Note: See Standard Values for Moving Average Charts in the SAS/QC Sample Library.
By default, the MACHART statement estimates the process mean () and standard deviation () from the data. This is illustrated in Getting Started: MACHART Statement. However, there are applications in which standard values ( and ) are available based, for instance, on previous experience or extensive sampling. You can specify these values with the MU0= and SIGMA0= options.
For example, suppose it is known that the metal clip manufacturing process (introduced in Creating Moving Average Charts from Raw Data) has a mean of 15 and standard deviation of 0.2. The following statements specify these standard values:
ods graphics on; title 'Specifying Standard Process Mean and Standard Deviation'; proc macontrol data=Clips1; machart Gap*Day / odstitle = title mu0 = 15 sigma0 = 0.2 span = 4 xsymbol = mu0 markers; run;
The XSYMBOL= option specifies the label for the central line. The resulting chart is shown in Output 9.6.1.
The central line and control limits are determined using and (see the equations in Table 9.9). Output 9.6.1 indicates that the process is out-of-control since the moving averages for Day
=17, Day
=19, and Day
=20 lie below the lower control limit.
You can also specify and with the variables _MEAN_
and _STDDEV_
in a LIMITS= data set, as illustrated by the following statements:
data cliplim; length _var_ _subgrp_ _type_ $8; _var_ = 'Gap'; _subgrp_ = 'Day'; _type_ = 'STANDARD'; _limitn_ = 5; _mean_ = 15; _stddev_ = 0.2; _span_ = 4; run; proc macontrol data=Clips1 limits=Cliplim; machart Gap*Day / xsymbol=mu0 odstitle = title markers; run;
The variable _SPAN_
is required, and its value provides the number of terms in the moving average. The variables _VAR_
and _SUBGRP_
are also required, and their values must match the process and subgroup-variable, respectively, specified in the MACHART statement. The bookkeeping variable _TYPE_
is not required, but it is recommended to indicate that the variables _MEAN_
and _STDDEV_
provide standard values rather than estimated values.
The resulting chart (not shown here) is identical to the one shown in Output 9.6.1.