Operations and Supply Chain Management The Core

QUALITY MANAGEMENT AND SIX SIGMA chapter 10 317
for a company that is making thousands of parts each hour, testing each critical dimension
of each part made can be very expensive. For the bearing, there could easily be 10 or
more additional critical dimensions in addition to the diameter. These would all need to
be checked. Using a 100 percent testing approach, the company would spend more time
testing than it takes to actually make the part! This is why a company uses small samples
to periodically check that the process is in statistical control. We discuss exactly how this
statistical sampling works later in the chapter.
We say that a process is capable when the mean and standard deviation of the process
are operating such that the upper and lower control limits are acceptable relative to the
upper and lower specification limits. Consider diagram A in Exhibit 10.9. This represents
the distribution of the bearing diameter dimension in our original process. The average or
mean value is 1.250 and the lower and upper design specifications are 1.245 and 1.255,
respectively. Process control limits are plus and minus three standard deviations (1.244 and
1.256). Notice that there is a probability (the yellow areas) of producing defective parts.
If the process can be improved by reducing the standard deviation associated with the
bearing diameter, the probability of producing defective parts can be reduced. Diagram
B in Exhibit 10.9 shows a new process where the standard deviation has been reduced to
0.00083 (the area outlined in green). Even though we cannot see it in the diagram, there is
some probability that a defect could be produced by this new process, but that probability
is very, very small.
Process Capability
exhibit 10.9
Diagram A
1.244 1.250
1.256
Lower spec
limit
1.245
1.255
Upper spec
limit
1.244
1.250
1.256
Diagram B
1.248 1.250 1.252
1.245
Improved
process
1.255
Original
process
1.244 1.250
1.256