Efficient Plant June 2021 - 9

feature | predictive-maintenance strategies
NEW INDUSTRIAL-AUTOMATION
capital projects can easily incorporate the
latest technologies for providing built-in
remote monitoring and analytical functions.
Oſt en these features can be included for a
negligible cost, especially in comparison with
the extensive value they deliver.
Th ere are far more manufacturing sites
already in service than there are new installations.
Equipment at existing discrete and
hybrid manufacturing sites is years or decades
old and must continue to operate, requiring
increasing amounts of ongoing maintenance.
End users at these sites would like to gain
some of the advantages of modern predictive
maintenance (PdM), overall equipment eff ectiveness
(OEE) analyses, and key performance
indicator (KPI) determination. Industrial
edge-computing devices, with integrated
computational capabilities, are the answer.
MODERN COMPUTING VALUE
Under normal operating conditions, personnel
at most manufacturing sites are satisfi ed
if equipment and systems achieve basic
functionality. Perhaps some locations have
undertaken rudimentary eff orts to measure,
and then improve, operational performance,
but essential productivity oſt en trumps more
involved optimization eff orts.
Th e reality is that aging equipment becomes
increasingly prone to failure. Most facilities
support their systems using traditional methods
such as time-based preventive maintenance
or event-based reactive maintenance.
Th e former approach can waste resources and
the latter leads to downtime because things are
only fi xed once they break. Both schemes are
costly in the long run.
Many users have come to realize the
elementary benefi ts provided by typical
automation devices and platforms such as
programmable logic controllers (PLCs),
human-machine interfaces (HMIs), and
supervisory control and data acquisition
(SCADA) systems. Th ese provide visualization
of current equipment status, annunciation of
alarms, and historization of data for analysis.
All are important for taking the fi rst steps
toward a continuous-improvement program,
but greater gains are achievable.
When modern computing systems can
Modern edge computing can be added to existing discrete-manufacturing islands of automation,
improving overall operations visibility and enabling access to valuable on-machine and plant-sourced
data. All images courtesy Emerson
Inset. The edge maturity model depicts how traditional discrete and hybrid manufacturing sites can
use modern hardware and software architectures to enable the transition from standard automation to
more advanced connectivity, analysis, and insight-driven operations.
be added to existing equipment, it becomes
possible to tap into on-machine and other
plant-sourced data. Once data is accessible,
performing OEE analyses quantifi es performance
so users can recognize problem areas,
implement potential solutions, and track the
results of optimization eff orts. OEE is also
useful as part of a broader strategy to improve
operational effi ciency, drive lean production,
and reduce overall waste. It's a fundamental
part of a data-based approach to improved
operation, but this can only be accomplished
when the right data gathering and computing
systems are in place.
Taking things a step further, PdM makes
maintenance more proactive and cost-eff ective,
minimizes costly failures, and increases
productivity. OEE information helps users
JUNE 2021
EFFICIENTPLANTMAG.COM | 9

http://www.EFFICIENTPLANTMAG.COM

Efficient Plant June 2021

Table of Contents for the Digital Edition of Efficient Plant June 2021