Contact:
(203) 744-5905
Working Definitions
Accuracy
the ability of any test
method, lab analysis, or analyzer, to yield the true value of the sample as a
result of the measurement. That is,
the result of the measurement gives the true value within the error of the
measurement. The accuracy of any
method is best determined by round-robin testing of that method.
Reproducibility
the determination of the spread around the true value. Determined by multiple measurements of the same samples at
multiple sites (round-robin testing). It
is the true error of the method.
Repeatability
the measurement of the spread around a test result from a single analyst and/or
single analyzer at the same site on the same sample. However, this does not mean that the result is accurate (produces the
true value).
Precision
- the
level to which any measurement can be accurate. That is, 46 or 46.259.
Bias
a
definite offset from the true value. Consecutive
single point measurements can be biased.
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Model Definitions
Global Model:
Any chemometric based prediction that incorporates lab analyses and
samples from multiple locations on multiple streams, multiple processes, and
multiple stream sources (i.e. crudes). By
definition then, the prediction is accurate (predicting the true value) to
within reproducibility. In
order to compare a global model prediction to any single point lab measurement,
the lab must first validate that the lab can meet the reproducibility
requirements of the method, or ascertain its actual reproducibility by as
described in ASTM D3764. Once the
lab measurements are validated, single point lab measurement comparisons to the
chemometric prediction should be within reproducibility limits. Global models are less prone to bias errors and drift.
Model Training:
The process of enabling a global model to statistically recognize (i.e.
f-test, mahalanobis distance, etc) the spectral results of a specific analyzer
at a specific location. Requires no
extensive lab sampling and analyses or exorbitant input of local unit and
process specific spectral files to the model.
Local Models and
Localization: Local models
are built on data from a specific process unit, in a specific location, usually
incorporating only lab analyses from the on-site laboratory. This effectively makes the model an on-line duplicate of the on-site
laboratory and therefore subject to bias. Further,
if a model is localized too much, it can be prone to drift (moving away from the
true value) and/or fail to predict outside of the model space when the process
changes or experiences an upset.
NMR Reproducibility:
The limits of the differences between a valid, single point lab
measurement and an NMR predicted result. This
value is determined by the primary method and range of samples that the model is
built on.
NMR Repeatability: The limits of the differences between successive predictions on a blocked in sample in the NMR under defined conditions. This value is determined bythe primary method and range of samples that the model is built on.
NMR Model and Application Strategies
NMR models based predictions are
based on two types of applications: Process Control or Product Certification.
Process Control: Feed Forward and/or Feedback
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NMR models cover a wider sample range. |
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Very Robust: continue to accurately predict over wide process ranges. |
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Reproducibility differences between the NMR prediction and any single point lab measurement will be slightly higher. |
Product Certification: i.e. Blending
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NMR model ranges are narrowed and confined with respect to the product (i.e. gasoline and blend components only) |
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NMR validation set at product certification levels. |
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Models are not as robust. That is, a gasoline blending model will not predict a diesel fuel as accurately as a more broad based model. |
For more information on this topic please contact:
Manager, Process and Analytical NMR Services
Process NMR Associates LLC,
87A Sand Pit Rd
Danbury, CT 06810, USA
Tel: (203) 744-5905