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Predictive Quality Indicators - Manufacture of semiconductor optoelectronic products

K

kualititaj

#1
I am the Company system and process Auditor. I work for a large electronics semiconductor company specializing in the mfg of optoelectronic products.
I have been tasked to identify leading indicators at the 'conversion process' (i.e. FOL & assy test)level which can predict potential customer problems detected in the field. (which later results in customer returns).

In my opinion the probable indicators are from SPC indicators such as Cpk, CP , Low yield triggers, COQ rel tests or maverick lots.

1) Are these good indicators?
2) Are they any other you may have come across,that have predictive properties?

Thank you for your kind consideration and help.
Regards
 
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Marc

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#2
Re: Predictive quality indicators - Manufacture of semiconductor optoelectronic produ

This is an old thread that was 'lost in the cracks'. Anyone have any thoughts on this?
 
F

flyin01

#3
Re: Predictive Quality Indicators - Manufacture of semiconductor optoelectronic produ

I am the Company system and process Auditor. I work for a large electronics semiconductor company specializing in the mfg of optoelectronic products.
I have been tasked to identify leading indicators at the 'conversion process' (i.e. FOL & assy test)level which can predict potential customer problems detected in the field. (which later results in customer returns).

In my opinion the probable indicators are from SPC indicators such as Cpk, CP , Low yield triggers, COQ rel tests or maverick lots.

1) Are these good indicators?
2) Are they any other you may have come across,that have predictive properties?

Thank you for your kind consideration and help.
Regards

This is interesting and highly relevant in your business where the product´s have a lot of highly sensitive components that can get damaged in the manufacturing process.

Please let us know a little bit on what parameters do you measure on?
Is it variable data only? How much of the process i automated and how much is manual production with attribute data (pass/fail test) performed by manual operators? If the latter is the case then high yield can be very unreliable and useless for any quality prediction. You want to be able to trust the data.

I think the key is to get a "red thread" between the tests in production and what the customer values. My experience is that first you need to understand what the customer complains about and why. Then make sure the tests in production are customer relevant. Find out if the tests fail for something that the customer doesnt care about. Also what is the perceived customer quality? Even if your measurement points are within spec the customer can still return the product. Then the requirements are wrong.

If you do not get questions sorted out it will be very hard to create any kind of prediction model to estimate the problems in the field :frust:
 
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