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.
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© 2007 Springer Science+Business Media, LLC
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(2007). Analysis and Optimization of Second Order Models. In: Process Optimization. International Series in Operations Research & Management Science, vol 105. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71435-6_4
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DOI: https://doi.org/10.1007/978-0-387-71435-6_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-71434-9
Online ISBN: 978-0-387-71435-6
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