One of the most powerful tools in quality control is the statistical control chart. First developed in the 1920's by Walter Shewhart, the control chart found widespread use during World War II and has been employed, with various modifications ever since. The drawbacks to multivariate charting schemes is their inability to identify which variable was the source of the signal. The multivariate ex...

Control charts based on generalized likelihood ratio test (GLRT) are attractive from both theoretical and practical points of view.Most of the existingworks in the literature focusing on the detection of the process mean and variance are almost based on the assumption that the shifts remain constant over time. The case of the patterned mean and variance changes may not be well discussed. In thi...

In this article, an attribute control chart has been proposed using the accelerated hybrid censoring logic for the monitoring of defective items whose life follows a Weibull distribution. The product can be tested by introducing the acceleration factor based on different pressurized conditions such as stress, load, strain, temperature, etc. The control limits are derived based on the binomial d...

The EWMA quality control chart, and its multivariate version (MEWMA), may be designed to efficiently detect small shifts in the mean vector of a set of p quality characteristics of a production process. However, this work presents a method for the optimal design of the parameters of the MEWMA and EWMA charts to control processes where it is not convenient to detect small magnitude shifts and, a...

With process computers routinely collecting measurements on large numbers of process variables, multivariate statistical methods for the analysis, monitoring and diagnosis of process operating performance have received increasing attention. Extensions of traditional univariate Shewhart, CUSUM and EWMA control charts to multivariate quality control situations are based on Hotelling's T 2 statist...

In high quality industrial processes, the control chart is design based on cumulative count of conforming (CCC) items is very useful. In this paper, the performance of CCC-r chart with variable sampling intervals (CCC-rVSI chart) in the presence ofinspectionerrors isinvestigated. The efficiency of CCC-rVSI chart is compared with CCC-r chart with fixed sampling interval (CC...

Abstract The objective of this research is to study numerical integral equation method (NIE) using five quadrature rules namely, composite midpoint rule, trapezoidal Simpson’s Boole’s rule and Gauss-Legendre for approximating the average run length on extended exponentially weighted moving (extended EWMA) control chart autoregressive process with explanatory variables when white noise follows a...

Quick detection of an assignable cause is necessary for process accuracy with respect to the specifications. The aim this study monitor time and magnitude processes based on unit-interval data. To end, maximum exponentially weighted moving average (Max-EWMA) control chart simultaneous monitoring event proposed. be precise, beta unit gamma distributions are considered develop Max-EWMA chart. cha...

Statistical process control methods for monitoring processes with univariate ormultivariate measurements are used widely when the quality variables fit to known probabilitydistributions. Some processes, however, are better characterized by a profile or a function of qualityvariables. For each profile, it is assumed that a collection of data on the response variable along withthe values of the c...