A quality engineer for a wallpaper manufacturer wants to assess the stability of the printing process. Every hour, the engineer takes a sample of 100 feet of wallpaper and counts the number of printing defects, which include print smears, pattern distortions, and missing ink.

The engineer creates a C chart to monitor the number of defects.

  1. Open the sample data, WallpaperDefects.MTW.
  2. Choose Stat > Control Charts > Attributes Charts > C.
  3. In Variables, enter Defects.
  4. Click C Chart Options.
  5. On the Tests tab, select 1 point > K standard deviations from center line (Test 1) and K points in a row on same side of center line (Test 2).
    If you are not sure which tests apply in your specific situation, use Tests 1 and 2 when you first establish the control limits based on your data.
  6. Click OK in each dialog box.

Interpret the results

The average number of defects per sample is 36.68. Samples 12 and 13 failed Test 1 because they are outside the control limits. Thus, the process is out of control. The engineer should identify and correct any factors that contribute to the special-cause variation.

TEST 1. One point more than 3.00 standard deviations from center line. Test Failed at points: 12, 13 * WARNING * If graph is updated with new data, the results above may no longer be correct.
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