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...

The most well-known uni-arribute control chart used to monitor the number of nonconformities per unit is the Shewhart type C-chart. In this paper, a new method is proposed in an attempt to reduce the false alarm rate in the C-chart. To do this, the decision on beliefs (DOB) concept is first uti [1] Corresponding author e-mail: [email protected]   lized to design an iterative method, where...

Control Chart Pattern Recognition (CCPR) is a critical task in Statistical Process Control (SPC). Abnormal patterns exhibited in control charts can be associated with certain assignable causes adversely affecting the process stability. Abundant literature treats the detection of different Control Chart Patterns (CCPs). In fact, numerous CCPR studies have been developed according to various obje...

The drawbacks to multivariate charting schemes is their inability to identify which variable was the source of the signal. The multivariate exponentially weighted moving average (MEWMA) developed by Lowry, et al (1992) is an example of a multivariate charting scheme whose monitoring statistic is unable to determine which variable caused the signal. In this paper, the run length performance of m...

In many manufacturing processes, the quality of a product is characterized by a non-linear relationship between a dependent variable and one or more independent variables. Using nonlinear regression for monitoring nonlinear profiles have been proposed in the literature of profile monitoring which is faced with two problems 1) the distribution of regression coefficients in small samples is unkno...

in this paper, we proposed a data-hiding scheme based on run length matrix. in a previously proposed method, a technique based on texture classification was introduced where four statically features extracted from run length matrix; then best cover images are selected based on these features. using appropriate features for comparing images from undetectability viewpoint, guarantees, less detect...

Shewhart charts are the most commonly utilised control for process monitoring in industries with assumption that underlying distribution of quality characteristic is normal. However, this may not always hold true practice. In paper, weighted-variance mean developed and their population standard deviation estimated using three subgroup scale estimators, namely deviation, median absolute trimmed ...

Online monitoring of high-dimensional processes variability in which the number variables is larger than sample size a challenging issue for quality practitioners because covariance matrix not invariable. To deal with this challenge, generalized multiple dependent state sampling (GMDS) chart based on ridge penalized likelihood ratio (RPLR) statistic developed Phase II multivariate process under...