Abstract
In this article, Bayesian approach is used to develop exponentially weighted moving average (EWMA) control chart under non-informative and informative priors and loss functions for small to moderate shift detection in the process. The performance of Bayesian EWMA control chart has been evaluated using ARL and SDRL. Simulations are performed to compute the performance measures for various values of smoothing constant and sample size. Sensitivity analysis of hyper-parameters of informative (conjugate) prior is also performed. To highlight the performance of Bayesian EWMA chart, we have presented two real life applications for illustrative purpose. The recommendations are also given for the future.
| Original language | English |
|---|---|
| Pages (from-to) | 426-436 |
| Number of pages | 11 |
| Journal | Computers and Industrial Engineering |
| Volume | 112 |
| DOIs | |
| State | Published - Oct 2017 |
Bibliographical note
Publisher Copyright:© 2017 Elsevier Ltd
Keywords
- Bayesian approach
- Exponentially weighted moving average
- Linex loss function
- Precautionary loss function
- Squared error loss function
ASJC Scopus subject areas
- General Computer Science
- General Engineering
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