I have a process that has 100's of fixture
for a lot I use some fixtures say 10-25 fixtures
for a lot I know # good pcs from lot, number of bad pcs, (lot size) as well as fixtures used HOWEVER I am not recording fixture to part rejected.
trying to find method to track this down for old data [Yes - I know I need to fix my data collection going foreword]
but if I have a lot of 10 and 2 were bad and I weight all 10 fixtures with a .20 POTENTIAL defect
then for a second lot of 15 with 6 defective I take those fixtures and weight them with a .40 potential defective
then after lots of lots 300+ I sum all the potential defective by a fixture and divide by number times fixture used
will this give me a fair good indication of the problem and not problem fixtures
If the distribution of the final proportion all the fixtures 100 fixture & 100 proportions (average potential defective) is normally distributed
this seems to be a good method, I ran a model and it was significant
so I think this would work
thought , comments, etc.
or if there is a standard or statistical test for this method I would appreciate the name so I can look it up
Thanks in advance,
for a lot I use some fixtures say 10-25 fixtures
for a lot I know # good pcs from lot, number of bad pcs, (lot size) as well as fixtures used HOWEVER I am not recording fixture to part rejected.
trying to find method to track this down for old data [Yes - I know I need to fix my data collection going foreword]
but if I have a lot of 10 and 2 were bad and I weight all 10 fixtures with a .20 POTENTIAL defect
then for a second lot of 15 with 6 defective I take those fixtures and weight them with a .40 potential defective
then after lots of lots 300+ I sum all the potential defective by a fixture and divide by number times fixture used
will this give me a fair good indication of the problem and not problem fixtures
If the distribution of the final proportion all the fixtures 100 fixture & 100 proportions (average potential defective) is normally distributed
this seems to be a good method, I ran a model and it was significant
so I think this would work
thought , comments, etc.
or if there is a standard or statistical test for this method I would appreciate the name so I can look it up
Thanks in advance,