In 1969, when I was a plebe (freshman) at West Point, engineering was the required course of study and a slide rule was standard issue. In my first engineering class there was a 10-ft-long working slide rule hanging from the ceiling to aid in instruction. I never once thought my slide rule was going to solve an engineering problem I was facing; it would just make my calculations easier. I also never thought my handheld calculator was going to solve my engineering problems, but now I could more easily solve many more types of engineering problems without having to resort to punch cards and mainframe computers. However, my ability to estimate orders of magnitude was diminished. The early 1980s saw the rise of the personal computer and now every entering engineering student at most universities has a laptop computer fully loaded with the latest technical software. When confronted with a problem before the desktop/laptop computer era, the engineering student would develop the problem solution by hand with pencil, paper and much thought and only then was the slide rule or calculator taken out of its case or, if needed, a computer program written and cards punched. Today, entering freshmen have the perception that the solutions to engineering problems are somewhere in the computer and just have to be found, when in fact the solutions are where they have always been — in the minds of the engineers!
Freshman engineering students in all disciplines usually take some computing class — usually C, Java or MATLAB programming — hopefully learn about pseudo code and flowcharting and then solve some simple problems developed primarily to make use of some features of the programming language just learned. In engineering practice today, only in special situations will an engineer write a computer program to solve a problem. Even in real-time computer applications, code generation programs are widely available. Most engineering problems today are solved using pre-written programs in MATLAB or LabVIEW, for example. Wouldn't it be most valuable if freshman engineering students were exposed to the types of engineering problems real engineers in any discipline face 90 percent of the time and appreciate the software used to solve these problems and how to use that as a tool? It certainly would put their laptop computer, computer software and computer programming in proper context. Aside from e-mail, word processing, presentation development, website creation and Internet use, what are the main types of problems practicing engineers in all disciplines solve using their computers, either with pre-programmed software or by writing their own code? The answer should help identify what our students should see in their freshman year.
My list starts with a basic assumption. All engineers must be able to model multidisciplinary engineering physical systems; predict how they will behave when built; optimize their design; validate their predictions and designs with engineering measurements; and see a design through to prototyping and manufacturing, with sustainability considerations paramount throughout. Based on this assumption, my list includes:
Solving linear and nonlinear algebraic equations.
Numerical simulation of time-dependent ordinary differential equations.
Numerical simulation of partial differential equations using MATLAB or some finite-element analysis software.
Kevin C. Craig, Ph.D., Robert C. Greenheck Chair in Engineering Design & Professor of Mechanical Engineering, College of Engineering, Marquette University. For more mechatronics news, visit www.mechatronicszone.com.
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.
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.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
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.