In today's highly competitive industrial environment due to fast technology development, quality practitioners will to detect out-of-control situations and take actions whenever is necessary as soon as possible. Accordingly, new statistical procedures have been enhanced incessantly both to handle high yield processes along with looking for methods of minimizing all quality cost. CCC-r chart, th...

Previously, quality control and improvement researchers discussed multivariate control charts for independent processes and univariate control charts for autocorrelated processes separately. We combine the two topics and propose vector autoregressive (VAR) control charts for multivariate autocorrelated processes. In addition, we estimateAR(p) models instead ofARMAmodels for the systematic cause...

Normality is a common assumption for many quality control charts. One should expect misleading results once this assumption is violated. In order to avoid this pitfall, we need to evaluate this assumption prior to the use of control charts which require normality assumption. However, in certain cases either this assumption is overlooked or it is hard to check. Robust control charts and bootstra...

In many situations, the times between certain events are observed and monitored instead of the number of events particularly when the events occur rarely. In this case, it is common to assume that the times between events follow an exponential distribution. Control charts are one of the main tools of statistical process control and monitoring. Control charts are used in phase I to assist operat...

In this article, a set of clustering algorithms based on Fuzzy Logic and Data Mining are applied, allowing to obtain data in the form of linguistic rules and charts about the behaviour of the Tinto and Odiel river estuary (SW Spain) affected by Acid Mine Drainage (AMD). In order to provide researchers with no skills on data mining techniques an easy and intuitive interpretation, we have develop...

A review of the literature on cause selecting charts (CSCs) in multistage processes is given, with a concentration on developments which have occurred since 1993. Model based control charts and multiple cause selecting charts (MCSCs) are reviewed. Several articles based on normally and non-normally distributed outgoing quality characteristics are analyzed and important issues such as economic d...

One of the primary tools used in statistical quality control is the control charts. The standard assumptions that are usually cited in justifying the use of control charts are that the data generated by the in control process are independent and identically distributed. However the independency assumption is not realistic in practice. Data sets collected from industrial processes may have corre...

One-class classification problems have attracted a great deal of attention from various disciplines. In the present study, we attempt to extend the scope of application of the one-class classification technique to statistical process control (SPC) problems. We propose new multivariate control charts that apply the effectiveness of one-class classification to improvement of Phase I and Phase II ...

usually, in monitoring schemes the nominal value of the process parameter is assumed known. however, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. on the other hand, applying a fixed control limit for the risk-adjusted bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar...

OBJECTIVE To examine the suitability of the growth charts that are currently used in Israel and consider their replacement with a recent standard. In a sample of schoolchildren, the current Tanner and Whitehouse standards were compared with the new growth charts from the Centers for Disease Control and Prevention (CDC). METHOD A total of 746 Israeli healthy children (368 boys and 378 girls) a...