Hydrocarbon Processing - June 2022 - 82

Biofuels, Alternative/Renewable Fuels
Improving overall efficiency works
in a data lake environment because this
makes it possible to recognize the opportunity
at the upper levels and then
to drill down to individual reactors, heat
exchangers, boilers, distillation towers
and other assets to recognize where inefficiencies
exist and how they can be
fixed. The required actions happen at all
levels and are coordinated by the overall
analytics platform.
FIG. 5. The ability of an analytics platform to work with a data lake's resources allows
for complex problem solving and decision support.
assigns a PFD value based on criticality of
a given installation, it will be a simple matter
to determine the remaining useful life
of an asset, thus allowing the maintenance
team to optimize its activities.
While this pump example is real and
valuable, the concepts that it illustrates go
beyond this limited application and can be
extended universally. We can move from
this simple case to a much higher level of
complexity, effectively treating an entire
plant or production unit as a single asset.
The bigger picture. Using analytics to
characterize a component-such as our
pump example-is the bottom of the
pyramid (FIG. 5). There are many other
examples, but these are the least complex,
and they offer, individually at least, the
lowest payoff. However, when combined,
they have a major financial benefit.
Moving up the pyramid includes more
complex and costly assets (such as large
compressors, heat exchangers and fired
heaters). Beyond these assets are a complete
production unit, a plant and, ultimately,
a company with multiple plants.
As complex as these assets can become,
they still follow the same basic methodology
of applying data-driven and principles-driven
tools.
FIG. 5 illustrates how this works. The
left section defines the levels of challenges
and opportunities based on their scale and
complexity. Moving from the bottom up,
the number of items analyzed becomes
smaller (a single plant vs. thousands of
components), but the complexity and
stakes increase. The upper sections are
where the importance of analytics supported
by data lake technology becomes
82 JUNE 2022 | HydrocarbonProcessing.com
the most evident. Traditional methods using
historians may be sufficient for some
components and assets, but the ability to
perform useful analysis begins to break
down due to data incompatibilities.
The data lake's ability to centralize and
contextualize data makes it possible to
apply analytical tools to more complex issues,
as illustrated in the central green section
of FIG. 5. As a practical matter, moving
higher up the pyramid calls for more datadriven
analysis due to complexity, whereas
principles-driven methodology is more
frequently used at the bottom. Solving
higher-level problems often assumes that
lower-level problems are resolved, so a bottom-up
approach may be preferred. Additionally,
addressing lower-level problems
can sometimes resolve higher-level issues.
Identifying opportunity. The rightmost
column in FIG. 5 illustrates the kinds of opportunities
available using this methodology.
Again, moving from the bottom to
the top, one starts with individual pieces
of equipment, and then gradually works
toward enterprise-wide solutions. Management
must look at this range and determine
where to work on improvements to
deliver the greatest impact.
Take efficiency, for example. Unfortunately,
no process unit or plant comes
equipped with an efficiency knob that
operators can easily turn up through
a single action. Improving overall efficiency
is a process of making dozens
and possibly hundreds of small changes
that tighten up the operation to improve
feedstock utilization, reaction rates and
heat recovery, while also reducing losses,
among other parameters.
The unique challenge of renewable
diesel production. The aforementioned
points apply to companies producing renewable
diesel, and to virtually every
process industry. It is true that renewable
diesel production faces particularly severe
challenges related to feedstock variability,
but those challenges are increasingly
common across many industries.
The challenges for renewable diesel
are not entirely technical, as environmental
sustainability is also a key component.
Often, conventional diesel
is easier to
make and cheaper to produce. A benefit
of renewable diesel is that it is not made
from fossil feedstocks and, therefore, it
helps to reduce carbon emissions.
Maintaining production efficiency despite
major feedstock variability requires
the right tools to handle refining complexity.
These new OT tools, with a data
lake and applications, unify data to produce
meaningful insights while connecting
systems and people. Together, these
tools drive operational performance and
workplace efficiency through automated
workflows, advanced analytics and enhanced
decision support. The challenges
are significant, but today's technologies
make it is easier than ever to design and
implement optimized processes and
work practices.
NOTE
a Emerson PlantWeb Optics platform
MART BERUTTI is the Vice President
of Digital Transformation at Emerson
Automation Solutions. He has 30 yr
of experience in the fields of
dynamic process simulation, control
system validation, industrial ethernet
integration and operator training.
At Emerson, before accepting his current role,
Mr. Berutti served as Vice President of process
simulation. Prior to joining Emerson, he was the
President and Chief Operating Officer of MYNAH
Technologies from its founding in 2002 until Emerson
acquired the company in May 2017. Mr. Berutti earned
a BS degree in chemical engineering from the
Missouri University of Science and Technology.
http://www.HydrocarbonProcessing.com
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