
When I joined Hewlett-Packard in 1988, I was assigned to a team that was working on a design for manufacturability manual for printed circuit board designers.
Our primary objective was to provide performance and cost information that could be used to guide decisions about different design options.
My favorite project during that time was a predictive model to estimate the manufacturing yield of a PCB design based on a composite “complexity” metric.
Because we were an internal supplier, I was able to look at the actual lot yields for hundreds of active part numbers with known design parameters, so it seemed like a fairly straightforward exercise to experiment with different regression models to find an optimum fit between complexity and yield.