Yep, absolutely still done, and for the same reason (in my experience), especially with Intel, and other companies who develop their own processes. What typica

Yep, absolutely still done, and for the same reason (in my experience), especially with Intel, and other companies who develop their own processes. What typically happens is that engineers do the best they can before release to model the process and experiment with building devices at different process "corners". This gives an idea of what the distribution of different electrical parameters will look like over the range of expected process variation (logic levels of FETs, sheet resistances, etc. etc.). Obviously this data is imperfect, because there are a TON of steps in a modern semiconductor process, and a TON of variables in each one. (For example, I worked on Ion Implanters, and we recorded hundreds of variables for our customers during the run, from vacuum levels, to gas dosages to voltages and currents in the various accelerator stages). As parent said, there is another group, who IMO are probably the original "big data" folks, usually called manufacturing or process engineers. They monitor the yields, binning and specific electrical measurements of all the wafers and parts coming off the line, along with process data for all the nanufacturing steps the wafer has gone through. These guys do the black magic of figuring out what needs to be tweaked in the process. At the higher levels it involves a mix of knowledge -- not only statistics and optimization, but also the semiconductor physics of how these parts actually operate, (since experiments can get expensive, you want to justify the knobs you are going to tweak!)