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Analysis and Optimization of Second Order Models

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 105)

As it can be seen from previous chapters, experimental design and process optimization are two intertwined tasks. Sequences of designed experiments are frequently run to optimize a process. In traditional RSM practice, such sequences are often first order designs with center runs that allow to test for curvature. If curvature is detected, second order experimental designs and models are used as a local approximation for process optimization. In this chapter we look at optimizing a second order model. Designs used to fit these models are described in Chapter 5.

Keywords

Stationary Point Controllable Factor Order Model Central Composite Design Desirability Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

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