I wanted to find out how much attentions validation time should be planned for DOE's (Design Of Experiment).
Testplaning - there are planning factors that need attention on repeatability over multi-runs, VT's and other varriables. Those thoughts will add or reduce validation time, resorces, and other infrustructure. I rely on DOE's to build statistics and modles to help focus on worst case areas. This gives many advantages like varriablility, repeatability, sensativity to help focus on more or focus less on particular areas. If you can not test milions of chips, platforms, and devices you need to plan a statistical target on exceptable margins. You can test ever thing so how do you plan and take some risks.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.