R
Reme101
Hi Everyone,
I have a few questions where I would like to see what the industry consensus is for working with these problems.
Working with validations, sometimes a distribution can be identified and accepted at DOE and used through to PQ successfully.
However on occasion, we get 2 runs in a PQ normal and one run for example non-normal which is not following the historical data.
Usually we perform an investigation, has anything changed between runs, set up of the machine, material, inspection equipment etc. If we don't find anything unusual we will repeat the run.
I'm wondering if there is an alternative accepted approach for working with non-normal data when the process is typically normal?
Looking forward to hearing the input.
I have a few questions where I would like to see what the industry consensus is for working with these problems.
Working with validations, sometimes a distribution can be identified and accepted at DOE and used through to PQ successfully.
However on occasion, we get 2 runs in a PQ normal and one run for example non-normal which is not following the historical data.
Usually we perform an investigation, has anything changed between runs, set up of the machine, material, inspection equipment etc. If we don't find anything unusual we will repeat the run.
I'm wondering if there is an alternative accepted approach for working with non-normal data when the process is typically normal?
Looking forward to hearing the input.