A kidney cooler, developed in the 2011 Precision Machine Design class, can be used to cool a kidney with ice slush during minimally invasive partial nephrectomies. This enables longer working times during operations. (Source: Nevan C. Hanumara, MIT)
I found this story really interesting to cover, and think this model should be replicated and promoted so more of these devices make it to the commercial market. What better than to hear directly from physicians about what they need to do their job, and get some of the best and brightest minds to develop them in collaboration? This could help get some of the most useful tools into the medical field as efficiently as possible.
I'm glad you covered this design program in your article. This need-driven project approach as a class structure teaches students so much more about real-world experiences that await them post-university than the traditional classroom approach can.
And while there are similar programs at other universities, these programs as a whole are in the minority when it comes to the teaching of engineering and design.
I know, Cabe, I can't imagine some of these things being used on patients...but hopefully they would be under anesthesia during the process! The thing is, I think there is more medical innovation than we think and I've written about some cool stuff lately...I think it's just difficult to get it out into the commercial market because of regulations and other hurdles to actual adoption. The minds and the technology are there, it's just seeing it make it to what has become a commoditized and politicized medical industry. And in my mind, it's one of the most important fields for innovation.
@Cabe: Huh? R&D spending on healthcare is much larger than R&D spending on smartphones. U.S. healthcare and life science companies spent $182 billion on R&D in 2012. That's not even counting government spending on healthcare R&D. That's just private sector spending.
Apple spent $3.4 billion on R&D in 2012, and smartphones are only part of that. Add in Microsoft ($9.8 billion) and Google ($5.2 billion), and that's still less than a tenth of healthcare R&D.
In the U.S., we spend nearly 18% of GDP ($8233 per person per year) on healthcare. I don't know about you, but I wouldn't spend that much on a smartphone.
Thank you, CLMcDade. I completely agree with you. I think this is the way forward to get innovations out into the commercial market and best prepare new engineers for their professional careers as well. I really enjoyed covering this topic, and appreciate your interest in it.
I couldn't agree more, CLMcDade. I like the idea that "everybody in the class has to be able to do the math, the analysis, the real dimension drwaings." It's nice to know that there's such practical application of knowledge outside the realm of the senior design project.
I think the approach is excellent and should be duplicated as often as possible by university engineering departments. This will give the students "hands-on" experience and allow them to solve, or at least approach solving, real-world problems faced on a daily basis. At GE, this is what we called quality functional deployment (QFD). Taking customer "wants" and transferring them into specifications usable enough to produce an actual product. Great experience for an engineering student. Great post Elizabeth--very informative.
I'm glad you enjoyed the post, bobjengr. It is always good to hear the perspective of someone in the industry as well. I think, too, this is just a more practical way to design things that customers in a particular market really need and it just makes sense to have this kind of program in place. I can't imagine why more universities and research institutes aren't doing it. I think it could not only benefit industries by giving professionals in them the products they want, but also save a lot of time and money.
I agree it is important to provide courses that exercise students knowledge in a practical way. This prpares them for the real world. Key elements of these courses are team-work, working closely with a "client", using an engineering design process, critical thinking, and communication (both written and oral).
Another example is the course I teach at Stanford - Perspectives in Assistive Technology - where students work on projects that benefit an individual with a disability or an older adult in the local community. Projects are "pitched" in class and come from researchers, family members, health care professionals, as well as people with disabilities or older adults. The projects represent real-world problems.
This is a ten-week course open to everyone, not just engineering students. Class sessions are filled with guest lecturers, field trips to local facilities, and an assistive technology faire.
Community members (several have disabilities) are encouraged to attend the class sessions and add to the in-class discussions.
Hi, Dave, thanks for your comment and for telling me about your class. It sounds great--something that benefits both the students and the community, giving the students hands-on practice in the real world. And I also like that it's open to anyone who wants to take it and learn how to develop these projects. I'll take a look at the information you provided.
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.