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Specialized Control Charts 
The following example^{*} is adapted from an application in aircraft component manufacturing. A metal extrusion process is used to make three slightly different models of the same component. The three product types (labeled M1, M2, and M3) are produced in small quantities because the process is expensive and timeconsuming.
Figure 49.14 shows the structure of a SAS data set named OLD, which contains the diameter measurements for various short runs. Samples 1 to 30 are to be used to estimate the process standard deviation for the differences from nominal.
In short run applications involving many product types, it is common practice to maintain a database for the nominal values for the product types. Here, the nominal values are saved in a SAS data set named NOMVAL, which is listed in Figure 49.15.

To compute the differences from nominal, you must merge
the data with the nominal values. You can do this with
the following SAS statements. Note that an IN= variable
is used in the MERGE statement to allow for the fact
that NOMVAL includes nominal values for product types
that are not represented in OLD. Figure 49.16
lists the merged data set OLD.
proc sort data=old; by prodtype; data old; format diff 5.2 ; merge nomval old(in = a); by prodtype; if a; diff = diameter  nominal; proc sort data=old; by sample; run;

Assume that the variability in the process is constant across product types. To estimate the common process standard deviation , you first estimate for each product type based on the average of the moving ranges of the differences from nominal. You can do this in several steps, the first of which is to sort the data and compute the average moving range with the SHEWHART procedure.
proc sort data=old; by prodtype; proc shewhart data=old; irchart diff*sample / nochart outlimits=baselim; by prodtype; run;The purpose of this procedure step is simply to save the average moving range for each product type in the OUTLIMITS= data set BASELIM, which is listed in Figure 49.17 (note that PRODTYPE is specified as a BY variable).

To obtain a combined estimate of , you can use the MEANS procedure to average the average ranges in BASELIM and then divide by the unbiasing constant d_{2}.
proc means data=baselim noprint; var _r_; output out=difflim (keep=_r_) mean=_r_; data difflim; set difflim; drop _r_; length _var_ _subgrp_ $ 8; _var_ = 'diff'; _subgrp_ = 'sample'; _mean_ = 0.0; _stddev_ = _r_ / d2(2); _limitn_ = 2; _sigmas_ = 3; run;The data set DIFFLIM is structured for subsequent use by the SHEWHART procedure as an input LIMITS= data set. The variables in a LIMITS= data set provide precomputed control limits or as in this case  the parameters from which control limits are to be computed. These variables have reserved names that begin and end with the underscore character. Here, the variable _STDDEV_ saves the estimate of , and the variable _MEAN_ saves the mean of the differences from nominal. Recall that this mean is zero, since the nominal values are assumed to represent the process mean for each product type. The identifier variables _VAR_ and _SUBGRP_ record the names of the process and subgroup variables (these variables are critical in applications involving many product types). The variable _LIMITN_ is assigned a value of 2 to specify moving ranges of two consecutive measurements, and the variable _SIGMAS_ is assigned a value of 3 to specify limits. The data set DIFFLIM is listed in Figure 49.18.

Now that the control limit parameters are saved in DIFFLIM, diameters for an additional 30 parts (samples 31 to 60) are measured and saved in a SAS data set named NEW. You can construct short run control charts for this data by merging the measurements in NEW with the corresponding nominal values in NOMVAL, computing the differences from nominal, and then contructing the short run individual measurements and moving range charts.
proc sort data=new; by prodtype; data new; format diff 5.2 ; merge nomval new(in = a); by prodtype; if a; diff = diameter  nominal; label sample = 'Sample Number' prodtype = 'Model'; proc sort data=new; by sample;
symbol1 v=dot c=yellow; symbol2 v=plus c=red; symbol3 v=circle c=green; title 'Chart for Difference from Nominal'; proc shewhart data=new limits=difflim; irchart diff*sample=prodtype / split = '/' cframe = vigb cinfill = vlib cconnect = yellow; label diff = 'Difference/Moving Range'; run;The chart is displayed in Figure 49.19. Note that the product types are identified with symbol markers as requested by specifying PRODTYPE as a symbolvariable.
You can also identify the product types with a legend by specifying PRODTYPE as a _PHASE_ variable.
symbol v=dot c=yellow; title 'Chart for Difference from Nominal'; proc shewhart data=new (rename=(prodtype=_phase_)) limits=difflim; irchart diff*sample / readphases = all phaseref phasebreak phaselegend split = '/' cframe = vigb cconnect = yellow cinfill = vlib; label diff = 'Difference/Moving Range'; run;The display is shown in Figure 49.20. Note that the PHASEBREAK option is used to suppress the connection of adjacent points in different phases (product types).
In some applications, it may be useful to replace the moving range chart with a plot of the nominal values. You can do this with the TRENDVAR= option in the XCHART statement^{*} provided that you reset the value of _LIMITN_ to 1 to specify a subgroup sample of size one.
data difflim; set difflim; _var_ = 'diameter'; _limitn_ = 1;
symbol v=dot c=yellow; title 'Differences and Nominal Values'; proc shewhart data=new limits=difflim; xchart diameter*sample (prodtype) / nolimitslegend nolegend split = '/' blockpos = 3 blocklabtype = scaled blocklabelpos = left xsymbol = xbar trendvar = nominal cframe = vigb cinfill = vlib cconect = yellow; label diameter = 'Difference/Nominal' prodtype = 'Product'; run;
The display is shown in Figure 49.22. Note that you identify the product types by specifying PRODTYPE as a block variable enclosed in parentheses after the subgroup variable SAMPLE. The BLOCKLABTYPE= option specifies that values of the block variable are to be scaled (if necessary) to fit the space available in the block legend. The BLOCKLABELPOS= option specifies that the label of the block variable is to be displayed to the left of the block legend.
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