In his blog, “OMG I became THAT Person”: The quirkiness of Engineers, our very own Scott Deuty introduced one of the generalized topics about engineers: our supposed quirkiness. But, are we like THAT? Maybe. Why not?
Engineering professions do demand quite a few characteristics from engineers. May I call them features? Some people reduce them to passing many exams at University for earning one Diploma. But looking at what NASA and ESA engineers do, just to put one example, it gets crystal clear that it all goes beyond one simple test-passing skill requirement.
I empirically see one distinctive feature: the mind flexing ability that allows seeing the whole picture from different perspectives, and thus foreseeing not one single, but more than one approach for solving one problem. Some call this ability Divergent thinking 1 , see Figure 1. Divergent thinking is now widely accepted as being in close relation to Creativity. I could take some risk now and say that, as I see it, divergent thinking also takes advantages of, and incorporates several aspects from, Inductive reasoning 2 and Deductive reasoning 3 .
Divergent thinking (Image source: Wikipedia).
Two more characteristics that make up one problem solver engineer are, in my opinion, the capacity of Knowledge summary and systematization , and of course the need to go beyond the surface by using Scientific methods 4 , see Figure 2.
Scientific method (Image source: Wikipedia).
To my curiosity, I found references to one tool and its associated theory called TRIZ5 . This acronym comes from the Russian:
Authors Victor D. Berdonosov and Elena V. Redkolis, from the Komsomolsk-on-Amur State Technical University talk about the TRIZ evolutionary model and its relation with knowledge systematization in their paper called Approach to Knowledge Systematization 6 .
Knowledge summary and systematization play key roles in overcoming our physical knowledge and data storage limitation. We must develop and further improve our methods to filter out irrelevant stimuli. And to create relations and links between the vast amount of knowledge and information we assimilate nowadays.
Perhaps from this summarizing and filtering comes our infamous Selective memory. But that would be closer to a “defective behavior” than to one feature. Don’t you think? Let us hear your experiences on this matter.
After all these years burning transistors and torturing keyboards, I’ve seen three major engineer groups: the purely theoretical engineers , the practical engineers , and the non-practicing engineers , with maybe a few more sub-groups in-between. I don’t intent to put threshold levels between groups. Would you? I consider myself a practical engineer that often makes little jumps into the theoretical engineers’ work area.
So, are we so quirky? Maybe not according to our personal point of view, but there are several stereotypes that have gained too much traction lately. The Big Bang Theory 7 , The IT Crowd 8 and other sitcoms have contributed to that, but we also have outstanding examples that confirm some stereotypes. Do you remember some of them?
Returning to Scott’s blog, many will agree that measuring temperature in half a dozen points, and then graphing the curves and extracting conclusions is not quirky. It is fun! It is a good thing being a Do It Yourself (DIY) enthusiast. The DIY and open source movements are driving innovation. And the Learn By Doing teaching paradigm makes extensive use of and promotes DIY.
One of my firsts tasks when I started working for my current employer was to make some temperature tests to one product. “How will you do that? ” asked one coworker. Simple, we put it inside the freezer, put some sensors in the critical points and use some sort of data logger. We had nothing of that in the company and only a couple of days to conduct the tests and give the answer to the customer. It was a good excuse for going to one nearby store, buy a few components, one Arduino UNO R3 and some thermistors. His Catalonian expression after a few hours, when He saw the test rig working and taking data was: “Ostres, això ha estat dit i fet! ” [That was said and done! ]. It was simple enough as for these tests 2.5o C of error was perfectly OK. See Figure 3.
Temperature curves measured with the Arduino UNO R3.
More recently we conducted one similar study with another product and it was a good chance to create one improved version. This time I used one Freedom KL25 board that was laying around, one 4 lines LCD module and a few Op Amps for buffering. It was a less than a two-day job including PCB design and milling, assembling, firmware writing, datalogging application writing and preparation of the rest of the test setup. Next figures show some details of this tool.
Pictures (top and bottom) of the 4-channel temperature measurement device.
The inter-comparison with another thermometer gave pretty good results and the measurement uncertainty was also good enough for the job. I will eventually clean-up and share the code and schematics for this device, just in case it can be of any use for other colleagues.
Are you also a DIY enthusiast? Tell us in the comments section about your experiences and your problem-solving DIY creations.
1 Divergent thinking, Wikipedia article.
2 Inductive reasoning, Wikipedia article.
3 Deductive reasoning, Wikipedia article.
4 Scientific Method, Wikipedia article.
5 TRIZ, Wikipedia article.
6 Approach to knowledge systematization, Proceedings of the TRIZfest-2015 International conference, Seoul, Korea.
7 The Big Bang Theory, CBS.
8 The IT Crowd, Channel 4.