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 are informed by posterior predictive distributions found three loss functions: squared error, precautionary, linex. We use on count data, performing simulation study assess chart performance. simulations consist sensitivity analysis out-of-control shift size choice hyper-parameters given distributions. Practical theses evaluated real data.