An Adaptive Exponentially Weighted Moving Average Control Chart

By Giovanna Capizzi, Guido Masarotto. Technometrics, 2003

364 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/afb357c1733923a94cedabed691d2c1f7c67d5db

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

A Nonparametric EWMA Sign Chart for Location Based on Individual Measurements (2011, methodology): “…EWMA procedure with resetting, Woodall and Mahmoud (2005) recommended that EWMA charts always be used in conjunction with Shewhart limits, and Capizzi and Masarotto (2003) proposed an adaptive EWMA (AEWMA) approach; their approach combined the EWMA and the Shewhart approaches in a smoother…”
Optimal design of the adaptive EWMA chart for the mean based on median run length and expected median run length (2019, methodology): “To avoid the inertia problem and balance the overall performance of the EWMA scheme, Capizzi and Masarotto (2003) proposed a new adaptive EWMA chart (denoted as AEWMA X̄ chart), which CONTACT Jinsheng Sun jssun67@163.com, tanganan@njust.edu.cn © 2018 International Chinese Association of…”
A variable sampling interval EWMA chart for attributes (2010, methodology): “Although the parameters of adaptive charts may be allowed to vary over a discrete set of values (see for instance Vaughan [34]) or even over a continuous interval (e.g., Capizzi and Masarotto [ 5 ]), most of the proposed schemes in the literature allow them to vary just between two values, for great”
An adaptive exponentially weighted moving average control chart for monitoring process variances (2008, methodology): “Capizzi and Mastrotto 18 developed a control chart based on the EWMA-C statistic for monitoring process means, which has been referred to as the adaptive EWMA (AEWMA) chart.”
The computation of average run length and average time to signal: an overview (2014, methodology): “To avoid the flaw that the ARL of a chart designed for a small shift is quite different from that designed for a large shift, Capizzi and Masarotto [49] devised a design strategy, in which the minimizing of the penalized function involved can be worked out through simulated annealing algorithm [51].”
Modified exponentially weighted moving average (EWMA) control chart for an analytical process data (2011, background): “Sci. problem, Capizzi and Masarotto (2003) designed Adaptive EWMA (AEWMA) control charts.”
CONTROL CHART FOR MONITORING NONPARAMETRIC PROFILES WITH ARBITRARY DESIGN (2009, methodology): “results in Capizzi and Masarotto (2003) , we recommend using �0 ∈ [0.05,0.1] and 5 ≤ c ≤ 15.”
CUSUM and EWMA multi-charts for detecting a range of mean shifts (2007, background): “Moreover, in recent years, adaptive CUSUM (Sparks (2000)) and adaptive EWMA (Capizzi and Masarotto (2003)) have been proposed in the literature to achieve the same aim as in the paper.”
Effect of measurement error on exponentially weighted moving average control charts under ranked set sampling schemes (2015, background): “For further details, see Lucas and Saccucci, [3] Steiner,[4] Capizzi and Masarotto,[5] Montgomery,[6] Abbas et al.,[7,8] Abbasi and Miller,[9] Nazir et al.,[10] Riaz et al.,[11] Haq,[12] Haq et al.,[13,14] and references cited therein.”
Adaptive nonparametric CUSUM scheme for detecting unknown shifts in location (2014, methodology): “Capizzi and Masarotto (2003) provided a class of new control charts, called adaptive EWMA charts.”