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Progressive
organizations are using mobile, wireless workflow technology to
streamline their process and maximize equipment reliability.
It
is no secret that each year petroleum refiners are spending less
to process a barrel of crude oil into marketable fuel. Corporations
realize they have to go beyond working harder to stay competitive.
Forward-thinking companies continuously find more cost effective
ways to streamline their processes by leveraging maintenance technologies
to improve the bottom line. It is a survival of the fittest for
the refining industry—fail to perform optimally over a substantial
period and chances are you will end up as the slowest in the herd,
eventually falling out of the pack, or worse, a more efficient organization
consumes you.
Progressive
organizations are using mobile, wireless workflow technology to
streamline their process and maximize equipment reliability to stay
ahead of the competition. This article will present a review of
the reliability goals (business drivers) and the results of implementing
an operator driven reliability (ODR) process using mobile, wireless
workflow technology at a Gulf Coast refinery.
The
first step
Valero Energy Corp. purchased a Gulf Coast, lower-quartile performing
refinery in 1997 from a crude oil trading company. After an infusion
of refining management, a reliability process was initiated using
consultants to facilitate teams that were formed to yield reliability
and quartile ranking improvements. Although several teams were successful,
two became paramount: the reliability measurements and the ODR teams.
Reliability measurements made sense and became a way of life—you
cannot manage what you cannot measure. The metrics for reliability
measurements were completed and implemented in early 1999, while
ODR blossomed in early 2000.
Both
teams identified a need to streamline operator rounds and obtain
technology to facilitate the review of all data collected. These
needs became key requirements for the ODR process. It was essential
to develop trending capability of field-collected data to identify
equipment in early phases of failure. If problems were detected
early, the equipment could be halted and corrective action taken
to minimize the cost to repair.
Profits
can be increased by producing more or spending less. Management
hoped the process of increasing reliability without adding personnel
or workflow would result in less spending. To gain data consistency
through the implementation of a best practice, the team identified
the need to eliminate paper and implement electronic devices where
data would be entered and seamlessly transferred to a system that
was available for analysis by interested parties. The goal was for
operators to accept ownership of their equipment and to accept a
new system, one that enforced a best practice workflow process.
After
evaluating available technologies, IntelaTrac from SAT Corp., Houston,
TX, was chosen. IntelaTrac is industry workflow automation software
used on rugged mobile handheld devices. The software aligned with
management’s vision for a tool that crosses all disciplines and
collects data for analysis—from operations to maintenance, environmental,
and turnarounds. As a bonus, the software leveraged existing legacy
software systems including the Aspen process historian and SAP.
While
in front of equipment, operators can take immediate, preventive
actions on their routine rounds. Asset status can be documented
with bar code technology or radio identification tags. Audit ability
can also be preserved and the data updates into back-end systems
for additional analysis in other departments.
During
the ODR implementation, a review was performed of what field data
should be collected. Input from several departments ensured that
all collected field data would be of value and analyzed. The golden
rule was, "if data is not going to be analyzed then it will not
be collected." The final result provided key visual, vibration,
and temperature readings that provide early detection of equipment
degradation, and include several preventive maintenance activities
that previously were performed by maintenance personnel. This is
beneficial to the maintenance craft as they have more time to perform
craft skills activities.
Results
in phases
The first phase was a pilot installation of the software and
the mobile technology in three process units within the complex.
Several specific assets in the early stages of failure were detected
and failure was prevented. The return on investment (ROI) for the
pilot from that failure prevention indicated a three-month payback.
Satisfied with the results, the site rolled out ODR to the remainder
of the complex. Similar results were observed and a two-month ROI
was determined.
Over
a 12-month period, the early detection of equipment failures was
recorded and a dollar value assigned. To define the value, historical
information from SAP provided the average cost of the specific equipment
repair that was used as a baseline against any items identified
using the software. The cost to repair equipment identified through
early detection was then subtracted from the historical baseline
average. Items found included worn bearings and seals, equipment
out of alignment, unexpected process conditions (plugged strainers
or seal pots), and coupling adjustments. Each item found to have
a problem was taken out of service before having a catastrophic
failure event. More than $558,000 in savings and maintenance avoidance
was identified.
