N
NotoriousAPP
I?m trying to design an attribute MSA for a new piece of metrology equipment used to measure defects for a gold ball deposition process for semiconductor wafer processing. Each gold ball that's deposited is analyzed for certain criteria, based on the results of the analysis the ball either passes or fails. The output of the inspection will only be bins (i.e. 1,2,3,4,5,6,7) where each bin corresponds to a certain failure mode however to reduce complexity I will simply assign any gold ball that's binned a "fail" and any that are not as "passing".
I will have three wafers at my disposal. On each wafer is 86 die, on each die is 250 gold balls, each ball is inspected during the inspection step. The equipment uses automated inspection: all loading, alignment, inspection and binning is done by the equipment automatically.
Will someone please tell me if my proposal for designing and running the attribute MSA is correct:
1) Run automated inspection on one wafer to generate a list of die which the equipment believes to be passing and failing.
2) Select die which have representative defective (failing) gold ball deposition and passing gold ball deposition. Try to select die with a 1/1 ratio of good to bad parts is recommended (I believe this will be highly unlikely, a 1:20 ratio of bad:good is more likely and that's in the extreme case). I propose selecting 10 die on the wafer which are spread across the entire wafer surface.
3) Have an expert appraiser categorize each gold ball on these 10 die to confirm passing balls are indeed passing and failing balls should have failed.
4) Run wafer through the inspection 10 times. This sequence would be load, align, measure, unload, repeat.
5) Generate list for each cycle to record whether a unique gold ball passes or fails for each measurement run.
6) Use the methods described at the link below to analyze the data. In my case I'm assuming that there is only one operator (the equipment). Note, this is a first of a kind tool for a process with no process record. There is no historical or data or data from another tool to use for comparison. We're using this MSA data to accept or reject the inspection equipment from the supplier.
w w w .isixsigma.com/tools-templates/measurement-systems-analysis-msa-gage-rr/making-sense-attribute-gage-rr-calculations/
Do my methods seem sound? Any recommendations on how this could be improved?
Individual repeatibility (step 5 at link) and individual effectiveness (step 6 at link) seem straightforward to calculate since there is only one operator however this only provides repeatibility, how do I calculate reproducibility with only one equipment (equipment = operator)? Can I use the load/measure/unload sequence for the reproducibility and simply measure the wafer 3 times without load/unload sequence to gauge repeatibility?
Thanks,
Alex
I will have three wafers at my disposal. On each wafer is 86 die, on each die is 250 gold balls, each ball is inspected during the inspection step. The equipment uses automated inspection: all loading, alignment, inspection and binning is done by the equipment automatically.
Will someone please tell me if my proposal for designing and running the attribute MSA is correct:
1) Run automated inspection on one wafer to generate a list of die which the equipment believes to be passing and failing.
2) Select die which have representative defective (failing) gold ball deposition and passing gold ball deposition. Try to select die with a 1/1 ratio of good to bad parts is recommended (I believe this will be highly unlikely, a 1:20 ratio of bad:good is more likely and that's in the extreme case). I propose selecting 10 die on the wafer which are spread across the entire wafer surface.
3) Have an expert appraiser categorize each gold ball on these 10 die to confirm passing balls are indeed passing and failing balls should have failed.
4) Run wafer through the inspection 10 times. This sequence would be load, align, measure, unload, repeat.
5) Generate list for each cycle to record whether a unique gold ball passes or fails for each measurement run.
6) Use the methods described at the link below to analyze the data. In my case I'm assuming that there is only one operator (the equipment). Note, this is a first of a kind tool for a process with no process record. There is no historical or data or data from another tool to use for comparison. We're using this MSA data to accept or reject the inspection equipment from the supplier.
w w w .isixsigma.com/tools-templates/measurement-systems-analysis-msa-gage-rr/making-sense-attribute-gage-rr-calculations/
Do my methods seem sound? Any recommendations on how this could be improved?
Individual repeatibility (step 5 at link) and individual effectiveness (step 6 at link) seem straightforward to calculate since there is only one operator however this only provides repeatibility, how do I calculate reproducibility with only one equipment (equipment = operator)? Can I use the load/measure/unload sequence for the reproducibility and simply measure the wafer 3 times without load/unload sequence to gauge repeatibility?
Thanks,
Alex