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http://dx.doi.org/10.7469/JKSQM.2016.44.1.167

On the Application of Zp Control Charts for Very Small Fraction of Nonconforming under Non-normal Process  

Kim, Jong-Gurl (Department of Industrial Engineering, Sungkyunkwan University)
Choi, Seong-Won (Department of Industrial Engineering, Sungkyunkwan University)
Kim, Hye-Mi (Department of Industrial Engineering, Sungkyunkwan University)
Um, Sang-Joon (SK hynix Inc.)
Publication Information
Journal of Korean Society for Quality Management / v.44, no.1, 2016 , pp. 167-180 More about this Journal
Abstract
Purpose: The problem for the traditional control chart is that it is unable to monitor the very small fraction of nonconforming and the underlying distribution is the normal distribution. $Z_p$ control chart is useful where it controls the vert small fraction on nonconforming. In this study, we will design the $Z_p$ control chart in order to use under non-normal process. Methods: $Z_p$ is calculated not by failure rate based on attribute data but using variable data. Control limit for non-normal $Z_p$ control chart is designed based on ${\alpha}$-risk calculated by cumulative distribution function of Burr distribution. ${\beta}$-risk, which is for performance evaluation, obtains in the Burr distribution's cumulative distribution function and control limit. Results: The control limit for non-normal $Z_p$ control chart is designed based on Burr distribution. The sensitivity can be checked through ARL table and OC curve. Conclusion: Non-normal $Z_p$ control chart is able to control not only the very small fraction of nonconforming, but it is also useful when $Z_p$ distribution is non-normal distribution.
Keywords
$Z_p$ Control Chart; Non-normal Process; Burr Distribution;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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