4.
Process Modeling
4.1.
Introduction to Process Modeling
4.1.3.
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What are process models used for?
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Three Main Purposes
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Process models are used for four main purposes:
- estimation,
- prediction,
- calibration, and
- optimization.
The rest of this page lists brief explanations of the different
uses of process models. More detailed explanations of the uses
for process models are given in the subsections of this section
listed at the bottom of this page.
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Estimation
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The goal of estimation is to determine
the value of the regression function
(i.e., the average value of the response variable),
for a particular combination of the values of the predictor variables.
Regression function values can be estimated for any combination of
predictor variable values, including values for which no data have been
measured or observed. Function values estimated for points
within the observed space of predictor variable values are sometimes called
interpolations. Estimation of regression function values for points outside
the observed space of predictor variable values, called extrapolations,
are sometimes necessary, but require caution.
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Prediction
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The goal of prediction is to determine either
- the value of a new observation of the response variable, or
- the values of a specified proportion of all future observations
of the response variable
for a particular combination of the values of the predictor variables.
Predictions can be made for any combination of predictor variable values,
including values for which no data have been measured or observed.
As in the case of estimation, predictions made outside
the observed space of predictor variable values
are sometimes necessary, but require caution.
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Calibration
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The goal of calibration is to quantitatively relate measurements made
using one measurement system to those of another measurement system.
This is done so that measurements can be compared in common units or to
tie results from a relative measurement method to absolute units.
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Optimization
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Optimization is performed to determine the values of process inputs that should be
used to obtain the desired process output. Typical optimization goals
might be to maximize the yield of a process, to minimize the processing
time required to fabricate a product, or to hit a target product
specification with minimum variation in order to maintain specified tolerances.
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Further Details
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- Estimation
- Prediction
- Calibration
- Optimization
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