by Oliver Yu
I was hired into a group called Manufacturing Sciences, which reported into the local technology department that reported to the plant manager. My job was to observe the large-scale cell culture process and analyze the data.
Our paramount concern was quantifying process variability and trying to reduce it. The reason, of course, is to make the process stable so that manufacturing is predictable. Should special cause variability show up, the job was to look for clues to improve volumetric productivity.
The circle of life (with respect to data) looks like this:
Data and observations come from the large-scale process. We applied statistical process control (SPC) and statistical analysis like control charts and ANOVA. And from our analysis, we are able to implement within-license changes to make the process more predictable. And should the special cause signals arise, we stood ready with more statistical analysis/methods to increase volumetric productivity.
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