Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...

The setting of the control limits to utilize on a control chart supposes the assumption of the normality. However, in many situations, this condition does not hold. There are numerous studies on the control charts when the underlying distribution is non-normal. This paper examines the effects of non-normality as measured by skewness and provides an alternative method of designing individuals co...

Control charts primarily in the form of X chart are widely used to identify the situations when control actions will be needed for manufacturing systems. Various types of patterns are observed in control charts. Identification of these control chart patterns (CCPs) can provide clues to potential quality problems in the manufacturing process. This paper introduces a novel hybrid intelligent syst...

In some multivariate statistical control applications, the data of the process cannot be precise and defined linguistically in practice. Using multivariate control charts in such situations with non-precise data leads to misleading results. In this paper, a new neural network-based monitoring scheme is presented by considering fuzzy multivariate multinomial data. The proposed approach is also a...

smart home is composed of several controllers with different plants in control. if each controller works independently, without considering the mutual effect of the others in the control process, the whole system could definitely not converge to an optimum desired status and may not ever reach the demanded condition. the function of different controller system may has conflict in some condition...

Software inspections are an efficient way of controlling and reducing the number of faults throughout the software life cycle [Ebenau94a]. A process, more or less stable and formal, is used when inspecting a document and by using statistical quality control [Mills88] the software inspection process can be monitored. Further, an early warning system can be implemented into organisations which ca...

• The Shewhart control charts, used for monitoring industrial processes, are the most popular tools in Statistical Process Control (SPC). They are usually developed under the assumption of independent and normally distributed data, an assumption rarely true in practice, and implemented with estimated control limits. But in general, we essentially want to control the process mean value and the p...

An effective control scheme can be instrumental in increasing productivity and reducing cost. While facing an outlier-existing process, using the mean ( X ) control chart and the range (R) control chart for monitoring the process mean and variance will lead to high level false alarms. Recently, some median ( X~ ) control charts, such as the X~ Shewhart control chart, the exponentially weighted ...

Our purpose is to indicate a new method for determining the control limits of univariate control charts to show the effectiveness of golden ratios search. We examine a solution to a problem when signals from mean and variance charts differ. Lack of concordance in the signals from mean and variance (or standard deviation) control charts bring confusion to Quality Control managers which in turn m...