Different control charts are developed for monitoring various types of quality characteristics
in the area of Statistical Process Monitoring (SPM). Moreover, new techniques are proposed …

Monitoring schemes are typically designed under the assumption of perfect measurements.
However, in real-life applications, data tend to be subjected to measurement errors, that is, a …

Control charts are important tools to monitor quality of products. One of useful applications is
to monitor the proportion of non‐conforming products. However, in practical applications …

In this paper, we shall discuss some statistical properties of the estimator of C p when
sample observations are autocorrelated and affected by measurement errors. The presence …

In this work we introduce two new classes of Shewhart-type control charts with
supplementary runs rules using a three or four region partition of the observed …

The performance of the triple sampling (TS) X¯ ̄X chart is investigated by using a linear
covariate error model that considers the presence of measurement errors (ME), called the …

In statistical process monitoring, the usual assumption when designing monitoring schemes
is that process parameters are known and have perfect measurements with independent …

In this paper, we introduce an R package EATME, which is known as E xponentially
weighted moving average (EWMA) control chart with A djustments T o M easurement E rror …

Autocorrelation and measurement errors have a negative effect on the performance of any
monitoring scheme; therefore, more efficient monitoring schemes are required to monitor …

Classical control charts were developed with the assumption that the quality characteristics
being monitored are independent. However, observations from several time‐dependent …