Control charts such as X and R charts are widely used in industry to monitor quality. These charts are effective in detecting large departures from the in-control condition. Other process monitoring methods, such as Cumulative Sum (CUSUM) charts are sequential in nature as they accumulate information from previous observations. CUSUM charts are good at detecting more moderate presistent process...

The integration of the curtailment method with control charts considerably improves detection speed by signalling an out-of-control condition prior to inspection whole sample. To date, few research works have focused on incorporation improve performance charts. Thus, this paper incorporates approach synthetic chart propose a (Curt_Syn) for detecting upward shifts in fraction non-conforming, p. ...

The CCC-r chart is developed based on cumulative count of a conforming (CCC) control chart that considers the cumulative number of items inspected until observing r nonconforming ones. Typically, the samples obtained from the process are analyzed through 100% inspection to exploit the CCC-r chart. However, considering the inspection cost and time would limit its implementation. In this paper, w...

In this paper, the concept of cumulative count of conforming chart (CCC chart) is applied in inspection and maintenance planning for systems where minor inspection, major inspection, minor maintenance and major maintenance are available. Several inspection and maintenance plans are defined and studied quantitatively. Analytic expressions of relevant statistics and their expectations are derived...

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...