12.3011408
Event: International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023), 2023, Istanbul, Turkey
Abstract
In this paper, we look at how measurement error affects the statistical performance of the s chart. The linear covariate error model is used to evaluate the efficiency of the s chart with measurement error. The influence of input factors on the performance of the s chart is explored using the linear covariate error model. Shorter out-of-control average run lengths of the s chart are seen to be connected to smaller measurement error ratios, higher coefficient B values, and more repeated measurements of each item in each sample. To illustrate how to use the s chart when there is measurement error, an example is given.
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Ming Ha Lee, Zhi Yau Lee, Wei Lin Teoh, Vie Ming Tan, Melinda Kong, and XinYing Chew "The effect of measurement error on the performance of the s chart", Proc. SPIE 12936, International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023), 129361M (19 December 2023); https://doi.org/10.1117/12.3011408
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KEYWORDS
Error analysis

Performance modeling

Design and modelling

Signal processing

Statistical modeling

Autocorrelation

Covariance

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