The SHEWHART Procedure |
[See SHWNP2 in the SAS/QC Sample Library]This example shows how you can apply tests for special causes to make charts more sensitive to special causes of variation. The following statements create a SAS data set named Circuit3, which contains the number of failing circuits for 20 batches from the circuit manufacturing process introduced in the section Creating np Charts from Count Data:
data Circuit3; input Batch Fail @@; datalines; 1 12 2 21 3 16 4 9 5 3 6 4 7 6 8 9 9 11 10 13 11 12 12 7 13 2 14 14 15 9 16 8 17 14 18 10 19 11 20 9 ; run;
The following statements create the chart, apply several tests to the chart, and tabulate the results:
ods graphics on; title1'np Chart for the Number of Failing Circuits'; title2 'Tests=1 to 4'; proc shewhart data=Circuit3; npchart Fail*Batch / subgroupn = 500 tests=1 to 4 table tabletest tablelegend zones zonelabels odstitle = title odstitle2 = title2; run;
The chart is shown in Output 13.18.1, and the printed output is shown in Output 13.18.2. The TESTS= option requests Tests 1, 2, 3, and 4, which are described in Tests for Special Causes The TABLETESTS option requests a table of counts of nonconforming items and control limits, with a column indicating which subgroups tested positive for special causes. The TABLELEGEND option adds a legend describing the tests. The ZONELABELS option displays zone lines and zone labels on the chart. The zones are used to define the tests.
Output 13.18.1 and Output 13.18.2 indicate that Test 1 is positive at batch 2 and Test 3 is positive at batch 10.
np Chart Summary for Fail | |||||
---|---|---|---|---|---|
Batch | Subgroup Sample Size |
3 Sigma Limits with n=500 for Number | Special Tests Signaled |
||
Lower Limit |
Subgroup Number |
Upper Limit |
|||
1 | 500 | 0.60851449 | 12.000000 | 19.391486 | |
2 | 500 | 0.60851449 | 21.000000 | 19.391486 | 1 |
3 | 500 | 0.60851449 | 16.000000 | 19.391486 | |
4 | 500 | 0.60851449 | 9.000000 | 19.391486 | |
5 | 500 | 0.60851449 | 3.000000 | 19.391486 | |
6 | 500 | 0.60851449 | 4.000000 | 19.391486 | |
7 | 500 | 0.60851449 | 6.000000 | 19.391486 | |
8 | 500 | 0.60851449 | 9.000000 | 19.391486 | |
9 | 500 | 0.60851449 | 11.000000 | 19.391486 | |
10 | 500 | 0.60851449 | 13.000000 | 19.391486 | 3 |
11 | 500 | 0.60851449 | 12.000000 | 19.391486 | |
12 | 500 | 0.60851449 | 7.000000 | 19.391486 | |
13 | 500 | 0.60851449 | 2.000000 | 19.391486 | |
14 | 500 | 0.60851449 | 14.000000 | 19.391486 | |
15 | 500 | 0.60851449 | 9.000000 | 19.391486 | |
16 | 500 | 0.60851449 | 8.000000 | 19.391486 | |
17 | 500 | 0.60851449 | 14.000000 | 19.391486 | |
18 | 500 | 0.60851449 | 10.000000 | 19.391486 | |
19 | 500 | 0.60851449 | 11.000000 | 19.391486 | |
20 | 500 | 0.60851449 | 9.000000 | 19.391486 |
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