A new alternative Hotelling’s T2 control chart using MEWMA to monitor minimal mean deviation

A New Control Chart to Monitor Mean Shifts of Bi-Variate Quality Control Processes

A New Uni-attribute Control Chart to Monitor the Number of Nonconformities

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...

A New Control Chart to Monitor Mean Shifts of Bi-Variate Quality Control Processes

We propose a new approach to monitor an overall mean shift of a bi-variate quality control system. To do this, we first define beliefs on deciding whether the quality characteristics are in out-of-control state. Then, by taking new observations, in an iterative approach we update the belief of each quality characteristics being out-of-control. This task is performed using a recursive method and...

Using a Single Average Loss Control Chart to Monitor Process Mean and Variability

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A New Bootstrap Based Algorithm for Hotelling’s T2 Multivariate Control Chart

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...