I totally agree that the education system for engineers is not that practicle as it should be .In our universities students are just bombarded with notes , lectures, numericles and so on instead they should be given practicle and hands on experience on different projects. They should be asked to make different projects because while making these projects students face alot of difficulties and by trial and error method they study alot .Our engineers gets graduated from universities with very good GPAs but unfortunately they exactly dont know what they will be required to do in there professional lifes .
In one of our recent stories, the author of this article (Ray Almgren), talked about the difficulty of teaching science and engineering to students. "Hard is fine," he said. "But we also want them to find their classes interesting." In FIRST and Lego Mindstorms, mentioned here, we see the embodiment of that spirit.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
Using Siemens NX software, a team of engineering students from the University of Michigan built an electric vehicle and raced in the 2013 Bridgestone World Solar Challenge. One of those students blogged for Design News throughout the race.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
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.