Abstract

We propose and study exponentially weighted moving average (EWMA) control charts for monitoring high-yield processes. The EWMA control charts are developed based on non-transformed geometric, binomial and Bernoulli counts. The proposed charts are evaluated based on the average number of items sampled before the first out-of-control signal is detected. By selecting small smoothing constants, the proposed EWMA control charts outperform in numerous cases the recently developed CUSUM control charts [Chang, T.C. and Gan, F.F., Cumulative sum charts for high yield processes. Statist. Sin., 2001, 11, 791–805], which are considered the most efficient control charting mechanisms in the existing literature for monitoring fraction non-conforming as small as 0.0001. Numerous simulations are included for performance comparisons. An example is also given to demonstrate the applicability of the proposed EWMA control charts.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.