J
JayGreen
I have only 15 samples of a fuse available. Each fuse is 6" long, containing a type of powder. The object is to prove with high reliability and confidence (~99%R/95%C) that the powder will burn continuously and not snuff or fizzle out.
To achieve this reliability and confidence is difficult. The only response seems to be pass/fail. Logistic regression seems a logical choice, but the independent variable may be difficult to decide upon (say, % binder, or amound of another ingredient). Even if the independent variable is determined, samples are limited to 15. With logistic regression, proving margin gets one the most bang for the buck, but replication at numerous inputs would be needed for most high reliabilities & confidence combinations.
DOE doesn't appear an option. I'd think the high reliability & confidence would be more difficult to prove out with multiple factors changing.
I see engineering confidence being shown, but not statistical confidence.
I know this is a bit vague, but I'd appreciate any ideas. There will likely be 1 or 2 input factors that can change.
More could be addressed (long term vs. short term lot production; homogeneity of the powder, more), but this seems enough for now.
Appreciate your input.
To achieve this reliability and confidence is difficult. The only response seems to be pass/fail. Logistic regression seems a logical choice, but the independent variable may be difficult to decide upon (say, % binder, or amound of another ingredient). Even if the independent variable is determined, samples are limited to 15. With logistic regression, proving margin gets one the most bang for the buck, but replication at numerous inputs would be needed for most high reliabilities & confidence combinations.
DOE doesn't appear an option. I'd think the high reliability & confidence would be more difficult to prove out with multiple factors changing.
I see engineering confidence being shown, but not statistical confidence.
I know this is a bit vague, but I'd appreciate any ideas. There will likely be 1 or 2 input factors that can change.
More could be addressed (long term vs. short term lot production; homogeneity of the powder, more), but this seems enough for now.
Appreciate your input.