CHAPTER 27 • Statistical Process Control

27-40 CHAPTER 27 • Statistical Process Control
TABLE 27.8 Proportions of workers absent during four weeks
M T W Th F M T W Th F
Workers absent 129 121 117 109 122 119 103 103 89 105
Proportion pˆ 0.131 0.123 0.119 0.110 0.124 0.121 0.104 0.104 0.090 0.106
M T W Th F M T W Th F
Workers absent 99 92 83 92 92 115 101 106 83 98
Proportion pˆ 0.100 0.093 0.084 0.093 0.093 0.117 0.102 0.107 0.084 0.099
the chart based on the new data. If the rate does not decline further (or even rises
again as the effect of your actions wears off), you will consider further changes.
Example 27.13 is a bit oversimplified. The number of workers available did
not remain fixed at 987 each day. Hirings, resignations, and planned vacations
change the number a bit from day to day. The control limits for a day’s pˆ depend
on n, the number of workers that day. If n varies, the control limits will move in
and out from day to day. Software will do the extra arithmetic needed for a different
n each day, but as long as the count of workers remains close to 987, the
greater detail will not change your conclusion.
A single p chart for all workers is not the only, or even the best, choice in this
setting. Because of the important role of supervisors in absenteeism, it would be
wise to also keep separate p charts for the workers under each supervisor. These
charts may show that you must reassign some supervisors.
0.18
0.16
UCL
Proportion absent
0.14
0.12
0.10
LCL
x
x
x
x
x
0.08
x
x
0.06
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Day
FIGURE 27.16
p chart for daily proportion of workers absent over a four-week period, for Example 27.13. The
lack of control shows an improvement (decrease) in absenteeism. Update the chart to continue
monitoring the process.