There is rarely acknowledged connection between yield and capacity in the sense that in many cases the most direct way to fix a yield problem is to restrict certain processes to go through a limited subset of available equipment. I know that we resorted to this technique many times in my past doing yield enhancement. By artificially constraining the toolset or dedicating specific pairings of tools, you get less variability in the mfg parameters and get more predictable yield. You hide the yield problem in a capacity problem.
An interesting point for this discussion: AMD paid dearly for the right to have 28-nm products manufactured at other foundries, yet 28-nm capacity is constrained. I assume that before AMD took that step they made sure they could get the capacity they needed.
Better get those 28-nm capacity, if you're going to hit revenue goals. I wonder what's the reason for the shortage? High in demand?
Member of the Patexia Semiconductor Group (http://bit.ly/HeyQJO)
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.