An EWMA-type sign chart with exact run length properties

Abstract In this paper, a new phase II EWMA-type chart for count data, based on the sign statistic, is proposed and applied to the monitoring of the location of an unknown continuous distribution. The most valuable characteristics of this new chart are that: a) it only uses positive integer-valued weights to account for the past process history, b) the plotted statistic is always an integer, and c) its run length properties can be exactly obtained without resorting to expensive simulations or unreliable approximations. We provide the methodology to compute the exact run length properties of the proposed chart and the algorithms to obtain the optimal chart parameters through the minimization of the out-of-control average run length. We also compare the statistical performance of this new EWMA-type sign chart vs. two classical continuous type EWMA sign charts, a CUSUM-type sign chart and a GWMA-type sign chart. The computational evaluations show that the proposed EWMA control chart outperforms the other control charts for a wide range of location shifts. Finally, two examples implementing this new EWMA type sign chart are given.

[1]  Marion R. Reynolds,et al.  A Nonparametric Procedure for Process Control Based on Within-Group Ranking , 1979 .

[2]  Philippe Castagliola,et al.  A new memory-type monitoring technique for count data , 2015, Comput. Ind. Eng..

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

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

[5]  N. Balakrishnan,et al.  A Generally Weighted Moving Average Signed‐rank Control Chart , 2016, Qual. Reliab. Eng. Int..

[6]  Marcel F. Neuts,et al.  Matrix-geometric solutions in stochastic models - an algorithmic approach , 1982 .

[7]  Subhabrata Chakraborti,et al.  Nonparametric Statistical Inference , 2011, International Encyclopedia of Statistical Science.

[8]  C. A. McGilchrist,et al.  Note on a Distribution-free CUSUM Technique , 1975 .

[9]  Raid W. Amin,et al.  A nonparametric exponentially weighted moving average control scheme , 1991 .

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

[11]  Tom Burr,et al.  Introduction to Matrix Analytic Methods in Stochastic Modeling , 2001, Technometrics.

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

[13]  M. R. Reynolds,et al.  Nonparametric quality control charts based on the sign statistic , 1995 .

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

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

[16]  Giovanni Celano,et al.  On the implementation of the Shewhart sign control chart for low-volume production , 2016 .

[17]  Shin-Li Lu,et al.  An Extended Nonparametric Exponentially Weighted Moving Average Sign Control Chart , 2015, Qual. Reliab. Eng. Int..

[18]  Giovanni Celano,et al.  The performance of the Shewhart sign control chart for finite horizon processes , 2015 .

[19]  Vaidyanathan Ramaswami,et al.  Introduction to Matrix Analytic Methods in Stochastic Modeling , 1999, ASA-SIAM Series on Statistics and Applied Mathematics.

[20]  Muhammad Riaz,et al.  An Efficient Nonparametric EWMA Wilcoxon Signed‐Rank Chart for Monitoring Location , 2017, Qual. Reliab. Eng. Int..

[21]  B. P. Dudding,et al.  Quality control charts , 1942 .

[22]  Christian H. Weiß,et al.  EWMA Monitoring of Correlated Processes of Poisson Counts , 2009 .

[23]  Smiley W. Cheng,et al.  A new non‐parametric CUSUM mean chart , 2011, Qual. Reliab. Eng. Int..

[24]  Fugee Tsung,et al.  A Multivariate Sign EWMA Control Chart , 2011, Technometrics.

[25]  Saddam Akber Abbasi,et al.  A new nonparametric EWMA sign control chart , 2012, Expert Syst. Appl..