Digitalization in today’s global economy
has become a necessity for modern
manufacturing facilities. When running
IIoT (industrial Internet of Things) applications,
most—if not all—data needs to be
collected, sorted, and analyzed in real time. To
move between the cloud and local devices, an
edge device is needed. These edge devices can
transmit data between protocols used by local
devices into the protocols used by the cloud.
Instead of directly sending data to an off-site
cloud to calculate analytics, edge devices can
provide local execution of data analysis with
low latency and a high level of determinism.
Data at the edge of the network can also
be aggregated and contextualized to send rich,
summary information directly to the cloud,
ultimately reducing cloud data storage costs.
Other edge computing benefits include condition-
based monitoring, which can help prevent
critical failures and downtime, as well as lower
parts inventory and maintenance costs.
Another advantage to many edge devices is
their use of the future-proof Linux operating
system. Linux has been around for more than
30 years, and its acceptance has been growing
exponentially. Used in most servers as well as
in many military applications, it is robust and
users can be confident that this open-source
platform will continue to be available. Not
having to update to a new platform every few
years makes Linux-based edge devices ideal for
innovative IIoT applications.
How to begin
using edge devices
The first step in using edge devices is to find
a business problem you are looking to solve.
Instead of looking at the entire scope of the
problem, try to break the issue down into
small, manageable sections. Once you have
done that, determine the priority of each—from highest to lowest.
The next step is to start collecting your plant
floor data using containerized applications to
analyze all the data. The benefit here is that
both the connected worker on the plant floor as
well as management can use the data to troubleshoot
problems at the manufacturing level as
they happen. It also helps off-site management
look at efficiency, logistics, and other data to
determine what is working, what areas need to
be looked at more closely, and formulate plans
for improvement on a long-term basis.
Depending on your industry, a good place
to start may be your asset management program.
If we look at this as an example, there
are many pieces of key data that can be analyzed
to help improve your company’s bottom
line. These may include power consumption,
vibration, bearing temperature, pressure, and
uptime. Using this information, patterns can
be recognized to determine causes of failure
and what can be done to avoid those failures
in the future. This can all done using edge
computers to track and store data for delivery
straight to the user when needed.
Wago’s edge approach
Wago combines the advantages of decentralized
cloud computing with local control networks
with our Edge Controller and Edge Computer.
The Edge Controller is used to collect
plant floor data information from industrial
fieldbuses. If the application calls for it, these
data can then be published directly to the cloud.
If not, the Edge Computer can take the Edge
Controller data, sort them and run analytics
locally before posting to the cloud for anyone
with proper access rights to see.
