Plots p or np charts for binomial testing for defective items (A.F. Kane & R.W. Payne).
Options
PRINT = string token |
What to print (warnings); default * i.e. nothing |
---|---|
PLOT = string token |
Type of chart to plot (p , np ); default p |
METHOD = string token |
Method to use to obtain the control limits (complementaryloglog , given , logit , probit , untransformed ); default untr |
TOLERANCEMULTIPLIER = scalar |
Multiplier to use to test whether to use mean sample size for control limits; default 1 |
WINDOW = scalar |
Which high-resolution graphics window to use; default 3 |
SCREEN = string token |
Whether or not to clear the graphics screen before plotting (clear , keep ); default clea |
Parameters
NDEFECTIVE = variates |
Number of defective items |
---|---|
NTESTED = scalars or variates |
Number of items tested |
CENTRELINE = scalars |
Sets or saves centre line |
LOWERCONTROLLIMIT = scalars or variates |
Sets or saves lower control limit |
UPPERCONTROLLIMIT = scalars or variates |
Sets or saves upper control limit |
Description
The p and np charts are used in statistical process control to evaluate testing schemes in which successive batches of items are classified as either good or defective. The number of defective items in each batch is specified, in a variate, by the NDEFECTIVE
parameter. The NTESTED
parameter supplies the number of items in each batch – this can be a scalar if the batches are all of the same size, otherwise it is a variate.
The PLOT
option controls the type of chart: the p chart plots the proportion of defective items while the np chart (which is most useful each batch of items has the same total size) plots the number of defective items.
The charts contain not only the observed numbers or proportions but also a centre line (indicating a target value) and lines showing upper and lower control limits (bounding the zone outside which the process is said to be out of control). The control limits relevant to each batch will depend on the batch sizes. The TOLERANCE
option determines whether an average total size is used if the individual totals are not exactly equal: this will happen unless either
MIN(NTESTED) * TOLERANCE < MEAN(TESTED)
or
MEAN(TESTED) * TOLERANCE < MAX(NTESTED)
The METHOD
option specifies how the various lines are to be defined, with the following settings. They are defined below for a p chart. For an np chart, the values are simple multiplied by the batch size(s).
untransformed |
this is the default setting, and requests the method conventionally used in SPC. The centre line is at |
---|---|
p = (total number defective) / (total number tested) | |
and the limits are at p + 3 × √(p / (1-p)) | |
given |
specifies that the values are supplied by the CENTRELINE , LOWERCONTROLLIMIT and UPPERCONTROLLIMIT parameters. |
logit |
obtains the values as the batch mean +/- three times its standard error as estimated on the logit scale of a generalized linear model (with binomial distribution). |
probit |
obtains the values as the batch mean +/- three times its standard error as estimated on the probit scale of a generalized linear model |
complementaryloglog |
obtains the values as the batch mean +/- three times its standard error as estimated on the complementary-log-log scale of a generalized linear model. |
For settings of METHOD
other than given
, the CENTRELINE
, LOWERCONTROLLIMIT
and UPPERCONTROLLIMIT
parameters can be used to save the centre line and limits.
You can set PRINT=warnings
to list any batches that are outside the control limits; by default these are suppressed. As usual, the WINDOW
option specifies which high-resolution graphics window to use for the plot, and the SCREEN
option controls whether or not to clear the graphics screen before plotting.
Options: PRINT
, PLOT
, METHOD
, TOLERANCEMULTIPLIER
, WINDOW
, SCREEN
.
Parameters: NDEFECTIVE
, NTESTED
, CENTRELINE
, LOWERCONTROLLIMIT
, UPPERCONTROLLIMIT
.
Method
For further information about the standard SPC methods see for example Chapter 5 of Montgomery (1985). Section 3.5 of the Guide to the Genstat Command Language, Part 2 Statistics gives more details about generalized linear models.
Action with RESTRICT
Any restrictions are ignored.
Reference
Montgomery, D.C. (1985). Introduction to Statistical Process Control. Wiley, New York.
See also
Procedures: SPCAPABILITY
, SPCCHART
, SPCUSUM
, SPEWMA
, SPSHEWHART
.
Commands for: Six sigma.
Example
CAPTION 'SPPCHART example',\ !t('Data from Montgomery (1985), Introduction to',\ 'Statistical Process Control, page 152.');\ STYLE=meta,plain VARIATE [VALUES=12,15,8,10,4,7,16,9,14,10,5,6,17,12,22,\ 8,10,5,13,11,20,18,24,15,9,12,7,13,9,6] Cans SPPCHART [PRINT=warnings] Cans; NTESTED=50