An effective control scheme can be instrumental in increasing productivity and reducing cost. While facing an outlier-existing process, using the mean ( X ) control chart and the range (R) control chart for monitoring the process mean and variance will lead to high level false alarms. Recently, some median ( X~ ) control charts, such as the X~ Shewhart control chart, the exponentially weighted ...

in many industrial and non-industrial applications the quality of a process or product is characterized by a relationship between a response variable and one or more explanatory variables. this relationship is referred to as profile. in the past decade, profile monitoring has been extensively studied under the normal response variable, but it has paid a little attention to the profile with the ...

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...

The exponentially weighted moving average chart of the squared deviation (EWMAS) is often applied for monitoring changes such as step shifts and linear drifts in process variation when no subgrouping is available. This paper analyzes the performance of the EWMAS chart under drifts in process variation. A fast and accurate algorithm based on the piecewise collocation method is presented for comp...

A memory-type control chart is an important tool of statistical process for monitoring small to moderate shifts in the manufacturing process. Using prior information by Bayesian approach helpful charts. In this paper, a new hybrid exponentially weighted moving average (HEWMA) suggested under theory using ranked set sampling (RSS) schemes posterior and predictive distribution with informative di...

The combination of Shewhart control charts and an exponentially weighted moving average (EWMA) control charts to simultaneously monitor shifts in the mean output of a production process has proven very effective in handling both small and large shifts. To improve the sensitivity of the control chart to detect off-target processes, we propose a combined Shewhart-EWMA (CSEWMA) control chart for m...

To detect sustainable changes in the production processes, memory-type control charts are frequently utilized. This study is conducted to assess performance of Bayesian adaptive exponentially weighted moving average (AEWMA) chart using ranked set sampling schemes following two different loss functions presence a measurement error for posterior and predictive distributions conjugate priors. base...

The exponentially weighted moving average (EWMA) control chart became very popular during the last decade. It is characterized by simple handling and good performance. It turns out, however, that the most popular EWMA scheme with fixed-width control limits – the asymptotic control limits are taken and do not change over time – detects early changes rather slowly. For the competing CUSUM chart t...