1 / 10

The One-Quarter Fraction of the 2 k

The One-Quarter Fraction of the 2 k. The One-Quarter Fraction of the 2 6-2. Complete defining relation: I = ABCE = BCDF = ADEF. The One-Quarter Fraction of the 2 6-2. Uses of the alternate fractions E = ± ABC, F = ± BCD

fleta
Download Presentation

The One-Quarter Fraction of the 2 k

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The One-Quarter Fraction of the 2k

  2. The One-Quarter Fraction of the 26-2 Complete defining relation: I = ABCE = BCDF = ADEF

  3. The One-Quarter Fraction of the 26-2 • Uses of the alternate fractions E = ±ABC, F = ±BCD • Projection of the design into subsets of the original six variables • Any subset of 4 factors of the original 6 variables that is not a word in the complete defining relation will result in a full factorial design • Any subset of 4 factors of the original 6 variables that is a word in the complete defining relation will result in a replicated one-half factorial design • Consider ABCD (full factorial) • Consider ABCE (replicated half fraction) • Consider ABCF (full factorial)

  4. Design Matrix of Example 8-4 • Injection molding process with six factors

  5. Large effects: A, B, and AB (Ockham’s razor) The process is sensitive to temperature (A) if the screw speed (B) is at the high level => both A and B should be at the low level (reduce mean shrinkage) How about the part-to-part variability?

  6. ŷ = bo + b1x1 + b2x2 + b12x1x2 = 27.3125 + 6.9375x1 + 17.8125x2 + 5.9375x1x2 e = y - ŷ

  7. Residual plots indicate there are some dispersion effects, which can be quantified by an analysis of residuals.

  8. Example 8-4 Factor C has a large dispersion effect. Its location effect is not large, so its level can be set to low to reduce variation.

  9. Projection onto a cube in A, B, and C (Example 8-4) 26-2 -> 23 (n=2) B=low results in low values of average part shrinkage C=low produces low part-to-part variation => B-C- 10

More Related