The notion of variation and determining and eliminating it has become a subject that has found a wide application area after total quality approach has become widespread. There is a variety of control charts used in determining variation. Since the 1920’s, when W.Shewhart developed the first control chart, control charts, which have been examined many times in every aspect, are accepted to be o...

Control charts for monitoring of process variance are developed based on Shewhart, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts for mean. In all these variance control charts, log transformation of the sample variance is used. The design procedure of this chart is complex and it is poorly understood by the industry. In this paper a EWMA chart for monito...

In most statistical process control (SPC) applications, it is assumed that the quality of a process or product can be adequately represented by the distribution of a univariate quality characteristic or by the general multivariate distribution of a vector consisting of several correlated quality characteristics. In many practical situations, however, the quality of a process or product is bette...

In Statistical quality control a very widely used measure is average run length (ARL) which may be worked out by different methods like integral equation, approximations, and Monte Carlo simulations. The ARL measure and the other related measures are of major significance in every type of production process. An omission in its computation (and hence its related measures such as extra quadratic ...

OBJECTIVE Applying statistical process control (SPC) charts in perinatal mortality surveillance (as an epidemiological indicator). METHOD The control charts were prepared using 51,840 births; 286 cases were produced from these births. All information came from SUSALUD between January 2004 and December 2007. Two control charts are presented; the first one's central line was considered to be th...

The performance of attributes control charts (such as c and np charts) is usually evaluated under the assumption of known process parameters (i.e., the nominal proportion of nonconforming units or the nominal number of nonconformities). However, in practice, these process parameters are rarely known and have to be estimated from an in-control phase I data set. In this paper, we derive the run l...

Processes characterized by high dimensional and mixture data challenge traditional statistical process control charts. In this study, we propose a multivariate control chart based on the Gower distance that can handle a mixture of continuous and categorical data. An extensive simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compa...

Control charts are widely used in industry as a tool to monitor process characteristics. Deviations from process targets can be detected based on the evidence of statistical significance. The control chart helps to take decisions such as the need for machine or technology replacement to monitor the process with categorical observations. Fuzzy logic is used to cram the uncertainty and vagueness ...