A S2-GWMA control chart for monitoring the process variability

2021 ◽  
pp. 1-19
Author(s):  
Vasileios Alevizakos ◽  
Kashinath Chatterjee ◽  
Christos Koukouvinos ◽  
Angeliki Lappa
Keyword(s):  
Control Chart ◽  
Process Variability

scholarly journals A process variability control chart

2008 ◽  
Vol 24 (2) ◽  
pp. 345-368 ◽  
Author(s):  
Muhammad Riaz ◽  
Ronald J. M. M. Does
Keyword(s):  
Control Chart ◽  
Process Variability

Simulation on control chart in monitoring the multivariate process variability

2017 ◽  
Author(s):  
Besse Helmi Mustawinar ◽  
Nurtiti Sunusi ◽  
Erna Tri Herdiani
Keyword(s):  
Control Chart ◽  
Process Variability ◽  
Multivariate Process

scholarly journals Complex Control Chart Interpretation

10.5772/56441 ◽  
2013 ◽  
Vol 5 ◽  
pp. 13 ◽  
Author(s):  
Darja Noskievičová
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Control Chart ◽  
Statistical Properties ◽  
Comparison Analysis ◽  
Statistical Process ◽  
Process Variability ◽  
Correct Application ◽  
Western Electric ◽  
Special Causes

Identification of the assignable causes of process variability and the restriction and elimination of their influence are the main goals of statistical process control (SPC). Identification of these causes is associated with so called tests for special causes or runs tests. From the time of the formulation of the first set of such rules (Western Electric rules) several different sets have been created (Nelson rules, Boeing AQS rules, Trietsch rules). This paper deals with the comparison analysis of these sets of rules, their basic statistical properties and the mistakes accompanying their application using SW support. At the end of this paper some recommendations for the correct application of the runs tests are formulated.

MONITORING AUTOCORRELATED PROCESS MEAN AND VARIANCE USING A GWMA CHART BASED ON RESIDUALS

2008 ◽  
Vol 25 (06) ◽  
pp. 781-792 ◽  
Author(s):  
SHEY-HUEI SHEU ◽  
SHIN-LI LU
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Moving Average ◽  
Autoregressive Process ◽  
Process Mean ◽  
Process Variability ◽  
Autocorrelated Process ◽  
Ewma Control Chart ◽  
Mean And Variance ◽  
Run Lengths

This investigation elucidates the feasibility of monitoring a process for which observational data are largely autocorrelated. Special causes typically affect not only the process mean but also the process variance. The EWMA control chart has recently been developed and adopted to detect small shifts in the process mean and/or variance. This work extends the EWMA control chart, called the generally weighted moving average (GWMA) control chart, to monitor a process in which the observations can be regarded as a first-order autoregressive process with a random error. The EWMA and GWMA control charts of residuals used to monitor process variability and to monitor simultaneously the process mean and variance are considered to evaluate how average run lengths (ARLs) differ in each case.

A NEW VARIABLES CONTROL CHART FOR SIMULTANEOUSLY MONITORING MULTIVARIATE PROCESS MEAN AND VARIABILITY

2002 ◽  
Vol 09 (01) ◽  
pp. 41-59 ◽  
Author(s):  
ARTHUR B. YEH ◽  
DENNIS K. J. LIN
Keyword(s):  
Control Chart ◽  
Integral Transformation ◽  
Real Life ◽  
Dimensional Control ◽  
Process Mean ◽  
Process Variability ◽  
Uniform Distributions ◽  
Probability Integral Transformation ◽  
Probability Integral ◽  
New Variables

In this paper, we propose a new variables control chart, called the box-chart, to simultaneously monitor, on a single chart, the process mean and process variability for multivariate processes. The box-chart uses a probability integral transformation to obtain two independently and identically distributed uniform distributions. Therefore, a box-shaped (thus the name), two-dimensional control chart can be constructed. We discuss in detail on how to construct the box-chart. The proposed chart is applied to two real-life examples. The performance of the box-chart is also compared to that of the traditional T2- and |S|-charts.

Multiobjective design of an S control chart for monitoring process variability

2012 ◽  
Vol 2 (4) ◽  
pp. 408 ◽  
Author(s):  
Abdul Sattar Safaei ◽  
Reza Baradaran Kazemzadeh ◽  
Seyed Taghi Akhavan Niaki
Keyword(s):  
Control Chart ◽  
Process Variability ◽  
Monitoring Process ◽  
Multiobjective Design
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