Page 190 - The Handbook for Quality Management a Complete Guide to Operational Excellence

176 P r o c e s s C o n t r o l Q u a n t i f y i n g P r o c e s s Va r i a t i o n 177

Figure 9.11 Non-normal control limits applied to data in Fig. 9.10 (Keller 2011b).

p charts can be applied to any variable where the appropriate perfor-
mance measure is a unit count. p charts answer the question: “Has a spe-
cial cause of variation caused the central tendency of this process to
produce an abnormally large or small number of defective units over the
time period observed?”

p Chart Control Limit Equations Like all control charts, p charts consist of
three guidelines: centerline, a lower control limit, and an upper con-
trol limit. The centerline is the average proportion defective and the
two control limits are set at plus and minus three standard deviations.
If the process is in statistical control, then virtually all proportions
should be between the control limits and they should fluctuate ran-
domly about the centerline.

subgroup defective count
p =
subgroup size

m
sum of subgroup defective counts
p =
o
sum of subgroup sizes
p − p)
1 (
LCL = p − 3
n
p − p)
1 (
UCL = p + 3
n

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