Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characterist...

Control charts are used to determine whether or not a manufacturing or business process is in a state of statistical control. Various schemes of the standard (Shewhart) X chart for autocorrelated data at sample sizes of 2 and 3 are developed and compared with the schemes of the same chart for IID data at various process shifts in the process mean. It is clear from the comparison that the in-con...

This paper proposes a distribution-free multivariate statistical process control (MSPC) chart to detect general distributional changes in multivariate process variables. The chart is deployed based on a multivariate goodness-of-fit test, which is extensible to high dimensional observations. The chart also employs data-dependent control limits, which are computed on line along with the charting ...

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...

BACKGROUND Comparison of outcomes requires adequate risk adjustment for differences in patient risk and the type of intervention performed. Both unintentional and intentional misclassification (also called gaming) of risk factors might lead to incorrect benchmark results. Therefore, misclassification of risk factors should be detected. We investigated the use of statistical process control tech...

This article investigates integrated maintenance, production, and product quality control policy for a supply chain consisting of single machine producing only one type product, main storage warehouse, multi-purchases warehouses. The variation the production rate its use over time impact manufacturing system’s degradation degree. Hence, is subject to random failure that directly affects product...

In statistical process control, the primary method used to monitor the number of nonconformities is the c-chart. The conventional c-chart is based on the assumption that the occurrence of nonconformities in samples is well modeled by a Poisson distribution. When the Poisson assumption is not met, the X-chart (individuals chart) is often used as an alternative charting scheme in practice. In thi...

In the previous two Chapters, we proposed fraction nonconforming nonparametric control charts to monitor process location and process variability. It is also shown that performance of proposed control charts are superior to that of the Shewhart X and sign charts. If process is running in an in-control state for a long period, it will reach in steady-state mode. In order to characterize long-ter...