Page 212 - DMGT524_TOTAL_QUALITY_MANAGEMENT

Unit 14: Statistical Process Control

etc. Such forces determine whether a coin when tossed will end up, showing a head or tail when Notes
on the floor. Together, however, these “chances” form a unique, stable and describable
distribution. The behaviour of a process operating under such conditions is predictable (Figure
14.8).
Inherent variability may be reduced by changing the environment or the technology, but given
a set of operating condition; this variability can never be completely eliminated from a process.
Variability due to assignable causes, on the other hand, refers to the variation that can be linked
to specific or special causes that disturb a process. Examples are tool failure, power supply
interruption, process controller malfunction, adding wrong ingredients or wrong quantities,
switching a vendor, etc.
Assignable causes are fewer in number and are usually identifiable through investigation in the
shop floor or an examination of process logs. The effect (i.e., the variation in the process) caused
by an assignable factor, however, is usually large and detectable when compared with the
inherent variability-seen in the process. If the assignable causes are controlled properly, the
total process variability associated with them can be reduced and even eliminated. Still, the
effect of assignable causes cannot be described by a single distribution (Figure 14.9).
Figure 14.9: Both Common and Assignable Causes affecting the Process

Variability cannot be
predicted

Time

A capability study measures the inherent variability or the performance potential of a process
when no assignable causes are present (i.e. when the process is said to be in statistical control).
Since inherent variability can be described by a unique distribution, usually a normal distribution,
capability can be evaluated by utilizing the properties of this distribution. Recall that capability
is the proportion of routine process output that remains within product specs.
Even approximate capability calculations done using histograms enable manufacturers to take
a preventive approach to defects. This approach is in contrast with the traditional two-step
process: production personnel make the product while QC personnel inspect and screen out
products that do not meet specifications. Such QC is wasteful and expensive since it allows plant
resources including time and materials to be put into products that are not salable.
It is also unreliable since even 100 percent inspection would fail to catch all defective products.
SPC aims at correcting undesirable changes in the output of a process. Such changes may affect
the centering (or accuracy) of the process, or its variability (spread or precision). These effects
are graphically shown in Figure 14.10 (a) and Figure 14.10 (b).

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