Constructing a Sensitive Control Chart to Monitor Process Mean using Optimal Filter: Time-Frequency Analysis Approach

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

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

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A Control Chart to Monitor a Multivariate Binomial Process

The most applied statistical methods for monitoring multivariate attribute processes have been developed assuming that they have a multinomial distribution, see e.g. Marcucci (1985) and Cassady and Nachlas (2006). However this assumption is not always reasonable; indeed, it is more general and correct to suppose that in each item it is possible to identify one or more of k ordered and not mutua...

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...

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...