Template:WebNotes/DOEGeneral Full Factorial: Difference between revisions
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In a general full factorial design, each factor can have a different number of levels. Both qualitative and quantitative factors can be analyzed. This design is used when the number of factors is small (<5) and the number of total runs in the experiment is not large. Otherwise, a fractional factorial design such as | In a general full factorial design, each factor can have a different number of levels. Both qualitative and quantitative factors can be analyzed. This design is used when the number of factors is small (<5) and the number of total runs in the experiment is not large. Otherwise, a fractional factorial design such as two level fractional factorial or Taguchi OA should be used. | ||
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| [http://help.synthesisplatform.net/doe9/general_full_factorial_designs.htm | | [http://help.synthesisplatform.net/doe9/index.htm#general_full_factorial_designs.htm V9 Help] or [http://help.synthesisplatform.net/doe10/index.htm#general_full_factorial_designs.htm V10 Help] | ||
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| [http://reliawiki.com/index.php/General_Full_Factorial_Designs the theory textbook...] | | [http://reliawiki.com/index.php/General_Full_Factorial_Designs the theory textbook...] | ||
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| [http://www.reliasoft.com/doe/examples/rc5/index.htm application example(s)...] | |||
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Latest revision as of 20:48, 28 April 2015
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| General Full Factorial Design
In a general full factorial design, each factor can have a different number of levels. Both qualitative and quantitative factors can be analyzed. This design is used when the number of factors is small (<5) and the number of total runs in the experiment is not large. Otherwise, a fractional factorial design such as two level fractional factorial or Taguchi OA should be used. |
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