techwatch
A new way to spot problems
in the DC
FASTER, PLEASE, WITH NO MISTAKES. THAT’S WHAT
most logistics managers are being asked to do with respect to
the movement of products through their distribution centers.
Companies today want to push products through their facilities
more rapidly than ever without incurring higher costs or sacrificing accuracy.
That’s a tough assignment. But one way a logistics manager
can increase warehouse throughput is by deploying camera-based data capture in conjunction with analytics. Cameras
snap a series of pictures of packages moving down a conveyor.
Those images can be stored in a database and
then retrieved by software for analysis of the
operation. Companies marketing these types
of systems include Datalogic and Sick Inc.
Searching a database of images for opera-
tional insights is the latest example of “big
data” analysis applied to the supply chain.
All those pictures would be just a pile of big
data if it weren’t for the development of spe-
cial software that can filter and search
through the images. “You’re sifting through
millions and millions of images to look for
something significant,” explains Mark
Kremer, director of sales for retail logistics at
Sick. “You can use filtering rules to look for
a specific set of images.”
Analysis of the images can be used to pinpoint problems in
a distribution operation so that corrective action can be taken.
For example, the system might identify a too-large gap
between packages moving on a conveyor. By shrinking the gap
from, say, 16 inches to 12, a distribution center could speed up
the flow, increasing throughput.
Analysis of the images could also be useful in determining
whether suppliers are in “bar code compliance”—that is,
whether they’re meeting their customers’ specifications for how
and where bar codes should be placed on a package or case.
Instead of having a worker at a retailer’s DC conduct a manual
audit for bar code compliance, the software could perform the
audit by searching the database.
In addition, an image analysis could be used to determine the
root cause of “side by sides” in sortation systems. Side by sides
occur when a smaller package gets
squeezed up against another, larger pack-
age, resulting in the two products’ being
mistaken for a single unit. “The camera sys-
tem analyzes the image to determine when
there is a condition of multiple cartons
coming down the conveyor,” says John
Park, a marketing product manager with
Datalogic Automation. By reviewing
images of “side-by-side” packages, man-
agers can figure out
what’s going on and
make adjustments to cor-
rect the problem.
