Combining Taguchi Methodology

1. Combining Taguchi Methodology with to Evolutionary Operation Improve Optimal Design Settings

2. Competitiveness in Industry the use of DOE Taguchi Methodolgy EVOP Introduction

3. 1985 Hunter : Discuss Taguchi Philosophy 1985Kackar: Tile Industryadding lime 1% to 5% help significantly improve the variation in size of tile. 2000 Taguchi: Robust Engineering application at Ford, Nissan, NASA, etc. Literature Review

4. Easy to Implement Do not need much of Statistics Backgroud Small no. of Experimental Runs Benefits of TAG

5. Drawbacks of TAG • Good Settings when the design points consist of Optimal values • Inappropriate starting range may mislead the solution.

6. Taguchi Experiment

8. Calculation of S/N Ratio

11. Evolutionary Operation Box & Draper (1969) x2 (2) (4) (0) (1) (3) x1

12. Benefits of EVOP • Easy to Implement • Can be performed On-Line (Plant Scale) • Small no. of Experimental Runs

13. Drawbacks of EVOP • May not improve easily if the variation is too small • Inappropriate starting range may result in high numbers of cycle.

14. Research Methodolgy Start Select Models Find Optimal values via WinQSB

15. Find Optimal values via Taguchi Method Calculate DTAG = | Y TAG - Y opt | Improve Optimal values via EVOP

16. Calculate DEVOP = | Y EVOP - Y opt | DEVOPvsDTAG Draw Conclusion

17. Models

19. Surface Finish (Prob. 5-2 p.211) Copper (Prob. 5-5 p.212) 32 Chemical Process (Prob. 9-6 p.388) Industrial Applications(DOE, Montgomery 5th edition,1999)

20. Fitting Models via WinQSBBox & Wilson (1951)

22. Optimum Soln via WinQSB

25. Initial Settings for model 1

26. Solutions from TAG

29. Comparison

32. Summary • EVOP has improved the solution for the total of 9 models and all case studies. • Model with Polynomial Degree 6th cannot be improved by EVOP

33. EVOP is bettter for Polynomial degree 2nd - 4th than Polynomial degree 5th or 6th.

34. Further Study • Limitation of EVOP: concern 2-3 variables • Model with more than 3 variables