Distribution-free exponentially weighted moving average control charts for monitoring unknown location

Distribution-free (nonparametric) control charts provide a robust alternative to a data analyst when there is lack of knowledge about the underlying distribution. A two-sided nonparametric Phase II exponentially weighted moving average (EWMA) control chart, based on the exceedance statistics (EWMA-EX), is proposed for detecting a shift in the location parameter of a continuous distribution. The nonparametric EWMA chart combines the advantages of a nonparametric control chart (known and robust in-control performance) with the better shift detection properties of an EWMA chart. Guidance and recommendations are provided for practical implementation of the chart along with illustrative examples. A performance comparison is made with the traditional (normal theory) EWMA chart for subgroup averages and a recently proposed nonparametric EWMA chart based on the Wilcoxon-Mann-Whitney statistics. A summary and some concluding remarks are given.

[1]  Douglas C. Montgomery,et al.  Statistical quality control : a modern introduction , 2009 .

[2]  S. W. Roberts Control chart tests based on geometric moving averages , 2000 .

[3]  Liu Jian-bin Nonparametric Control Charts Based On Medians , 2005 .

[4]  Ron S. Kenett,et al.  Encyclopedia of statistics in quality and reliability , 2007 .

[5]  W. Y. Wendy Lou,et al.  Distribution Theory of Runs and Patterns and Its Applications: A Finite Markov Chain Imbedding Approach , 2003 .

[6]  Douglas C. Montgomery,et al.  Introduction to Statistical Quality Control , 1986 .

[7]  M. A. Graham,et al.  A Nonparametric EWMA Sign Chart for Location Based on Individual Measurements , 2011 .

[8]  D. A. Evans,et al.  An approach to the probability distribution of cusum run length , 1972 .

[9]  Longcheen Huwang,et al.  New EWMA control charts for monitoring process dispersion , 2010, Comput. Stat. Data Anal..

[10]  Philippe Castagliola,et al.  Computational Statistics and Data Analysis an Ewma Chart for Monitoring the Process Standard Deviation When Parameters Are Estimated , 2022 .

[11]  Yan Su,et al.  Adaptive EWMA procedures for monitoring processes subject to linear drifts , 2011, Comput. Stat. Data Anal..

[12]  Subha Chakraborti,et al.  A nonparametric exponentially weighted moving average signed-rank chart for monitoring location , 2011, Comput. Stat. Data Anal..

[13]  Charles W. Champ Introduction to Statistical Quality Control, Fourth Edition , 2001 .

[14]  Narayanaswamy Balakrishnan,et al.  Precedence-type tests and applications , 2006 .

[15]  Stephen V. Crowder,et al.  Exponentially Weighted Moving Average (EWMA) Control Chart , 2008 .

[16]  Connie M. Borror,et al.  Robustness of the EWMA Control Chart to Non-Normality , 1999 .

[17]  Wilbert C.M. Kallenberg,et al.  Parametric control charts , 2003 .

[18]  Subhabrata Chakraborti,et al.  Robustness of the EWMA control chart for individual observations , 2011 .

[19]  S. Chakraborti Nonparametric (Distribution-Free) Quality Control Charts† , 2011 .

[20]  Szu Hui Ng,et al.  Nonparametric CUSUM and EWMA Control Charts for Detecting Mean Shifts , 2010 .

[21]  James M. Lucas,et al.  Exponentially weighted moving average control schemes: Properties and enhancements , 1990 .

[22]  Mark Jones,et al.  Risk‐adjusted survival time monitoring with an updating exponentially weighted moving average (EWMA) control chart , 2009, Statistics in medicine.

[23]  Amitava Mukherjee,et al.  Distribution-Free Exceedance CUSUM Control Charts for Location , 2013, Commun. Stat. Simul. Comput..

[24]  J. Bert Keats,et al.  Statistical Methods for Reliability Data , 1999 .

[25]  S. Chakraborti,et al.  Nonparametric Control Charts: An Overview and Some Results , 2001 .

[26]  W. Nelson Statistical Methods for Reliability Data , 1998 .

[27]  P Laanvander,et al.  A class of distribution‐free control charts , 2004 .