These are excellent points and provide guidelines that serve as a checklist for engineers and designers.I do think that we are aided today with solid modeling and computational methods that greatly shorten the design process, if used.One of the most fascinating technologies now in practice is computational engineering.This science combines engineering, mathematics and solid modeling to provide predictive solutions to designs that would generally require typical "cut and try" techniques.If I were younger (maybe much younger) and had it to do all over again, I definitely would explore all of the options with this technology.Bob Jackson, PE
I think the most salient definition is the one on over design: What overeating does to a person, over-designing does to a product. The brilliance of Steve Jobs, who was not an engineer, is that he stood as a bulwark against overdesign. I suspect Apple's products will now suffer from overdesign as a consequence of his absence from the design process.
Ratsky: I couldn't agree more. Reality -- in the form of cost, longevity, reliability and ease of use -- are my keys to buying a product. In a sense, all of those could be traced back to cost, since unreliable products that wear out early tend to cost more in the long run.
The trick to Apple's success may be a simple as paying attention to the principles on this list. Apple's products pretty much tick off these considerations. Apple really hasn't come out with anything new, but they've done a great job of executing this list of engineering principles.
I don't know if it counts toward looking attractive. But often how tough a device looks has something to do as well. The average consumer will shy away from a design that looks fragile, even if it can do the job. If it looks flimsy it might now sell.
Reality is always at the very top of my list. It includes so many of the other items as representing aspects of the real world of engineering and design. Economics (costs and cost/benefit ratio), legal concerns, constraints of all kinds, recognition of the limits of models and simulations, market considerations, and so forth. Dreaming is a starting point; implementation is where the rubber hits the road, and that will succeed only with an approach recognizing all of these real-world aspects. This is one of the greatest shortcomings of engineering education today: students are not taught about the real world (neglect of so many fundamentals, especially physics and related areas like thermodynamics).
Although sketches are useful, it is perilous to begin a design with sketches before having created a full list of all the technical requirement Specifications. A design cannot be great unless it is Specified, Tested and validated against those Specs. I would classify sketches under I for Imagination or R for Realization.
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.