in this research, an iterative approach is employed to recognize and classify control chart patterns. to do this, by taking new observations on the quality characteristic under consideration, the maximum likelihood estimator of pattern parameters is first obtained and then the probability of each pattern is determined. then using bayes’ rule, probabilities are updated recursively. finally, when...

control chart is the most well-known chart to monitor the number of nonconformities per inspection unit where each sample consists of constant size. generally, the design of a control chart requires determination of sample size, sampling interval, and control limits width. optimally selecting these parameters depends on several process parameters, which have been considered from statistical and...

a new method is developed for a fast identification of the stability situation of industrial processes. the proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. an indication ratio is then defined as the ratio of the maximum data range value to the difference between the maximum and average values for individual d...

Multivariate control charts such as Hotelling`s T^ 2 and X^ 2 are commonly used for monitoring several related quality characteristics. These control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. The purpose of this article is to discuss some issues related to the G chart proposed by Levinson et al. [9] for detecting shifts in ...