Novel Bayesian CUSUM and EWMA control charts via various loss functions for monitoring processes
In this work, both the cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts have been reconfigured to monitor processes using a Bayesian approach. Our construction of these charts are informed by posterior and posterior predictive distributions found using three loss functions: the squared error, precautionary, and linex. We use these control charts on count data, performing a simulation study to assess chart performance. Our simulations consist of sensitivity analysis of the out‐of‐control shift size and choice of hyper‐parameters of the given distributions. Practical use of theses charts are evaluated on real data.
Other Information
Published in: Quality and Reliability Engineering International
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1002/qre.3229
Funding
Open Access funding provided by the Qatar National Library.
History
Language
- English
Publisher
WileyPublication Year
- 2022
License statement
This Item is licensed under the Creative Commons Attribution 4.0 International License.Institution affiliated with
- Qatar University
- College of Arts and Sciences - QU