INTERNET OF THINGS HANDBOOK
The integration of data-driven predictive maintenance with
preventive maintenance also allows for just-in-time part
replacements, decreasing the need to purchase and warehouse
a full inventory of system-critical “just-in-case” parts.pneumatics operations in several ways,
including:Regulating upstream/downstream flow
Combining the traditional strengths of a
pneumatics system with IIoT-based technology
can maximize process control and monitoring,
particularly for upstream/downstream fl ow.
The result is enhanced OEE and lower total
cost of ownership (TCO).
Consider a plant using a system that
allows only fully open or fully closed positions
on pneumatically actuated gates on a hopper
or silo that dispenses bulk material for
packaging. Uneven product fl ow and traffi c
jams can inundate or starve downstream
processing stations. The inability to vary
the dispensing gates’ position based on
downstream demand creates ineffi ciencies
and bottlenecks throughout the plant. The
results range from damages to the bulk
material to overtime costs for personnel to
make up production quotas.
A retrofi t solution, without disturbing the
existing controller or its program, can addressthe issue at a fraction of the cost required for
new controller equipment or work process
modifi cations. An intelligent, IIoT-based,
closed-loop system, with appropriate sensors
on IIoT-enabled pneumatics components,
allows each gate’s position to vary from 0
to 100% of the opening — not just the two
positions of opened or closed. The fl exibility
results in much better fl ow control for bulk
material, without the need to change the
controller program.
By adding additional components, such
as an extremely precise pneumatic positioning
system for control and IIoT gateway to analyze
functionality, the system enables more effi cient
control of the bulk material, preventing
starvation of the packaging system downstream
as well as optimizing OEE. In addition, data
from the IIoT system can be leveraged for
additional system improvements. It could, for
example, measure valve life so the operator
understands whether a valve is performing
to specifi cation and, if necessary, change the
component during scheduled maintenance
while alleviating any unplanned downtime.As pneumatics technology becomes
more intelligent, additional data
points are being generated across the
production systems where they are
installed. Examples include information
such as diagnostics, usage statistic
and lifetime data. In addition, if all
the pneumatics components (along
with other intelligent machine drives,
devices and subsystems) are generating
megabytes of performance data,
there’s a potential to overwhelm the
machine control network and complicate
automation process and control
performance.
A smart pneumatics monitor (SPM) is
a “gateway” that aggregates, organizes
and analyzes pneumatics performance
data and can deliver it through separate
pathways to plant management systems,
cloud environments and/or simple HMIs.
This gateway can be independent of the
process control architecture, using OPC
UA, MQTT, FTP or email pathways to
deliver alerts for both system-level and
device-level performance data.
Organizing data
with a Smart
Pneumatics Monitor
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