The inference about the statistical properties of quality control methodologies is based on
the assumptions of normality and independence. In real industrial environments though …

This study compares the multi-period predictive ability of linear ARIMA models to nonlinear
time delay neural network models in water quality applications. Comparisons are made for a …

Purpose–The purpose of this paper is to suggest better methods for monitoring the
diagnostic and treatment services for providers of public health and the management of …

With the growth of automation in process industries, there is correlation in the process
variables. Deep learning has achieved many great successes in image and visual analysis …

In this article we propose a model suitable for statistical process control in short production
runs. We wish to detect on-line whether the mean of the process has exceeded a …

In this paper, a neural network-based identification model is proposed for both mean and
variance shifts in correlated processes. The proposed model uses a selective network …

Nowadays, customers are increasingly claiming not only for better quality products at the
lowest possible cost, but also demanding customized solutions to satisfy their specific …

Though traditional control charts have been widely used as effective tools in statistical
process control (SPC), they are not applicable in many industrial applications where the …

One of the primary tasks for process personnel is to detect and identify the underlying
process disturbances such that they can be quickly removed. Most research has concluded …

The aim of this paper is to present an economical design of an X chart for a short-run
production. The process mean starts equal to μ0 (in-control, State I) and in a random time it …