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The Relationship Between Cycle Time
and Capacity
In the (imaginary) novariability
case, cycle time remains constant as
start rate is increased, up to the
maximum system capacity. At that point,
if start rate is increased further, cycle
time increases linearly. This is shown in
the following chart.
In a real fab, with variability, cycle
time tends to increase with start rate
(or throughput rate  the two measures
are directly related by line yield).
Exactly how much the cycle time increases
will depend on the amount of variability
in the system. In most fabs, once the
system is loaded above approximately 85%,
cycle time starts to increase rapidly.
This is sometimes called the
“hockey stick effect,” as
illustrated below.
Cycle time limits the effective
capacity of a wafer fab. Even the low
variability system cannot be run at 100%
of the maximum throughput, because cycle
time increases rapidly to unacceptable
levels. In fact, the limiting case for
systems with any variability is that as
the factory loading approaches 100%, the
cycle time approaches infinity. In the
real world, factory planners account for
this by including “catchup
capacity” in their plans. That is,
they typically plan for about 15% idle
time on all of their tool groups. This
keeps factories out of the steep portion
of the curve shown above.
We have worked on projects in which
the factory performance measure used was
cycletimeconstrained capacity. This
is defined as the maximum capacity at
which the factory can achieve a given
average cycle time, expressed as a
multiple of raw process time. The
multiple of raw process time is usually
called an Xfactor. So, the shorthand
term for three times raw process time is
3X. In the chart above, the 3X
cycletimeconstrained capacity (or 3X
capacity) for the low variability system
is approximately 80% of the maximum
theoretical capacity of the system. For
the highest variability factory, the 3X
capacity is only about 45% of the maximum
theoretical capacity.
The maximum theoretical capacity of a
factory is the start rate that drives the
bottleneck
to 100% loading. The only way to increase
it is to add equipment, or make process
changes that reduce the load on the
bottleneck. However, as the example chart
shows, cycletimeconstrained capacity
can sometimes be dramatically improved by
reducing variability in the factory. This
is one of the key strategies used for
lowcost cycle time reduction
efforts.
