Economic statistical design of adaptive control schemes for monitoring the mean and variance: An application to analyzers

Several individuals control chart schemes are contrasted for the problem of monitoring the mean and variance of a normal process variable, with special consideration given to monitoring process analyzers, such as electrochemical devices, chromatographs, potentiometers, refractometers, and spectrometers. The combination of the exponentially weighted moving average (EWMA) chart and the Shewhart X chart that uses a variable sampling interval (VSI) policy is shown to be very effective for this problem. We develop a comprehensive economic model for the design of control schemes based on this chart combination. The economic model expresses the long-run cost per time unit of operating the combined VSI EWMA and VSI X chart scheme as a function of its design parameters, the parameters that describe the behavior of the process, and the cost parameters associated with the operation of the scheme. This economic model can be used to quantify the cost reduction that can be achieved by using the combined VSI scheme instead of traditional control schemes that use fixed sampling rates. We show that the reduction in cost as well as gains in performance are substantial.

[1]  Marion R. Reynolds,et al.  Robustness to non-normality and autocorrelation of individuals control charts , 2000 .

[2]  Kenneth J. Clevett Process Analyzer Technology , 1986 .

[3]  Changsoon Park,et al.  Economic design of a variable sampling rate EWMA chart , 2004 .

[4]  E. S. Page CONTINUOUS INSPECTION SCHEMES , 1954 .

[5]  W Zhang Variable Sampling Interval Control Charts with Sampling at Fixed Times , 2002 .

[6]  William H. Woodall,et al.  The State of Statistical Process Control as We Proceed into the 21st Century , 2000 .

[7]  W. Shewhart The Economic Control of Quality of Manufactured Product. , 1932 .

[8]  James M. Lucas,et al.  Exponentially weighted moving average control schemes with variable sampling intervals , 1992 .

[9]  Charles W. Champ,et al.  Design Strategies for Individuals and Moving Range Control Charts , 1994 .

[10]  Marion R. Reynolds,et al.  Evaluating properties of variable sampling interval control charts , 1995 .

[11]  Zachary G. Stoumbos,et al.  Control charts applying a sequential test at fixed sampling intervals with optional sampling at fixed times , 1993 .

[12]  Lloyd S. Nelson,et al.  Control Charts for Individual Measurements , 1982 .

[13]  Gary D. Nichols On-Line Process Analyzers , 1988 .

[14]  K. Schittkowski,et al.  NONLINEAR PROGRAMMING , 2022 .

[15]  S. Crowder Average Run Lengths of Exponentially Weighted Moving Average Control Charts , 1987 .

[16]  Leon S. Lasdon,et al.  Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming , 1978, TOMS.

[17]  Marion R. Reynolds,et al.  Control Charts and the Efficient Allocation of Sampling Resources , 2004, Technometrics.

[18]  Raid W. Amin,et al.  A Note on Individual and Moving Range Control Charts , 1998 .

[19]  E. Saniga Economic Statistical Control-Chart Designs with an Application to X̄ and R Charts@@@Economic Statistical Control-Chart Designs with an Application to X and R Charts , 1989 .

[20]  Marion R. Reynolds,et al.  Corrected diffusion theory approximations in evaluating properties of SPRT charts for monitoring a process mean , 1997 .

[21]  W. H. Boyes,et al.  Instrumentation reference book , 2003 .

[22]  Ronald J. M. M. Does,et al.  Shewhart-Type Control Charts for Individual Observations , 1993 .

[23]  Changsoon Park,et al.  Economic Design of a Variable Sampling Rate X-bar Chart , 1999 .

[24]  Marion R. Reynolds,et al.  The SPRT control chart for the process mean with samples starting at fixed times , 2001 .

[25]  D. T. LEWIS,et al.  Analytical Instrumentation , 1961, Nature.

[26]  E. Yashchin Statistical Control Schemes: Methods, Applications and Generalizations , 1993 .

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

[28]  D. Siegmund Sequential Analysis: Tests and Confidence Intervals , 1985 .

[29]  Acheson J. Duncan,et al.  The Economic Design of X Charts Used to Maintain Current Control of a Process , 1956 .

[30]  J. Macgregor,et al.  The exponentially weighted moving variance , 1993 .

[31]  R Reynolds Marion,et al.  Optimal variable sampling interval control charts , 1989 .

[32]  David G. Luenberger,et al.  Linear and Nonlinear Programming: Second Edition , 2003 .

[33]  York Marcel Dekker The State of Statistical Process Control as We Proceed into the 21st Century , 2000 .

[34]  Douglas C. Montgomery,et al.  Statistically constrained economic design of the EWMA control chart , 1995 .

[35]  T. Lai Sequential changepoint detection in quality control and dynamical systems , 1995 .

[36]  George Tagaras A Survey of Recent Developments in the Design of Adaptive Control Charts , 1998 .

[37]  Douglas C. Montgomery,et al.  The Economic Design of Control Charts: A Review and Literature Survey , 1980 .

[38]  F. Gan Joint monitoring of process mean and variance using exponentially weighted moving average control charts , 1995 .

[39]  Marion R. Reynolds,et al.  Monitoring the Process Mean and Variance Using Individual Observations and Variable Sampling Intervals , 2001 .

[40]  Marion R. Reynolds,et al.  Individuals control schemes for monitoring the mean and variance of processes subject to drifts , 2001 .

[41]  Rickie J. Domangue,et al.  Some omnibus exponentially weighted moving average statistical process monitoring schemes , 1991 .

[42]  J. Bert Keats,et al.  Economic Modeling for Statistical Process Control , 1997 .

[43]  Marion R. Reynolds,et al.  Control charts applying a general sequential test at each sampling point , 1996 .

[44]  Douglas C. Montgomery,et al.  Economic-statistical design of an adaptive chart , 1997 .

[45]  S. Crowder A simple method for studying run-length distribution of exponentially weighted moving average charts , 1987 .

[46]  Marion R. Reynolds,et al.  Should Observations Be Grouped for Effective Process Monitoring? , 2004 .

[47]  António Pacheco,et al.  On the performance of combined EWMA schemes for μ and σ: a markovian approach , 2000 .

[48]  George C. Runger,et al.  Steady-state-optimal adaptive control charts based on variable sampling intervals , 2001 .

[49]  Robert Hooke,et al.  `` Direct Search'' Solution of Numerical and Statistical Problems , 1961, JACM.

[50]  William H. Woodall,et al.  Ch. 13. Control chart schemes for monitoring the mean and variance of processes subject to sustained shifts and drifts , 2003 .

[51]  Antonio Fernando Branco Costa,et al.  Economic design of X charts with variable parameters: The Markov chain approach , 2001 .

[52]  Lonnie C. Vance,et al.  The Economic Design of Control Charts: A Unified Approach , 1986 .

[53]  Raid W. Amin,et al.  An EWMA Quality Control Procedure for Jointly Monitoring the Mean and Variance , 1993 .

[54]  Kenneth E. Case,et al.  Economic Design of Control Charts: A Literature Review for 1981–1991 , 1994 .

[55]  S. Albin,et al.  An X and EWMA chart for individual observations , 1997 .

[56]  E. Lehmann Testing Statistical Hypotheses , 1960 .

[57]  Marion R. Reynolds,et al.  The SPRT chart for monitoring a proportion , 1998 .