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March
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HYDROCARBON
ENGINEERING
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diagnostic inspections and preventive maintenance
according to fixed schedules. This is a costly,
labour-intensive process with little assurance that failure
will not occur between inspections.
To improve efficiency, companies have implemented
advanced process control (APC), defined operating
boundaries with their alarm system, created key
performance indicators (KPIs), and called upon local
experts to help solve operating problems. The
effectiveness of these measures has been difficult to
sustain as they rely on dedicated and knowledgeable
on-site personnel.
In addition, industrial firms are looking for ways to make
sense of vast quantities of data that can have a significant
impact on their performance. For instance, reporting and
interpreting of alarms and alerts is central to safe
operations. It is also important to act upon abnormal
situations quickly and effectively.
To support the variety of monitoring and decision
support applications necessary within a manufacturing
facility, data needs to be turned into information and
delivered with context so it can be understood and used in
a myriad of ways by various people.
Operational objectives
For manufacturers and other operating companies, asset
failure and almost imperceptible reductions in process and
equipment efficiency are constant threats to the operating
plan and overall equipment effectiveness (OEE). As a result,
they are shifting their spending to increased equipment
maintenance, and thus losing potential revenue. Factors
such as availability of skilled workers and increasingly
complex production processes are impacting the ability to
predict and detect deteriorating asset health and process
performance.
To maximise their overall performance, modern plants
are looking for ways to transform their operating and
maintenance philosophy from ‘break-fix’ to keeping
operations running as efficiently and steadily as possible
while decreasing unplanned downtime.
Key operational objectives include the following:
Deploy online, continuous monitoring and
exception-based alerts for process performance,
equipment, and controls.
Capitalise on increased data availability across the
enterprise.
Put data into context so as to compare assets to
determine similar conditions or behaviour.
Implement tools for process and reliability engineers,
enabling visual data exploration to decrease reliance
on complex machine learning algorithms to solve
problems.
Establish collaboration with both internal and external
subject matter experts (SMEs).
Integrated, operational and maintenance strategies
open up new possibilities for companies. Data from sensors
monitoring both process and machine conditions are
combined to identify any patterns that indicate a possible
fault or process limitation. This allows the onset of a
stoppage to be recognised early, and corrective measures
to be planned and introduced in the most effective way.
Combining both process and equipment data leads to
truly understanding asset capability, and enables the
definition of accurate, consistent operating and integrity
envelopes that can be used in APC strategies. The result is
greater process stability within control and monitoring
systems for situational awareness at all levels of operations,
as well as improved decision support systems to ensure
assets are operated in an optimal manner. With this
approach, unplanned downtime can be avoided, and both
staff and resources can be employed more effectively.
Leveraging IIoT
There is no doubt the IIoT carries major implications for
industry, especially at a time when infrastructure is ageing
and veteran operators and engineers are retiring. There is
a shortage of experienced workers to take the place of
seasoned personnel, resulting in a loss of knowledge. The
IIoT can be leveraged to institutionalise knowledge
capture while requiring fewer internal experts. This can be
carried out with the help of external experts, such as
process licensors, who have expertise and visibility
beyond the company’s assets. Moreover, the IIoT can have
a significant impact on competitiveness as manufacturers
struggle to pull their weight in the global economic
recovery.
The IIoT allows companies to do more with their
current systems and extend their business processes to
enhance monitoring and reduce the time to action. For
example, a cloud-based control loop and APC monitoring
system can be set up to monitor controls across the
enterprise by an internal or external domain expert. With
visibility and knowledge across sites, experts can alert and
collaborate with site SMEs and recommend actions when
control benefit degradations are detected. Each site can
benefit from earlier detection and faster resolution of
problems afforded by a higher level of expertise focused
on control performance. For the enterprise, these
capabilities can be deployed using fewer resources than
having an expert at each site.
Figure 1.
Equipment failures have a significant impact
on industrial operations, making it imperative to
optimise predictive maintenance strategies.