Robust multivariate control charts based on Birnbaum–Saunders distributions

C Marchant, V Leiva, FJA Cysneiros… - Journal of Statistical …, 2018 - Taylor & Francis
Multivariate control charts are powerful and simple visual tools for monitoring the quality of a
process. This multivariate monitoring is carried out by considering simultaneously several …

Robust T2 control chart using median‐based estimators

F Maleki, S Mehri, A Aghaie… - Quality and Reliability …, 2020 - Wiley Online Library
One of the most widely used multivariate control charts is the Hotelling T2. In order to
construct a Hotelling T2 control chart, the mean vector (μ) and the variance–covariance …

Anomaly detection for unlabelled unit space using the Mahalanobis–Taguchi system

M Ohkubo, Y Nagata - Total Quality Management & Business …, 2021 - Taylor & Francis
Alongside the progress in technology related to the Internet of Things, the Mahalanobis–
Taguchi (MT) system, which is an anomaly detection technique suitable for monitoring the …

Alternative Hotelling's T2 Charts using Winsorized Modified One‐Step M‐estimator

FS Haddad, SS Syed‐Yahaya… - Quality and Reliability …, 2013 - Wiley Online Library
Hotelling's T2 chart is a popular tool for monitoring statistical process control. However, this
chart is sensitive in the presence of outliers. To alleviate the problem, this paper proposed …

A Robust Bivariate Control Chart Alternative to the Hotelling's T2 Control Chart

MOA Abu‐Shawiesh, BM Golam Kibria… - Quality and Reliability …, 2014 - Wiley Online Library
In this paper, we proposed a new bivariate control chart denoted by based on the robust
estimation as an alternative to the Hotelling's T2 control chart. The location vector and the …

Robust control charts for monitoring process variability in phase I multivariate individual observations

AM Variyath, J Vattathoor - Quality and Reliability Engineering …, 2014 - Wiley Online Library
Multivariate control charts are widely used in various industries to monitor the shifts in
process mean and process variability. In Phase I monitoring, control limits are computed …

A control chart based on cluster-regression adjustment for retrospective monitoring of individual characteristics

HC Ong, E Alih - PloS one, 2015 - journals.plos.org
The tendency for experimental and industrial variables to include a certain proportion of
outliers has become a rule rather than an exception. These clusters of outliers, if left …

What is the role of expert intuition in process control?

MD Hanna, D Pons… - International Journal of …, 2020 - inderscienceonline.com
Rules of statistical process control (SPC) suggest that processes should not be adjusted by
workers without an explicit data-driven management directive. By contrast, in many …

A non-linear mixed model approach for detecting outlying profiles

AV Quevedo, GG Vining - Journal of Quality Technology, 2023 - Taylor & Francis
In parametric non-linear profile modeling, it is crucial to map the impact of model parameters
to a single metric. According to the profile monitoring literature, using multivariate T 2 statistic …

Approximate design and performance of the robust control charts for monitoring dispersion in Phase I

A Saghir, A Faraz - Quality and Reliability Engineering …, 2018 - Wiley Online Library
This article designs and studies the approximate performance of robust dispersion charts,
namely, MAD chart, S n chart, and Q n chart, in Phase I analysis (recently developed in the …