In some applications, the quality of a process is characterized by the functional relationship between a response variable and one or more explanatory variables. Profile monitoring is a technique for checking the stability of this relationship over time. General linear profile monitoring is particularly useful in practice due to its simplicity and flexibility. The existing monitoring methods su...

In manufacturing processes, maintaining quality is associated with proper process mean parameters and product quality metrics. The early detection of mean changes is important to reduce the number of defectives or non-conformities in the production. In this work, a diverse ensemble of Artificial Neural Networks (ANNs) with a leader network have been used to achieve this purpose, then a performa...

In this paper, a synthetic scaled weighted variance Xbar (synthetic SWV-Xbar) control chart is proposed to monitor the process mean of skewed populations. A comparison between the performances of the synthetic SWV-Xbar and synthetic WV-Xbar charts are made in terms of the average run length (ARL) values for the various levels of skewnesses as well as different magnitudes of positive and negativ...

In this paper, a comparative study of performance of some parametric and nonparametric EWMA control charts for detecting the process mean shift is considered. In section 2, we briefly describe each of the various EWMA models that are taken into account in our present study, Viz. the Parametric X -EWMA and Nonparametric Grouped Signed Rank (GSR)-EWMA, for the purpose of comparative study. In Sec...

Statistical process control is an important and convenient tool to stabilize the quality of manufactured goods and service operations. The traditional Shewhart control chart has been used extensively for process control, which is valid under the independence assumption of consecutive observations. In real world applications, there are many types of dependent observations in which the traditiona...

The problem of quickest change detection (QCD) under transient dynamics is studied, where the change from the initial distribution to the final persistent distribution does not happen instantaneously, but after a series of transient phases. The observations within the different phases are generated by different distributions. The objective is to detect the change as quickly as possible, while c...

Nonparametric or distribution-free charts can be useful in statistical process control when there is limited knowledge about the underlying process. In this paper a Shewhart-type chart is considered for the location, based on the Mann-Whitney statistic. The control limit calculations use Lugannani-Rice saddlepoint, Edgeworth and other approximation methods along with Monte Carlo estimation and ...

Time series monitoring methods, such as the Brown and Trigg methods, have the purpose of detecting pattern breaks (or “signals”) in time series data reliably and in a timely fashion. Traditionally, researchers have used the average run length statistic (ARL) on results from generated signal occurrences in simulated time series data to calibrate and evaluate these methods, with a focus on timeli...

The engineering processes are made up of a number of the phenomenons working together that may lead to defects with multiple causes. In order to model such types of multiple cause defect systems we may not rely on simple probability models and hence, the need arises for mixture models. The commonly used control charts are based on simple models with the assumption that the process is working un...