ENGR 2210: Principles of Engineering. Even though the name may sound like a theory-based engineering course, the course catalog description states “students will work in small multidisciplinary teams to design and to build a mechatronic system of their own choosing.” The first third of the semester consists of hands-on lab experience, and the remainder of the semester is for an intensive collaborative project. I took Principles of Engineering (POE) last fall semester and it’s one of Olin College’s required courses to graduate; Olin is entirely an engineering school.
We began the course with a handful of labs to become acquainted with Microchip’s PIC18F2455 microcontroller, which I’ll simply refer to as a PIC, short for programmable intelligent computer. Because C programming is not a prerequisite, students without C experience became proficient in C by writing programs that are compiled and flashed onto the PIC. This method of do-learn is what many Olin professors and students call “spiral learning” – the process of not necessarily understanding (and possibly struggling) learning a topic or skill, but then when returning and using it again, having a deeper understanding than if explicitly initially instructed.
Before midterms even started, teams of roughly 3 to 5 students were formed around project ideas and we began working on our final projects. The only requirements for the projects were that it must have a non-trivial electrical and mechanic system and that the college would cover up to $350 of supplies for each team. The professors reviewed the projects primarily for feasibility and difficulty – usually ensuring that the project is not too difficult.
I was on a team of three and we ventured to build a mechatronic player piano. It was an adventure that I’ll save for a future post.
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.