This is all very detailed and complex. Most engineers I know have not used math beyond algebra or geometry in their day job careers. However, when faced with a problem, most engineers know where to look up info like the above. (The old cliche)
I think taking time to write down the model can help insure that we don't miss one important detail which is ususally what happens when we do it in our head.
Modeling of physical systems was not taught in school. I claim it's an art. When I have performed this "art", only other engineers who were intelligent enough to have done it themselves have understood. Experiance? No. As a new grad years ago, I had to model a motor driver / antenna / radar system. I had no experiance but I pulled it off. It required understanding that a derivative is the change of parameter A w.r.t. parameter B. Hmm, I couldn't understand why that concept was so difficult to grasp by others. One of the closed-loop parameters was the angle of the target. This was in radians. Another parameter was the electrical phase lag angle of the motor current. This was in degrees. "You can't mix degrees with radians" some people shouted." I remember this vividy from decades ago. They were actually angry. "You certainly can", I replied. Luckily for this new grad, there were other engineers in the room who understood simple principles of math and the model was accepted.
I agree that the ability to physically model systems is a valuable skill. Having a good physical model can shed light on different areas of the design and accelerate system optimization and solution break throughs.
These skills are quite complicated to master and I think the main keys are gaining experience through practice and also having a good mentor.
The ability to produce an adequate model is very useful, but accuracy is omportant. One additional advantage of producing the model is that it serves as a "reality check" as it helps to avoid missing pieces and details.
BUT attaching real numbers to a model does get quite tedious, while some of them can be looked up, othhers must be calculated.THAT can be very tedious indeed, I have found in the past.
I agree. In many cases, the real numbers needed for these equations must be empirically determined through experimental measurement (and that can get quite tedious, time-consuming and expensive when a project is on a fast-track). Sometimes engineers want to take the time to run experiments to properly model the system, but management may not have the patience or commitment to allocate the needed resources and or allow the time to do it right.
Being able to procede without doing the modeling, or being able to do the modeling without doing all of the math, and getting it right, is the vaue of experienc, at least potentially the value. Knowing where you can't get away with assumptions is the biggest value of experience.
Interesting discussions. As a mechanical engineer who has made the transition into marketing and product development I can say that modeling (i.e. the mathmatical representation of the real world) is not confined to physical systems. Buying behavior, pricing scenarios, market response to financial pressures all lend themselves to modeling. Having the experience to look for these associations and the understanding to apply the correct modeling dynamics comes from my engineering background.
Scott, well said. Too many times, our engineering team delivered our product design on time, on cost and on spec. but the product didn't sell as well as anticipated. Why? Because the buying behaviors as you stated below were also not properly or accurately 'modeled'.
Gigabit and PoE are two networking technologies moving ahead in tandem as industrial users power remote Ethernet devices such as IP security cameras at 1,000 Mbps over existing CAT5 cable.
New disc magnet motors fit into the design trend of stepping up to closed loop performance while maintaining the cost advantage of stepper motor technology.
At the Design News webinar on June 27, learn all about aluminum extrusion: designing the right shape so it costs the least, is simplest to manufacture, and best fits the application's structural requirements.
A new battery design, which replaces lithium with abundant and low-cost elemental sulfur, is still in its nascent stages but shows real promise for giving batteries more energy potential.
From Dell / Intel® New Paradigms in Design Work Scott Hamilton, vertical market strategist for Dell Precision workstations, 5/2/2013 5
Early in my career, I worked as a draftsman and remember the days of drawing on vellum with numbered pencils and Mylar with plastic lead. This was a fun experience in the sense that I ...
I've been using workstations for more than 10 years and love finding ways to get more performance from my system. With demanding professional applications that require more power each ...
A lasting memory from my first job as an engineer in an auto assembly plant is standing on hard concrete at six in the morning, vending-machine coffee clutched in hand, listening to ...
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 radio show will show what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.
To save this item to your list of favorite Design News content so you can find it later in your Profile page, click the "Save It" button next to the item.
If you found this interesting or useful, please use the links to the services below to share it with other readers. You will need a free account with each service to share an item via that service.