Exploring Best Practices in the Design of Experiments - JMP

More documents

Recommendations

Info

Problem-Driven Paradigm • With good software, approach easy to use and to teach. • One, unified approach to (nearly) all design problems: 1. Describe your responses 2. Describe your factors 3. Describe your objectives (model terms) 4. Describe your constraints and budget (n) 5. Press button to create the design 6. Check diagnostics, do sensitivity analysis 7. Manually alter as with classical 4/29/2013 24
Problem-driven paradigm pros, cons: Pros 1. Design tailored to problem 2. One unified approach to nearly all problems Cons 1. No textbook advocating computer-aided design 2. Technical concerns from the stats community 4/29/2013
Page 1 and 2: Exploring Best Practices in the Des
Page 3 and 4: Overview • Where have we been?
Page 5 and 6: Where have we been? • 10 th Centu
Page 7 and 8: Where have we been? • James Lind,
Page 9 and 10: Where have we been? • Gergonne: 1
Page 11 and 12: 1920’s-1950’s: Orthogonality is
Page 13 and 14: 1950s: Baby steps away from orthogo
Page 15 and 16: Shift to problem-driven design (70s
Page 17 and 18: Paradigms for DOE Classical: • Fi
Page 19 and 20: Classical design paradigms pros, co
Page 21 and 22: What DOE Expertise (continued)? •
Page 23: New Paradigm: Problem-driven design
Page 27 and 28: Example 1: Extracting food solids f
Page 29 and 30: Knowledge Requirements: • Main ef
Page 31 and 32: Here’s how it’s done: 4/29/2013
Page 33 and 34: Example 2: Maximize recall of TV co
Page 35 and 36: Contrast: Problem-Driven Design App
Page 37 and 38: Example 3: Supersaturated Designs P
Page 39 and 40: You can’t do that! 1. Design matr
Page 41 and 42: FF designs are supersaturated desig
Page 43 and 44: Problem-Driven Design Approach Know
Page 45 and 46: All experimental Not all main facto
Page 47 and 48: Color-coded correlation matrix has
Page 49 and 50: Example 4: Sheet Aluminum Rolling M
Page 51 and 52: But there is a problem: We have con
Page 53 and 54: DOE to the rescue! • Result: When
Page 55 and 56: Confession of a Text Book Author
Page 57 and 58: Recent Paper---My Conversion 4/29/2
Page 59 and 60: Example 5: Corrosion resistance of
Page 61 and 62: Actual Corrosion Resistance DOE Who
Page 63 and 64: Contrast with ordinary DOE In usual
Page 65 and 66: Analysis depends on the randomizati
Page 67 and 68: Take-Aways 1. Always consider runni
Page 69 and 70: What’s driving the software? Opti
Page 71 and 72: Lots of work in Model Robust and Mu
Page 73 and 74: Multi-objective designs: six-factor
Page 75 and 76:
Alias Matrix of Plackett-Burman des
Page 77 and 78:
Turns out there is: Six foldover pa
Page 79 and 80:
Definitive Screening Design for 6 f
Page 81 and 82:
Now generalize this structure for m
Page 83 and 84:
Conference Matrices & Telephony Fro
Page 85 and 86:
Here the amazing result: Form the a
Page 87 and 88:
Impact? A break-through solution fo
Page 89 and 90:
Impact? From the conclusions: “De
Page 91 and 92:
Upshot - Definitive Screening Desig
Page 93 and 94:
BUT!…a limitation DSDs can only b
Page 95 and 96:
Example 6: Extracting food solids f
Page 97:
So, what are the current best pract
show all

Exploring Best Practices in the Design of Experiments - JMP

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?