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4. Process Modeling
4.5. Use and Interpretation of Process Models


How can I optimize my process using the process model?

Detailed Information on Process Optimization Process optimization using models fit to data collected using response surface designs is primarily covered in Section 5.5.3 of Chapter 5: Process Improvement. In that section detailed information is given on how to determine the correct process inputs to hit a target output value or to maximize or minimize process output. Some background on the use of process models for optimization can be found in Section of this chapter, however, and information on the basic analysis of data from optimization experiments is covered along with that of other types of models in Section 4.1 through Section 4.4 of this chapter.
Contents of
Chapter 5
Section 5.5.3.
  1. Optimizing a Process
    1. Single response case
      1. Path of steepest ascent
      2. Confidence region for search path
      3. Choosing the step length
      4. Optimization when there is adequate quadratic fit
      5. Effect of sampling error on optimal solution
      6. Optimization subject to experimental region constraints
    2. Multiple response case
      1. Path of steepest ascent
      2. Desirability function approach
      3. Mathematical programming approach
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