This paper studies an attribute control chart for monitoring the number of nonconforming items using a triple sampling (TS-np) which has not yet been applied to charts. The design and procedure decision about state process are given. Mathematical expressions average run length (ARL) in-control out-of-control processes sample (ASN) A bi-objective genetic algorithm that seeks minimize ASN probabi...

Abstract This study aim to propose a moving average control chart explicit formula based on the Generalized Poisson distribution ( MA GP ) and compare performance of with that Shewhart C ). The run length ARL is used consider performance. results indicated superior for detecting small shifts. Practitioners will find this be accurate as well simple apply use.

Automation in the service industry is emerging as a new wave of industrial revolution. Standardization and consistency quality an important part automation process. The control methods widely used manufacturing can provide measurement process monitoring. In particular, chart online monitoring technique be to quickly detect whether out control. However, more difficult than that because variabili...

Most commonly used control charts for monitoring quality characteristics of the processes were developed under the assumption that the observations are randomly sampled from a normal population. It is well known that these control charts have more false alarms than usual when processes are positively autocorrelated. One remedy is to adjust the control limits such that the modified control chart...

Not all data in practice came from a process with normal distribution. When the process distribution is non-normal or unknown, the commonly used Shewhart control charts are not suitable. In this paper, a new non-parametric CUSUM Mean Chart is proposed to monitor the possible small mean shifts in the process. The sampling properties of the new monitoring statistics are examined and the average r...

Time series control charts are popular methods for statistical process control of autocorrelated processes. In order to implement these methods, however, a time series model of the process is required. Since time series models must always be estimated from process data, model estimation errors are unavoidable. In the presence of modeling errors, time series control charts that are designed unde...