@Kevin Craig, I quite like your last statement "This type of work should be considered fundamental for all engineers; it is what differentiates model-based design engineers in the 21st century."
In your own classes, do you prepare your students to have a competency to be "model builders" or to be efficient "model users"? I can easily see this model being delivered along with the MEMS device by the OEM as well as the OEM being expected to model and experimentally verify the performance of their product.
Do your students differentiate into "users" and "modelers", or you push for equal facility in both modes?
Consider the products that now use MEMS-based gyroscopes: automotive stability control; Wii products; Nintendo products; iPhones; iPads; image-stabilization cameras; and RC helicopters, just to name a few. Those few categories probably represent about 50 million products a year, maybe more. So, as you say Kevin, it's handy, maybe even critical, for a healthy percentage of model-based design engineers to know the underlying math.
I hope he's teaching them to be model builders. I have seen far too many cases of model users depending on inappropriate models because they don't understand their limits. Even if a model builder doesn't build his own models all the time, a quick perusal of the derivation will tell him what the assumptions are. Then he will know whether he is operating outside the model or not. A mere model user won't have that insight.
Are they robots or androids? We're not exactly sure. Each talking, gesturing Geminoid looks exactly like a real individual, starting with their creator, professor Hiroshi Ishiguro of Osaka University in Japan.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
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.