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5. Process Improvement
5.5. Advanced topics


What if classical designs don't work?

Reasons designs don't work Most experimental situations call for standard designs that can be constructed with many statistical software packages. Standard designs have assured degrees of precision, orthogonality, and other optimal properties that are important for the exploratory nature of most experiments. In some situations, however, standard designs are not appropriate or are impractical. These may include situations where
  1. The required blocking structure or blocking size of the experimental situation does not fit into a standard blocked design
  2. Not all combinations of the factor settings are feasible, or for some other reason the region of experimentation is constrained or irregularly shaped.
  3. A classical design needs to be 'repaired'. This can happen due to improper planning with the original design treatment combinations containing forbidden or unreachable combinations that were not considered before the design was generated.
  4. A nonlinear model is appropriate.
  5. A quadratic or response surface design is required in the presence of qualitative factors.
  6. The factors in the experiment include both components of a mixture and other process variables.
  7. There are multiple sources of variation leading to nested or hierarchical data structures and restrictions on what can be randomized.
  8. A standard fractional factorial design requires too many treatment combinations for the given amount of time and/or resources.
aided designs
When situations such as the above exist, computer-aided designs are a useful option. In some situations, computer-aided designs are the only option an experimenter has.
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