Chapter 12 Quality Control 489
Controlled Variation
The reduction of variation in any process is benefi cial. However, you can
never eliminate all variation, even in the simplest process, because there
are bound to be many small, unobservable, chance effects that infl uence
the process outcome. Variation of this kind is called controlled variation
and is analogous to the random-error effects in the ANOVA and regres-
sion models you studied earlier. As in those statistical models, many in-
dividually insignifi cant random factors interact to have some net effect on
the process output. In quality-control terminology, this random variation
is said to be “in control,” not because the process operator is able to con-
trol the factors absolutely, but rather because the variation is the result of
normal disturbances, called common causes, within the process. This type
of variation can be predicted. In other words, given the limitations of the
process, each of these common causes is controlled to the greatest extent
possible.
Because controlled variation is the result of small variations in the nor-
mally functioning process, it cannot be reduced unless the entire process
is redesigned. Furthermore, any attempts to reduce the controlled variation
without redesigning the process will create more, not less, variation in the
process. Endeavoring to reduce controlled variation is called tampering; this
increases costs and must be avoided. Tampering might occur, for instance,
when operators adjust machinery in response to normal variations in the
production process. Because normal variations will always occur, adjust-
ing the machine is more likely to harm the process, actually increasing the
variation in the process, than to help it.
Uncontrolled Variation
The other type of variation that can occur within a process is called uncon-
trolled variation. Uncontrolled variation is due to special causes, which are
sources of variation that arise sporadically and for reasons outside the nor-
mally functioning process. Variation induced by a special cause is usually
signifi cant in magnitude and occurs only occasionally. Examples of special
causes include differences between machines, different skill or concentra-
tion levels of workers, changes in atmospheric conditions, and variation in
the quality of inputs.
Unlike controlled variation, uncontrolled variation can be reduced by
eliminating its special cause. The failure to bring uncontrolled variation
into control is costly.
SPC is a methodology for distinguishing whether variation is controlled
or uncontrolled. If variation is controlled, then only improvements in the
process itself can reduce it. If variation is uncontrolled, then further analy-
sis is needed to identify and eliminate the special cause.
Table 12-1 summarizes the two types of variation studied in SPC.
