Tech Briefs Magazine - March 2022 - Sensor-7

A wealth of breakthrough ideas and
business-changing opportunities can
come from mining IIoT data - that's
one of its primary benefits. Data analysis
should be done seamlessly across
the spectrum of micro to macro levels
- from individual machine performance
analysis to the connected factory
collectively. You're in the best position
to innovate when barriers are removed
to IIoT data access and analysis for
everyone, from production line maintenance
managers to business analysts
to executives.
Figure 2. Sensors help you monitor machines while on the factory floor, in the front office, or on the
go 24/7. (Image: Monnit)
Valuable Data Insights Come From
Connected Machines
Uptime is everything in manufacturing.
When one machine malfunctions or
fails, it can create ripple effects of
increased time to market and potentially
damaging downtime all the way to product
delivery and customer service.
Data from the IIoT is the " currency "
of the smart, connected factory. It produces
reactive, predictive, and even
transformative value by fundamentally
influencing how and when a person or
machine takes control, makes corrections,
conducts maintenance, and
streamlines production. Actionable data
from the IIoT is the main benefit of a
connected factory.
Using data to feed dashboards, analytical
tools, and operational management
systems leads an organization to better
innovation, efficiency, and profitability.
Wireless sensor data activates the IIoT's
value across a factory - from faster corrective
reactions to predictive management to
transformative business innovation.
Help Factory Sensor Data Flourish
People and machines must collaborate
and share information seamlessly
to orchestrate ideal production performance.
Wireless sensors embedded
in or attached to virtually all assets can
deliver the data that managers need to
keep the factory humming and to
refine processes.
Manufacturers can use many strategies
to ensure wireless sensor data gives them
the most value from their connected factory.
The following are three important
data management approaches.
* Leverage the autonomous functions of
control systems. Many critical assets
Sensor Technology, March 2022
Cov
work together as a seamless unit in a
connected factory. But two of the most
important assets are industrial control
systems (ICSs) and programmable
logic controllers (PLCs). An ICS works
to run and automate industrial
processes by collectively managing
data, devices, systems, networks, and
controls throughout a factory. In comparison,
a PLC can stand alone as a
sensor data collection hub or integrate
into an ICS as a critical control component
of the overall system.
Predictive maintenance depends on
ICSs and PLCs. The real-time data
from sensors they receive, process, and
put into play is vital for running, maintaining,
and automating a factory.
Manufacturers can leverage advanced
diagnostics, analytics, and
insights using data from sensor systems
to boost productivity, reduce costs, and
improve safety. An ICS is at the core of
this endeavor. The automated processes
initiated from ICSs free up IT and
operational technology (OT) professionals
to optimize the factory without
having to worry about reactive or routine
maintenance tasks. Factory managers
can know about machine performance
issues in advance and move
to predictive rather than repetitive,
scheduled maintenance. With sensor
data filtered through an ICS, technicians
can know which machines to control
and when they need maintenance.
* Remove data barriers and silos. Data
sets shouldn't stay within individual
departments. It was essential to eliminate
data silos when the information
age began, and it's even more imperative
ever since machines started talking
to each other and to us.
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* Take a leaner approach to data sharing.
On a global industrial scale, the
IIoT generates data in massive volumes.
Even on a significantly smaller
scale, factory management can still get
overwhelmed by the speed and volume
of data. Edge computing can help by
providing actionable sensor data to
frontline factory managers and
machines to make fast or automated
real-time decisions. With smart sensors
and gateways doing edge computing
- the method of efficiently capturing,
storing, and processing data where it's
generated - managers don't have to
analyze a large amount of raw data to
take action. They also don't have to
wait for data to be sent to the cloud,
exported, mapped, and analyzed to
arrive at the same conclusion the edge
devices already delivered.
While it's important to consistently
improve data access and analysis, it's
crucial not to overload anyone who
isn't a data analyst. Keep data alerts,
feeds, and reports to what applies to a
person's role. When you glean significant
new data insights, ensure key
stakeholders are aware and share why
specific data points matter to different
departments.
Wireless Sensor Platforms Support
Maintenance and Business
Optimization
It's important to take a careful, systematic
approach to factory automation. It
may not matter how automated your factory
is if you're not aware that a machine
is vibrating too much. The vibrating
machine could mean it's ready to malfunction.
In turn, this failure could
cause the entire, or a portion of, an
automated system of machines to go
offline, creating unplanned, unnecessary
downtime. The lesson here is that
automation can crumble even when only
one cog is loose.
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Tech Briefs Magazine - March 2022

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