Sometimes a problem seems to linger forever. For the many
years I have worked with advanced process control (APC)
practitioners, APC controller maintenance has been a topic
near, or at the top of, their problem list. Given that APC
practitioners are not generally demure personality types and
are extremely passionate about their business, the
conversations about APC maintenance can be dynamic
at times. Fortunately, with the recent developments in APC, the
tenor of the conversation has shifted dramatically, and there
is great optimism.
When considering APCs history, there is no doubt that
the angst surrounding controller maintenance is understandable.
Traditional maintenance approaches have been expensive,
disruptive and labor intensive. Arguably, the most prominent
and visible issue has been the need to take controllers offline
to collect open-loop process data suitable for model
identification, which resulted in lost stability and benefits.
Similarly, step testing was disruptive and resulted in further
costs due to off-spec product and lost throughput.
In attempts to address the maintenance problem, many APC
vendors have developed tools to assist in revamping APC models
and, to one degree or another, they did deliver some benefits.
Nonetheless, these solutions never completely addressed the
core problems: Maintenance was still done infrequently.
Controllers were still taken offline to collect current
open-loop process data. The scope of effort was still high due
to a lack of precision in identifying problematic aspects of
the models. Step testing was still done in an aggressive manner
to shorten the duration of the testing period.
These issues have affected not only the core base of users
of the technology (like refiners and
olefins/bulk chemical producers), but they have also created
barriers to APC adoption in adjacent industry segments. The
initial and ongoing cost of ownership relegated the technology
to very large-scale processes where the benefits were large
enough to justify the effort and expense of developing APC
solutions. The deep skill set required to be an effective
practitioner further hampered growth of the installed base.
It needs to be pointed out that these advances are the
result of over 10 years of concentrated effort. The solution
required innovation in just about every area of the technology,
from the model identification algorithms to the optimization
engine. It is driving considerable change in practitioner
workflows and methodologies. And as we observe the early
adopters of the technology, we are seeing a wholesale change in
the economics of APC, with lower initial costs and less erosion
of benefits over time.
Wholesale change in economics
The game-changing innovation is called adaptive process
control. To appreciate the significance of this achievement for
APC technology, Table 1
points out some of the key innovations developed during the
How it works
Rather than build another tool for sustained value, the
latest adaptive process control software develops a controller
that is more self-sufficient and requires less maintenance. APC
maintenance becomes a continuous built-in process rather than a
project. It automates the process of
assessing model quality, collecting current data and generating
new models as needed.
Adaptive vs. sustained value
In the traditional model of controller maintenance
(sustained value), revamping the controller was a lengthy and
costly project. Under adaptive process control, however, the
controller is modified over time in more of a continuous
process (Fig. 1). The model update occurs
without the need to take the controller offline and enables a
company to reap the benefits of both control and optimization
while the model is under maintenance. Model quality analysis
(Fig. 2), which continually runs and assesses
the accuracy of the model, can detect when degradation of
performance occurs. It can pinpoint a specific part of a
controller, thereby helping engineers to determine the
underlying cause of the degradation in performance.
1. In adaptive process control, the
controller is modified
over time in a continuous process.
2. Model quality analysis runs continually
assesses the accuracy of the model.
The innovations in the model identification algorithms increase
efficiency by enabling the use of data with lower
signal-to-noise ratios. This improvement, in turn, enables the
use of smaller test step sizes, resulting in less disruptive
testing. By performing very small perturbation tests, adaptive
process control is able to maintain process stability and, in
parallel, generate data that is sufficient to create a new and
accurate controller model. The control engineer has the ability
to define the degree of trade-off between the length of the
testing period vs. the degree of optimizing control.
Adaptive modeling creates candidate models for the engineer
for review. Importantly, the engineer always has the final
decision about which models to deploy online. In addition,
adaptive process control runs an automated test agent to
continuously monitor the process and alert the engineer in real
time of any problems that occur within the workflow. As a
result, adaptive process control shifts maintenance from
arduous projects to a pragmatic online
approach for continuous maintenance.
Now, engineers can do everything required to update control
models without the need to turn off the controller. Of equal
importance, the software design ensures that the process
control engineer remains central to the decision-making process
in deciding which new models to deploy.
More than maintenance
One happy consequence of the automation in adaptive process
control is that it reduces the cost and effort to apply APC to
new controllers, not just to the existing ones. This area is
where process manufacturers will see maximum benefit. That is,
applying APC to multiple controllers in parallel. With adaptive
process control doing more of the work, the engineer can split
time between controllers and complete multiple modeling efforts
in the same time span. With this approach to controller
modeling, users have reported a minimum 25% reduction in effort
for single projects and twice the benefit for multiple parallel
projects. In addition, companies
that are well along the maturity curve with APC are uncovering
new rollout opportunities in secondary units and utility
systems. Due to these new economics, companies are re-thinking
the traditional wisdom of where it makes sense to apply
Consider the following scenario: A typical refining unit with APC generates a
minimum annual benefit of $2.5 million (MM) but gives away 35%
across a five-year cycle due to maintenance-related issues.
Thats a loss of $875,000 per APC application. Multiplied
across an average of nine major units under APC control per refinery, this totals almost $8 MM
in potential lost benefits over a five-year period that can be
traced back to downtime or sub-optimal operating periods of the
controller. Of this time, 60% is usually spent in revamp, 30%
is underutilization due to the controller not operating at peak
performance and the final 10% is attributed to plant
turnaround. With adaptive process control, refiners can get
online faster to begin accruing benefits sooner after
turnaround and reduce sub-optimal operation over the life of
Adaptive process control introduces a new economic rationale
for APC and easily justifies its pursuit. With this latest
advance, its easier than ever to unlock APCs
tremendous operational benefits. Refiners and chemical/petrochemical producers can now
deploy APC and enjoy sustained benefits by implementing a
continuous process for controller maintenance. Adaptive process
control is here, and it realizes the decades-long goal of more
sustainable APC solutions. HP
Robert Golightly is senior manager
for manufacturing product marketing at Aspen Technology. He is
responsible for solution marketing for advanced
process control on a global basis, primarily dealing
with bulk chemicals, refining, specialty
chemicals and polymers.