Hydrocarbon Processing - November 2022 - 32

Process Controls, Instrumentation and Automation
gency and never addressing the root causes. However, no plant
manager will approve an expenditure of resources on a system
study if it is not directly tied to an actionable plan.
Pitfall #1: Asking for a site survey without a defined
action plan. Before asking for funds to hire experts to produce
an expensive report, ensure the team understands what the data
will be used for: to create a master, evergreen maintenance plan.
Evergreen lists provide managers with a tool to paint a holistic,
realistic picture of upcoming analyzer projects for leaders to
understand and assess in the budgeting cycle. Although the cost
of developing and maintaining such a list can create sticker shock,
translating analyzer failures into financial risk can justify the plan
and make it easier to convince the leadership of its importance.
Analyzers are complex, with sophisticated sampling and calibration
systems. Many are housed in their shelters in the field and
have heating, ventilation and air-conditioning systems to keep
the surrounding environment clean and stable. As a result, it can
be time-consuming to get a complete picture of model numbers,
obsolescence and parts availability. The picture gets complicated
and costly if the systems reside in hazardous classified areas.
This is where a planning team can balance the insights of the
facility manager's technical counterpart, who may want to go
into more detail than necessary, with what is financially feasible
to decision-makers. Managers should also factor in the ongoing
maintenance of the list. Paying for a holistic study makes no
sense if the resulting upgrade plan is not maintained long term.
Pitfall #2: Performing a survey without identifying a
long-term owner. Once decision-makers agree to the initial
study, assigning an internal expert responsible for maintaining
the data ensures the initial investment. The person who
will be responsible should also be involved in developing the
evaluation plan. This step is crucial; without an assigned person
committed to the concept, any money spent on this effort
will be wasted.
An internal evergreen expert can be trained to manage the
evergreen spreadsheet or database efficiently. The system is
intuitive to whomever has helped create it, and the feeling of
ownership from the development encourages that expert to be
more invested in maintaining it.
The first step in building this internal skill set is to identify
the primary internal content expert and ensure that person understands
the project's goal and their role. The expert must see
the evergreen list as a smart strategic investment.
For example, despite their extensive knowledge on the subject,
maintenance and reliability personnel may not be ideal
candidates for maintaining the evergreen list because they often
deal with emergencies, which naturally interfere with longterm
maintenance projects. Successfully creating and maintaining
the evergreen list takes time and planning.
The task is well-suited to a project leader or engineer with
the bandwidth and organizational skills to reliably manage and
maintain the list. Field technicians who are in the plant or the
field every day working on the analyzers and know their operational
status can provide technical input.
The internal evergreen list expert must take the input provided
by the technical and maintenance staff and drive the
tasks, keeping staff on schedule, managing the budget and act32
NOVEMBER 2022 | HydrocarbonProcessing.com
ing as the intermediary to translate technical language into dollars-and-cents
proposals that can be understood and accepted
by leadership. Typically, these efforts fail because the technical
needs are not converted into financial costs and risks. In
addition to maintenance plans for monitoring equipment and
analyzers, upgrades and ongoing support to data acquisition
systems must be included to maintain streamlined compliance
reporting and data reviews.
Pitfall #3: Failing to translate and quantify risk into
financial terms. Familiarity with the reliability of analyzers
is valuable to decision-makers for safety and regulatory reasons
and for the general planning of maintenance and replacement.
Reliability-or the absence of it, in the form of equipment
failure-is one piece of the risk analysis puzzle. Risk is a combination
of the likelihood that a failure will occur, along with
the consequences of that failure. Many technicians and maintenance
engineers excel at describing scenarios and predicting
the likelihood, but they may need help balancing that information
against other competing interests to determine where that
risk fits in terms of priority for capital expenditure.
That balance is a key part of any meaningful discussion with
leaders about what deserves budgetary priority. In many cases,
the underlying issue is an inability to convey what is most important
(e.g., breakdowns, equipment failures and the inability
to make repairs because of obsolescence). Technicians and
planning professionals must take this a step further and balance
the identified risk against the cost and the effort that will be required
to mitigate that risk.
Experts with a technical background know these things are
important, but they often struggle to communicate them using
the language of risk analysis that will resonate with decisionmakers.
An experienced project leader or engineer brings the
skills to translate such vital analysis.
Consider the scenario where an analyzer is old and will break
down. A leader may ask what the risk would be if it fails. The
risk may be fines to the organization from regulatory agencies
when a boiler is forced to be taken offline because an analyzer
breakdown inhibits emissions monitoring.
This is an accurate description of the consequences of an
analyzer failing. However, risk analysis is a multi-faceted examination
of consequences and likelihood of failure in concert. A
project team expert can ask the right questions to understand
the entire risk spectrum-the likelihood and how to plan for it.
A holistic survey helps organizations go beyond planning
for failure. For example, a particular analyzer is obsolete, which
means spare parts are hard to procure, but the facility has one set
of spare parts on hand. On average, spare parts are needed about
once a year, but that has been increasing. In the subsequent 5
yr, it is reasonable to expect one failure will use the spare parts,
and a second failure will result in a shutdown. In this case, the
internal expert can forecast a high chance of being out of commission
within 2 yr-3 yr and certainly within the next 5 yr.
Equipped with a reasonable time frame, a facility manager
can make a plan that balances the consequences with the likelihood
the analyzer will reach the end of its lifecycle by a specific
date. The manager can then determine an acceptable level of
risk and isolate the point at which that risk becomes unacceptable,
enabling the organization to set priorities. This contrasts
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