Macros for Quality Control and Designed Experiments

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  1. ANOM for 2 Level, 2 Factor Design
  2. Bland-Altman Plot
  3. Blank Xbar or Individuals Control Chart
  4. Box-Cox Transformation for Regression and Response Surface Models
  5. Control Charts from Summary Statistics - New Version
  6. Detecting sustained shift sizes using a CUSUM
  7. Gage R&R on multiple measurement columns
  8. Levey-Jennings Control Chart
  9. Non-Parametric Capability Analysis
  10. Path of Steepest Ascent
  11. Random Data for a Control Chart
  12. Select a D-optimal Design from a Factorial or a Central Composite Design
  13. Simplex Method for Linear Programming Problems
  14. Standardized Control Chart for Fraction of Nonconformities
  15. Tolerance Intervals
  16. Variance Dispersion Graphs

ANOM for 2 Level, 2 Factor Design
This macro creates an ANOM chart for a 2 factor, 2 level factorial design. The interaction between the 2 factors is displayed on the same scale as the main effects. The default decision limits are calculated at alpha = .05. Written by Cathy Akritas Back to Top
Bland-Altman Plot
This macro produces a Bland-Altman plot of paired data. The differences and averages of the data pairs are plotted with the center line and the limits of agreement (LOA). Plotted points beyond the LOA are flagged in red. Written by Eli Walters Back to Top
  • Minitab 15 and 16
  • Code
Blank Xbar or Individuals Control Chart
This macro creates a blank Xbar or Individuals control chart where the control limits are based on historical information. There are two options for obtaining the control limits: Calculate the control limits based on a historical mean and a historical sigma or directly input the values for the historical upper and lower control limits. Written by Cathy Akritas Back to Top
  • Minitab 15 and 16
  • Code
Box-Cox Transformation for Regression and Response Surface Models
This macro determines the likelihood estimate of the Box-Cox power transformation parameter in regression and response surface modeling applications. A plot of the log-likelihood function over a range of parameter values is displayed showing the likelihood estimate and an approximate 95% confidence interval for the parameter. Also displayed is a plot of the values of the PRESS statistic transformed back to the original response scale over the 95% confidence interval. Optionally, the user may choose to specify the range of parameter values in the plot of PRESS, display an index plot due to Cook and Wang (1983) showing the influence of individual cases on the likelihood estimate, and store all computed results.
Some of this functionality has been added to Minitab 16 as part of the analysis at Stat > Regression > General Regression. Written by Steve Orlich and Mike Delozier Back to Top
Control Charts from Summary Statistics - New Version
This macro uses summary data to make an Xbar chart and either an R chart or an S chart. The R/S choice is determined by whether ranges or standard deviations are entered. These three subcommands are required: MEAN, SIZE and either STDEV or RANGE. The arguments to MEAN, SIZE, STDEV and RANGE can either be a column containing one value for each subgroup or a single constant that should be used for all subgroups. Legal values for TEST are 1, 2, 3, 4, 5, 6, 7, 8. An historical grouping column can be entered using the HPROCESS subcommand. Written by Andy Haines Back to Top
  • Minitab 15 and 16
  • Code
Detecting sustained shift sizes using a CUSUM
This macro can be used along with a CUSUM chart to estimate the size of a small, sustained shift in a process mean. This shift size is also expressed in terms of the within-subgroup sigma estimate. Written by Keith Bower Back to Top
Gage R&R on multiple measurement columns
This macro performs a Gage R&R analysis on multiple measurement columns, using the same part and operator columnms. Tolerances can be specified for each measurement column. Written by Veronica Bubb Back to Top
  • Minitab 15 and 16
  • Code
Levey-Jennings Control Chart
This macro generates a Levey-Jennings control chart. You can choose to label the x-axis with values from a column, which would typically contain dates. Written by Kelly Aubuchon Back to Top
  • Minitab 15 and 16
  • Code
Non-Parametric Capability Analysis
This macro calculates capability indices (Cnpk) using the empirical percentile method as described in the reference

    D. W. McCormack Jr., Ian R. Harris, Arnon M. Hurwitz, and Patrick D. Spagon 2000). "Capability Indices for Non-Normal Data," Quality Engineering, 12 (4), 489-495.

      There are other non-parametric capability analysis methods available. Only the empirical percentile method is presented here. Written by Cathy Akritas Back to Top
      • Minitab 15 and 16
      • Code
      Path of Steepest Ascent
      This macro computes a specified number of runs along the path of steepest ascent or descent. The macro is flexible enough to accomodate for different base factors, step sizes and number of runs. Written by Daniel Griffith and Eduardo Santiago Back to Top
      Random Data for a Control Chart
      This macro generates random data for a control chart. Written by Isaac Newton Back to Top
      • Minitab 15 and 16
      • Code
      Select a D-optimal Design from a Factorial or a Central Composite Design
      This macro selects a D-optimal design from either a 2-level factorial design or a central composite design as the base design. This D-optimal design will be able to estimate all main effects, all two-way interactions and, if a central composite base design is specified, all quadratics. Written by Doug Gorman and Jim Colton Back to Top
      • Minitab 15 and 16
      • Code
      Simplex Method for Linear Programming Problems
      This macro finds the optimal solution of a linear program, using the Revised Form of the Simplex. Linear programming (LP) deals with an objective function with only linear terms, and assumes only linear constraints exist. Written by Eduardo Santiago Back to Top
      Standardized Control Chart for Fraction of Nonconformities
      This macro creates a standardized control chart for the fraction of non-conforming units. Written by Cathy Akritas Back to Top
      • Minitab 15 and 16
      • Code
      Tolerance Intervals
      This macro calculates a (1-alpha)100% tolerance interval which covers at least p*100% of the population (distribution). This functionality is new in Minitab 16 and can be found at Stat > Quality Tools > Tolerance Intervals. Written by Cathy Akritas Back to Top
      Variance Dispersion Graphs
      This macro calculates the scaled prediction variance for up to five design matrices given a specific model. This will allow you to compare designs in coded units and their performance prior to collecting any data for a DOE. Written by Eduardo Santiago Back to Top

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