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Demystifying Design of Experiments: A Practical Approach for Quick Results

Discover a new approach to Design of Experiments (DOE) that simplifies the process and provides fast results. Learn to implement five steps to change the traditional DOE method, illustrated through an example using attribute and ordinal data. This presentation challenges the reliance on computer-generated designs, emphasizes operator involvement, explains key statistical concepts without technical jargon, and showcases the importance of visual representations for effective analysis. Un-Geek the DOE process by shutting off the computer, speeding up the process, and making statistical insights more accessible through visuals.

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Demystifying Design of Experiments: A Practical Approach for Quick Results

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  1. A New Theme for Design of Experiments or How to Un-Geek the DOE Process Bill Hooper Sr. Statistical Engineer Elkay Manufacturing ASQ – CQE, CRE, CSSBB, CMQ/OE May 24, 2010

  2. Overview of Presentation • The status-quo of a DOE • Five steps to changing the status-quo for the DOE process • An example DOE with attribute and ordinal data

  3. So what is the status quo? Computer generated designs Low operator involvement/commitment Statistics! Statistics! Statistics! 4-6 months to get results 30 days for the rebound

  4. So what is not the status quo?

  5. #1 – Shut the computer off and design freehand

  6. Fraction Factorial Design • Factors: 8 Resolution: IV • Runs: 67 Replicates: 2 Fraction: 1/8 • Blocks: 2 Center pts 3 • Design Generators: F = ABC, G = ABD, H = BCDE

  7. Available Factor Designs and their Resolution III Do only if necessary Memorize!!

  8. #2: Understand Statistics without talking statistics What is an Alpha error? What is a Beta error?

  9. What the jury found guilty Not guilty He did it What really happened He did not do it

  10. #3 Eliminate the killer Alpha errors! So what is an example of an alpha error?

  11. #4 - Speed does matter (2-4 days tops)

  12. Typical fast results

  13. #5 – make it visual

  14. The defects Bowl Break Bowl wrinkle

  15. Ordinal/Attribute Data Run Analysis Breaks Bowl Wrinkle Deck Wrinkles Possible sweet spot

  16. Follow-up Runs – making it work Additional runs to define sweet spot

  17. …and it does work

  18. Un-geeking the DOE process • Shut the computer off • Understand statistics without talking statistics • Stop the Nelson Mandela errors • Speed • Make it obvious – use graphics

  19. …..the simplest DOE

  20. Bill HooperElkay Manufacturing Company

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