We review the long-established rational subgrouping principle for determining an effective
sampling plan for process monitoring. We present some other general advice that has been …

The main aim of this article is to review and discuss two particular topics of statistical process
monitoring: the need for a nonparametric approach to Phase I analysis and the use of …

A multistage system refers to a system consisting of multiple components, stations or stages
required to finish the final product or service. Multistage systems are very common in …

In monitoring complex systems, apart from quick detection of abnormal changes of system
performance and key parameters, accurate fault diagnosis of responsible factors has …

Memory control chart such as multivariate CUSUM (MCUSUM) and multivariate EWMA
(MEWMA) control charts are considered superior for the detection of small-to-moderate …

Fault detection and root cause identification are both important tasks in Multivariate
Statistical Process Control (MSPC) for improving process and product quality. Most …

In multidimensional applications, it is very rare that all variables shift at the same time. A
statistical process control procedure would have superior efficiency when limited to the …

Most statistical process control research focuses on single-stage processes. This article
considers the problem of multistage process monitoring and fault identification. This problem …

Statistical Process Control (SPC) including monitoring and diagnosis is very important and
challenging for multistage processes with categorical data. This article proposes a Binary …

Quality prediction model has been developed in various industries to realize the faultless
manufacturing. However, most of quality prediction model is developed in single-stage …