Recent advancements in data-driven process control and performance analysis could
provide the wastewater treatment industry with an opportunity to reduce costs and improve …

Technological advances led to increasingly larger industrial quality-related datasets calling
for process monitoring methods able to handle them. In such context, the application of …

Operating units, in practice, often suffer from multiple modes of failure, and each failure
mode has a distinct influence on the service life cycle path of a unit. The rapid development …

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

There are always challenges in various industrial or non-industrial processes in which the
product quality/service is described by a large number of quality characteristics. Thus …

Improvements in measuring devices, the development of sensing technologies, automated
record-keeping and cloud storage facilities have offered us a large volume of data streams …

Monitoring high-dimensional processes is a challenging task, as the underlying dependency
structure among variables is often too complicated to estimate accurately. The inherent …

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 …

High‐dimensional applications pose a significant challenge to the capability of conventional
statistical process control techniques in detecting abnormal changes in process parameters …

High-dimensional data refers to a dataset that contains many variables or features, typically
with many more features p than observations n (ie n< p). With technological advancements …