Figure
1
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| Total
work order costs during the period support the findings in specific
equipment saves. |
Measuring
the result
To
align with the reliability measurements effort, total work order
costs were reviewed. Figure 1 illustrates total monthly work
order cost for the complex implementing ODR.
An
equal period pre- and post-IntelaTrac implementation is illustrated.
Total work order costs during the period support the findings in
specific equipment saves.
Total
work order cost was analyzed for the months prior to the ODR process
and software implementation. Comparing the 44 months prior to ODR
implementation to the 12 months that followed pointed out the obvious—
the complex monthly work order costs had been reduced by more than
$87,000 per month, a 33 percent improvement. With this result, a
complete ODR site rollout was justified and is currently in progress.
Figure
2 is a Crow/AMSAA reliability growth diagram illustrating a
positive step change in work order cost over time, and a prediction
of the amount to be saved in avoided maintenance at a future referenced
date.
Crow/AMSAA
charts are the log-versus-log of a cumulative-sum graph. Initially
used by J. T. Duane of General Electric to plot cumulative failures
over time and later mathematically proven by Dr. L. Crow of the
U.S. Army Materiel Systems Analysis Activity (AMSAA), the plot is
a fairly accurate model and predictor of maintenance costs.
Each
point in the graph represents maintenance costs for 1 mo. After
a few points are plotted, a best-fit line can be drawn through them.
The Beta, or slope of the line, shows if improvements are taking
place. A slope greater than 1.0 indicates that reliability efforts
are failing while a slope less than 1.0 indicates that reliability
efforts are succeeding. A slope of 1.0 is simply treading water.
Lambda is the Y intercept of the work order cost line. R2 is the
mathematical fit of the work order cost line to the monthly cost
points (the closer to 1.000, the more accurate the line is drawn,
i.e., the better the slope is).
Figure
2
|
| CROW/AMSAA
reliability growth diagram of work order cost after implementation
shows a positive step change over time, and a prediction of
the amount to be saved in avoided maintenance at a future referenced
date. |
The
figure illustrates the total work order cost each month for the
complex implementing ODR. An equal period pre- and post-software
implementation is illustrated. A best fit line was drawn for months
prior to ODR and the slope calculated. A 1.24 slope was determined
indicating that a step change, almost a paradigm shift, was warranted.
A second best fit line was drawn for months after ODR implementation
and the slope calculated. A 0.75 slope was determined indicating
that a paradigm shift in maintenance avoidance had taken place;
hence the $87,000 per month cost savings in the complex.
Success
factors
Could all of these savings be attributed to the implementation
of the ODR process? Probably not. A refinery is a dynamic place
with many influencing factors. During this period, operations management
took a strong reliability stance, seasoned reliability engineers
were assigned to the complexes, and a turnaround was conducted during
the period. Maintenance activities likely took place during the
outages that may not have been true turnaround items. Operations
also took an equipment ownership position during this period that
continues today. However, it is difficult to dispute the data. The
step change only occurred in the complex that implemented the ODR
process, including the installation of the software, and the use
of wireless, handheld data collectors.
The
trickle-down effect
Operators and other personnel have begun using the software
and the wireless handhelds outside of the ODR realm.
Process
safety management and occupational safety inspections, such as car
seal, fire extinguisher, and hose station inspections, are being
conducted. Volatile organic compounds information is being collected,
stored, and transferred to the environmental department for regulatory
requirements. Caustic concentrations are being reviewed and calculated
in the field. Even a large expansion and turnaround conducted early
in 2002 was followed and reported to corporate management using
the handhelds and software. This was received with enthusiastic
acceptance by the turnaround management team.
Staying
ahead of the pack
Realizing
the need to go beyond just working harder to stay competitive and
trying to be the faster animal in the herd, investigation is underway
to meld ODR into reliability centered maintenance and risk-based
inspection initiatives to develop a more seamless reliability process
at the site. The wireless handhelds are rapidly becoming the mobile
laptop for many individuals who are required to complete various
tasks within the site. It will be another year before the effort
to implement ODR refinery-wide is fully analyzed, reviewed, and
reported.
James
R. Cesarini is manager of reliability and turnarounds,
Valero
Energy Corp., San Antonio, TX
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