Reducing Variability With DOE
A Case Study On Propagation of Error (POE)

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ark J. Anderson and Patrick J. Whitcomb

Page 1 > Minimizing Propagation of Error (POE) from Varying Inputs

Page 2 > A Case Study On POE

References
1. Anderson, M.J., Whitcomb, P.J., "Design Experiments that Combine Mixture Components with Process Factors," Paint and Coatings Industry, November 2000.

2. Anderson, M.J., Whitcomb, P.J., "Computer-Aided Tools for Optimal Mixture Design," Paint and Coatings Industry, November 1999.

3. "Making Six Sigma Benefits Stick," Chemical Week Vol. 163, No. 19. p. 40, 5/9/2001.

4. Adsit., D. "Six Sigma's Intangibles," Spring 1999 Leadership Report, Rath and Strong.

5. WR Medical Electronics Company, 123 N. 2nd St., Stillwater, MN 55082.

6. Helseth, et al, Design-Expert, Version 6 for Windows, Stat-Ease, Inc, Minneapolis, 2001 ($995).

7. Anderson, M.J., Whitcomb, P.J., "Optimization of Paint Formulations Made Easy with Computer-Aided Design of Experiments for Mixtures," Journal of Coatings Technology, Volume 68, Number 858, July 1996, pages 71-75.

Appendix: Data For Powder-Coating Study

Comb.	A: Epoxy	B: Ca	C: Ti	D: Bake temp	E: Bake time	Adhesion	Hardness
	wt %	wt %	wt %	deg F	min
1	40	20	30	360	25	112.1	115
2	35	30	25	360	25	116.4	103
3	38.3	23.3	28.3	360	25	156.0	72
4	45	20	25	360	25	245.0	167
5	35	20	35	320	15	169.0	140
6	45	20	25	320	15	174.8	19
7	35	30	25	320	15	126.8	130
8	35	20	35	320	35	87.2	57
9	45	20	25	400	15	339.3	294
10	35	30	25	400	35	146.6	119
11	35	20	35	400	15	213.0	143
12	45	20	25	320	35	327.0	142
13	35	30	25	400	15	102.2	52
14	35	20	35	400	35	146.1	153
15	45	20	25	400	35	356.9	241
16	35	30	25	320	35	144.2	123
17	35	20	35	320	25	152.9	92
18	35	20	35	360	30	195.7	127
19	45	20	25	360	35	392.5	226
20	35	25	30	320	15	164.6	102
21	40	25	25	320	15	101.0,  75.2	11,   17
22	40	20	30	320	15	106.9	19
23	35	25	30	320	35	183.9	109
24	40	25	25	320	35	149.7, 139.7	89,   78
25	40	20	30	400	15	208.7	163
26	35	25