Abstract
Statistical process control chart constants are bias correction factors used to establish three-sigma limits that are used to identify assignable variation. These constants have been tabulated for normal sampling. Subsequent research has verified the robustness for non-normal sampling. This paper explores exact results for both the normal distribution and select non-normal distributions using a computer algebra system to compute the exact values of the constants.
This original work highlights the wide application that APPL enjoys. The ability to find exact control chart constants for non-normal distributions highlights the utility of exploring many distributions in an applied setting. The calculation of control chart constants is critical in the area of quality control known as statistical process control. Use of APPL procedures OrderStat, RangeStat and Transform are critical to this research. Furthermore the BootstrapRV procedure extends such investigations into non parametric, bootstrap based analysis.
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Kaczynski, W.H., Leemis, L.M. (2017). Control Chart Constants for Non-normal Sampling. In: Glen, A., Leemis, L. (eds) Computational Probability Applications. International Series in Operations Research & Management Science, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-43317-2_9
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DOI: https://doi.org/10.1007/978-3-319-43317-2_9
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