Information Technology Reference
In-Depth Information
relied on PLS projection to latent structures regression (Berntsson et al.,
2002). In this method, many collinear spectra variables are transformed
to a small number of new orthogonal variables called PLS components,
which contain the systematic information in the spectra that gives the
best regression model.
The infl uence of critical granulation parameters (fl ow rate of
granulation liquid and the granulation end point moisture content) on
median particle size was studied using MLR (Rantanen et al., 2000). The
regression model for two independent variables was fi rst presented in the
second-order polynomial form:
[4.20]
where
a
−
f
are model coeffi cients. The model was then simplifi ed with a
backward selection technique, which means that terms were removed
one by one, so that only the signifi cant terms were included in the fi nal
model.
Prediction capability of multivariate methods (PLS and ANN) was
performed for in-line moisture measurement during fl uid bed granulation
(Rantanen et al., 2001). The back-propagation (BP) neural network
approach was found to have more predictive power with the independent
test data.
The PLS method was also used for quantitative analysis of fi lm coating
in fl uidized bed process by in-line NIRS (Andersson et al., 2000).
Application of NIR in real-time release in tablet manufacturing, on
the basis of multivariate analysis, was presented (Skibsted et al., 2007).
The authors compare statistical process control to regression models.
In the statistical model, new measurements are compared statistically to
historical data from normal operating conditions batches that provide
good quality products. Regression models were developed for instances
when a quality parameter (intermediate property or the fi nal product)
was available. The drying process in a fl uid-bed was one of the processes
studied and NIR spectra were automatically collected every half minute,
with a process refl ectance probe inserted into the reactor. As a reference
method, LOD was determined as % weight LOD for samples collected in
close proximity to the NIR probe port. The spectrum that was recorded
during the removal of the sample was assigned to the corresponding
LOD reference value. A PLS model with 3 LVs was developed, using 28
calibration spectra of 12 batches.
Many different pre-processing methods were investigated and
also wavelength selection routines were applied in order to minimize
Search WWH ::
Custom Search