IFOY MGZN 2022 EN

IFOY
MGZN
VERDICT OF THE INNOVATION CHECK
With an estimated 500 million Euro pallets in circulation, not to mention
the other types, the savings potential through PACS is in the tens of
millions. But also companies that regularly use, for example, pallet cages
or small load carriers in their Intralogistics can use PACS. The application
range of the very reliable pallet classification system covers a broad
spectrum: retail, freight forwarding, automotive, mechanical engineering
and many other industries.
The detailed IFOY Innovation Check is available free of charge at www.ifoy.org.
Market relevance ++
Customer benefit ++
Degree of innovation +
Quality of implementation +
++ very good / + good / Ø balanced / - less / -- not available
PACS – this acronym stands for "Pallet
Classification System", i.e. a recognition
system that uses images to identify the type
of pallet. Four pictures of the pallet feet are
necessary for this, the fifth picture is taken
from above and shows what is on the pallet.
The whole thing is usually integrated into
the stationary conveyor system directly in
the goods receiving area; for the test setup
in Dortmund, a SICK employee still had to
manually feed the incoming pallet onto
the camera technology for demonstration
purposes. The aim is to provide companies
from industry and trade with full transparency
in goods receiving and consequently
in the flow of goods. Until now, employees
had to manually determine whether a pallet
was "good" or "bad" when it entered the
factory gate – an additional task that was
error-prone and resource-intensive. With
the PACS deep-learning pallet identification
system, customers are given the opportunity
to automate this process on the basis of a
modular system of hardware and software.
The financial aspect is the direct benefit
of this classification system. But there is
also an indirect effect, in fact several, that
make this solution so interesting. Because
incorrect pallets in the system also lead to
damage and expensive downtimes of the
conveyor system more often than average.
Another, even more valuable aspect is more
transparent processes by connecting the
goods to the load carrier. And finally, no
specialised personnel is required to operate
the PACS system. How does PACS work?
The hardware of the system consists of one
or more cameras with which the images
for the system are taken, a light barrier
arrangement for triggering and a controller
for processing the recorded data and for
executing the trained neural network. Even
without in-depth knowledge of programming
or machine learning, the software
tools SICK Appspace and dStudio enable
image recording, training, classification
and execution of the trained network.
Optionally, even further SICK sensors
can be integrated, which can take over
additional tasks. No programming knowledge
is required because the system
learns from concrete examples.
55