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aren’t suitable for every environment or job. OEMs have
zeroed in on activities where driverless trucks can improve
productivity and accuracy, reduce injuries and damage, and
handle repetitive, non-value-adding tasks. These include:
; Horizontal transport, with or without loads, between
specified points, with no other action required
; Pallet picking and putaway
; Case picking and putaway (typically using semi-automated trucks that users control remotely as they pick orders).
Some end-users are focusing on horizontal transport,
says Micheletto of Hyster. Examples he’s seen include delivering pallets to manufacturing areas or storage, moving
loads from storage to shipping, and transporting loads from
conveyors and automated storage and retrieval systems
(AS/RS) to a stretch-wrap station.
According to Raymond’s Rosenberger, there’s more
demand for automation in receiving and replenishment,
which largely involve routine processes and thus are well
suited to automation, than there is in picking, a high-speed
activity that requires flexibility. He’s also seeing adoption
at combination manufacturing/warehouse facilities, where
product comes off a production line in batches and moves
into an attached warehouse.
Consumer packaged goods and food and beverage manu-
facturing and distribution operations have been the biggest
look at scaling up, while a few customer locations have
done “full-scale, complete, almost ‘lights out’ implementa-
tions,” he says. Those operations continue to manually load
and unload trucks, but robotic forklifts handle everything
inside the DC. A small staff supports the robotics system
and resolves any problems. Facilities that are running on
a completely robotic basis, he notes, tend to work 24/5 or
24/7, with more than two shifts.
POINTS TO PONDER
Thinking about giving driverless forklifts a try? It’s a big
leap for most operations, with many complex considerations to keep in mind. Here are some of the big ones:
; Prioritizing the steps. One piece of advice that came up
over and over was this: “Don’t just automate your current
process. Optimize first, then automate.” In Rosenberger’s
view, this may be the single most important bit of advice.
He strongly urges those planning to introduce driverless
forklifts to “connect, optimize, and only then automate—in
that order.” By “connect,” he means using telematics and
fleet management systems to get accurate baseline data
about forklift activity, which can then be used to improve
current operations. That step will help users make significant headway on the problems they want automation to
solve, freeing up money to spend on the project while helping identify where automation is genuinely needed and can
generate an ROI (return on investment), he says.
; Cost justification. ROIs of two years or even less
are achievable, according to some proponents. But other
Driverless forklifts and the dock of the future
It may not be long before driverless forklifts are common
and even ubiquitous. How will they interact with loading and receiving docks?
While the day may come when automated forklifts
can load and unload trucks on their own, today’s models
still lack the necessary sensing and recognition capabilities, according to one expert. In order to go it alone,
robotic forklifts will need the ability to recognize the
state of the dock, such as the presence of a trailer and
the dock’s position, as well as the trailer’s destination or
origin, in order to connect goods with specific inbound
and outbound vehicles, says Michael Eastabrook, president, loading dock products for Entrematic, the parent
of Serco and Kelley dock systems.
The first step toward making that possible will be to
deploy the necessary architecture for connectivity and
the exchange of data between the forklift and the dock
equipment—something the machines used to load or
unload trailers today usually lack, Eastabrook says. Next,
forklifts and dock equipment will need to have sensors
that can communicate their status.
Eastabrook believes that as full automation takes
hold, more advanced sensing, including detection of
anomalies, will be necessary. But the variability around
a loading dock—in truck heights and positioning, and
trailer and pallet configurations, for example—will
delay full automation for five to 10 years, he predicts.
Addressing such complexities will probably require artificial intelligence (AI) or machine learning, he adds.
But until then? Eastabrook expects the loading process
will be collaborative, with a human working with multiple pieces of automated equipment. He foresees cloud-based loading dock software coordinating information
among a loading dock, a warehouse management system
(WMS) or enterprise resource planning (ERP) system, and
a human dock attendant. The loading dock application
would contain data on a dock position’s status, such as
time and presence at the dock, state of the equipment,
identification of the trailer, and so forth. Based on that
data, a WMS would dispatch an automated forklift to
the dock position, where it would collaborate with the
human operator for loading or unloading. This approach,
he says, would create a reasonable ROI for early adopters
and generate momentum across the industry.
