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Cognis Corporation’s unique QTA® system provides data and
information to better control processes and improve profitability.
With the ability to rapidly analyze a variety of materials, QTA
delivers results when and where you need them. The system consists
of three layers in an FT infrared instrument, patented data
treatment technology and centralized calibrations:
The Platform: Fourier Transform -
Infrared
The platform is the latest Fourier Transform
– Infrared technology that allows exploration of a comprehensive
range of material traits.
Patented Data Treatment:
Chingometrics
Our patented data treatment, known as
Chingometrics, ensures consistent results throughout the supply
chain with no calibration adjustments.
Networked Systems: with centralized
calibration models
Our networked systems with centralized calibration models
allow users to receive updates immediately. The results are stored
in a central database where they are instantaneously available
across an organization or entire supply chain.
Using QTA, producers will maximize the value of product streams
by sourcing and blending incoming materials, increasing yield and
minimizing scrap or waste. When used in conjunction with the
manufacturing process, QTA will monitor the output characteristics
of various process streams from beginning to end.
Customer Testimonials:
"QTA has proven to be an extremely valuable tool for our plant start
up. Immediate results provided by Cognis enabled us to quickly make
changes and dial in the plant much quicker than any conventional
style wet lab.
It is also the quickest, most cost efficient
method we have found to ensure that every load that leaves our plant
falls within specifications. Samples are taken while the truck is
loading and results for that specific load leave in the hand of the
driver along with the bill of lading."
- John Whittington, VP, Integrity Biofuels
"During an
annual model validation several samples were sent into the QTA lab.
Most of the samples fit well into the existing QTA model. However,
there were three samples that had primary data that did not look
correct to Dr. Ching-hui Tseng. These three samples simply did not
fit into our model. Instead of forcing them into the model Dr. Tseng
asked if our customer would rerun their samples through their normal
GC process. The GC values were over 3% from QTA prediction.
The new results showed that the QTA predictions were right and the
original GC values were off! The customer's stated "We did go
back and rerun the samples you requested. It looks like there could
have been an error the first time in the wet chemistry. I think it
is great to see how we can use NIR to verify wet chemistry results."
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