Example 41.2: Specifying a Known Expected Number of Nonconformities

UCHART Statement

Example 41.2: Specifying a Known Expected Number of Nonconformities

See SHWUEX2 in the SAS/QC Sample Library

This example illustrates how you can create a u chart based on a known (standard) value u₀ for the expected number of nonconformities per unit.

A u chart is used to monitor the number of defects per square meter of fabric. The defect counts are provided as values of the variable DEFECTS in the data set FABRIC (see "Creating u Charts from Defect Count Data" ). Based on previous testing, it is known that u₀ = 0.325. The following statements create a u chart with control limits derived from this value:

   title  'u Chart for Fabric Defects per Square Meter';
   title2 'Using Data in FABRIC and Standard Value U0=.325';
   symbol v=dot c=vig;
   proc shewhart data=fabric;
      uchart defects*roll / subgroupn = 30
                            u0        = 0.325
                            usymbol   = u0
                            cframe    = steel
                            cinfill   = ligr
                            coutfill  = yellow
                            cconnect  = vig;
   run;

The chart is shown in Output 41.2.1. The U0= option specifies u₀, and the USYMBOL= option requests a label for the central line indicating that the line represents a standard value.

Output 41.2.1: A u Chart with Standard Value u₀

Since all the points lie within the control limits, the process is in statistical control.

Alternatively, you can specify u₀ as the value of the variable _U_ in a LIMITS= data set, as follows:

   data tlimits;
      length _subgrp_ _var_ _type_ $8;
      _u_      = .325;
      _limitn_ = 30;
      _type_   = 'STANDARD';
      _subgrp_ = 'roll';
      _var_    = 'defects';

   proc shewhart data=fabric limits=tlimits;
      uchart defects*roll / subgroupn=30
                            usymbol  =u0;
   run;

The chart produced by these statements is identical to the one in Output 41.2.1. For further details, see "LIMITS= Data Set" .

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