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Case Study: Reduced electricity use reduces production cost, lowers carbon footprint
 
 
Figures 2 & 3. The box plots, in general, reveal the upper limit of the data (top end of the whisker), lower limit of the data (bottom end of the whisker), a quartile box (show-
ing the spread of the data observed), the mean of the data (dot) and the median of the data (horizontal line within the quartile box).
recipe (21% for Assembly 1 and Mike Payne is general manager of high-mix,
17.7% for Assembly 2), when low-volume electronics manufacturing services
compared to the original oven provider Delta Group Electronics. Based in
recipe. This possibly indicates
Albuquerque, New Mexico, Delta Group also
that the oven performance
has assembly operations in Florida, Texas and
was more uniform with the
Arkansas.
optimized profile.
4. The upper and lower limits of
the whiskers for the optimized
oven recipe, for both Assem-
bly 1 and Assembly 2, show a
more balanced (tighter) power
Figure 4. Delta Group Electronics focuses on reduc-
consumption pattern for the
ing cost and carbon footprint, as evidenced by the
oven when compared to the
wind turbine installed next to its factory.
original oven recipe. This
balanced power consumption
be as good or better than before. Once
pattern could lead to extended
the production resumed, we recorded the
life of the heater elements in
readings from the power meter again. We
the oven.
repeated the above procedure for a differ-
ent PCB assembly (Assembly 2).
conclusion
Introduction of a simple process optimiza-
electricity use analysis tion software resulted in an immediate
Power consumption (kilowatt hour or reduction of the reflow oven electricity use
KWH) data was collected for all batches of of 13.6% and 15.8% respectively for our
PCB assemblies that were run through the two PCB assemblies included in the test.
process. Figures 2 and 3 show box plots of This gain did not come at the expense of
the power consumption data and compare either productivity or quality. Actually, the
the original recipe with the optimized profile was positioned deeper in spec dur-
recipe. ing this project, indicating that the process
The following are key observations became more robust.
from the box plots of the run data: There is no such thing as a “free
lunch”—after all we had to pay for the
1. The optimized oven recipe
marginal cost of the process optimization
showed a 15.8% reduction
software—but this does come very close.
in power consumption for
Prior to KIC’s new approach, no one had
Assembly 1 and a 13.6% reduc-
been thinking about electricity consump-
tion in power consumption for
tion when selecting an appropriate reflow
Assembly 2.
oven recipe, and the odds were that the
2. No outliers were observed in
oven would be running too hot in one or
the data sets for both assem-
more zones. The KIC Navigator Power uses
blies, indicating no abnormal
a scientific method to optimize electric-
observations during the runs.
ity use and, hence, takes any slack out of
3. For both assemblies, the spread
the oven recipe. That optimized equation
in the observed data was
converts directly to energy savings.
reduced for the optimized oven
30 – Global SMT & Packaging – October 2009 www.globalsmt.net
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