Hydrocarbon Processing - December 2021 - 32
Process Optimization
FIG. 3. ANN model structure.
FIG. 2. ANN model development, validation and deployment workflow.
was deployed online, and prediction results
were validated over a period and
over various grades. It was observed that
the model's results and responses conformed
to actual values within a defined
accuracy range. The model also responded
to the changes in process conditions in
desired directions. The response during
the grade transition was also acceptable.
The model's predictions were used for
plant operations, thus reducing the need
for expensive laboratory analysis.
Process description. The ANN model
was used in an LDPE plant, where the
LDPE was produced in a very high-pressure
tubular reactor. A simplified version
of the existing plant is shown in FIG. 1. The
process gas and the mixture of ethylene
and modifiers were heated in the preheater
before entering the reaction zone. The
complete reaction occurred across four
reactors in a series. A free radical initiator
was pumped into the four reactors to start
the polymerization reaction. Multiple
modifiers in different proportions were
added to vary the MFI. Polymerization
was a strongly exothermic reaction. Unreacted
reactants were separated in high- and
low-pressure separators before sending
the polymer to the extruder, after which
it was bagged in the packing section. Mul32
DECEMBER 2021 | HydrocarbonProcessing.com
tiple grades of LDPE were produced and
characterized primarily by MFI/density.
The ANN model. The workflow for the
model development, validation and deployment
of the ANN model are shown
in FIG. 2. All raw historical data was taken
from process and quality data servers. For
the development phase, the raw data underwent
pre-processing and feature engineering
to finalize the dataset for model
input. The model was then trained, using
a training dataset, and validated against
test data. Upon successful validation, the
model was then picked for real-time prediction.
Real-time data also came from the
same server and underwent the same preprocessing
and feature engineering before
being inputted into the model. The online
deployed model was scheduled to run at a
particular frequency (5 min in this case),
as it provided enough time for the operator
to respond to the changes in the MFI.
Data pre-processing, feature engineering
and transformation. In any
polyolefin reaction, the kinetics of the reaction
are very important. It is also important
to take care of process lags at the time
of dataset preparation. In this case, while
MFI sampling was done from the extruder
end, the reaction occurred across four reactors,
followed by the product passing
through a high-pressure separator section
(HPSS) and a low-pressure separator section
(LPSS) to reach the extruder. Time lag
was considered for the proper match of the
target variable to the process parameters.
Interaction analysis of the process variable
to the MFI indicated that it took approximately
20 min for any changes done on the
inputs to be reflected in the MFI. Out of
these 20 min, materials remained in the reactors
for about 10 min, while the remaining
time was consumed to pass through the
HPSS and LPSS. To provide the impact of
the transportation lag while making input
data sets, a lag of 15 min was considered
for parameters until the second reactor, 10
min for the third and fourth reactor parameters,
while zero lag was considered for the
extruder parameter.
On understanding the process and interaction
of the variables to the MFI, 21
variables were identified. These included
flow (such as fresh feed, recycled flow,
modifiers and free radical initiators at different
reactor locations), temperature (all
four reactor inlets, and maximum and end
temperatures) and pressures (reactors,
extruders and feed, among others). With
more than 21 parameters and time lag, a
dataset was prepared with 2 yr of historical
data. After outlier treatment, the correlation
was checked for each input parameter
with the MFI.
On analysis, it was found that the initiator
flowmeter did not measure pure initiator
content, as this measurement was done
after the addition of solvent. This called for
additional parameter generation through
feature engineering to map the proper response
to the MFI. The initiator impacted
the extent of the reaction, which led to a
temperature increase across the reactor.
This increase also indirectly indicated the
same extent of the reaction. Therefore,
in the following, the rise in temperature
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Hydrocarbon Processing - December 2021
Table of Contents for the Digital Edition of Hydrocarbon Processing - December 2021
Contents
Hydrocarbon Processing - December 2021 - Cover1
Hydrocarbon Processing - December 2021 - Cover2
Hydrocarbon Processing - December 2021 - Contents
Hydrocarbon Processing - December 2021 - 4
Hydrocarbon Processing - December 2021 - 5
Hydrocarbon Processing - December 2021 - 6
Hydrocarbon Processing - December 2021 - 7
Hydrocarbon Processing - December 2021 - 8
Hydrocarbon Processing - December 2021 - 9
Hydrocarbon Processing - December 2021 - 10
Hydrocarbon Processing - December 2021 - 11
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Hydrocarbon Processing - December 2021 - 19
Hydrocarbon Processing - December 2021 - 20
Hydrocarbon Processing - December 2021 - 21
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Hydrocarbon Processing - December 2021 - 81
Hydrocarbon Processing - December 2021 - 82
Hydrocarbon Processing - December 2021 - Cover3
Hydrocarbon Processing - December 2021 - Cover4
Hydrocarbon Processing - December 2021 - GP-1
Hydrocarbon Processing - December 2021 - GP-2
Hydrocarbon Processing - December 2021 - GP-3
Hydrocarbon Processing - December 2021 - GP-4
Hydrocarbon Processing - December 2021 - GP-5
Hydrocarbon Processing - December 2021 - GP-6
Hydrocarbon Processing - December 2021 - GP-7
Hydrocarbon Processing - December 2021 - GP-8
Hydrocarbon Processing - December 2021 - GP-9
Hydrocarbon Processing - December 2021 - GP-10
Hydrocarbon Processing - December 2021 - GP-11
Hydrocarbon Processing - December 2021 - GP-12
Hydrocarbon Processing - December 2021 - GP-13
Hydrocarbon Processing - December 2021 - GP-14
Hydrocarbon Processing - December 2021 - GP-15
Hydrocarbon Processing - December 2021 - GP-16
Hydrocarbon Processing - December 2021 - GP-17
Hydrocarbon Processing - December 2021 - GP-18
Hydrocarbon Processing - December 2021 - GP-19
Hydrocarbon Processing - December 2021 - GP-20
Hydrocarbon Processing - December 2021 - GP-21
Hydrocarbon Processing - December 2021 - GP-22
Hydrocarbon Processing - December 2021 - GP-23
Hydrocarbon Processing - December 2021 - GP-24
Hydrocarbon Processing - December 2021 - GP-25
Hydrocarbon Processing - December 2021 - GP-26
Hydrocarbon Processing - December 2021 - GP-27
Hydrocarbon Processing - December 2021 - GP-28
Hydrocarbon Processing - December 2021 - GP-29
Hydrocarbon Processing - December 2021 - GP-30
Hydrocarbon Processing - December 2021 - GP-31
Hydrocarbon Processing - December 2021 - GP-32
Hydrocarbon Processing - December 2021 - GP-33
Hydrocarbon Processing - December 2021 - GP-34
Hydrocarbon Processing - December 2021 - GP-35
Hydrocarbon Processing - December 2021 - GP-36
Hydrocarbon Processing - December 2021 - GP-37
Hydrocarbon Processing - December 2021 - GP-38
Hydrocarbon Processing - December 2021 - GP-39
Hydrocarbon Processing - December 2021 - GP-40
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