How to help engineers do new.
Creating new products that provide a useful function is hard, and insuring they function day-in and day-out is harder. Plain and simple, engineering is hard.
Planes must fly, cars must steer, and Velcro must stick. But, at every turn, there are risks, reasons why a new design won’t work, and it’s the engineer’s job to make the design insensitive to these risks. (Called reducing signal to noise ratio in some circles.) At a fundamental level engineering is about safety, and at a higher level it’s about sales – no function, no sales.
That’s why at every opportunity engineers reduce risk . (And thank goodness we do.) It makes sense that we’re the ones that think things through to the smallest detail, that can’t move on until we have the answer, that ask odd questions that seem irrelevant. It all makes sense since we’re the ones responsible if the risks become reality. We’re the ones that bear ultimate responsibility for product function and safety, and, thankfully, it shapes us.
But there’s a dark side to this risk reduction mindset – where we block our thinking, where we don’t try something new because of problems we think we may have, problems we don’t have yet. The cause of this innovation-limiting behavior: problem broadening, where we apply a thick layer of problem over the entirety of a new concept, and declare it unworkable. Truth is, we don’t understand things well enough to make that declaration, but, in a knee-jerk way, we misapply our natural risk reduction mindset. Clearly, problems exist when doing new, but real problems are not broad, real problems are not like peanut butter and jelly spread evenly across the whole sandwich. Real problems are narrow; real problems are localized, like getting a drip of jelly on your new shirt.
How to get the best of both worlds? How to embrace the risk reduction mindset so products are safe and help engineering folks to try something radically new? To innovate?
We’ve got the risk reduction world covered, so it’s all about enhancing the try-something-new side. To do this we need to combat problem broadening; we need a process for problem narrowing. With problem narrowing, engineers drill down until the problem is defined as the interaction of two elements (the jelly and your shirt), defined in space (the front of your shirt) and time (when the knife drops a dollop on your shirt). Where problem broadening tells us to avoid making peanut butter and jelly sandwiches altogether (those sandwiches will always dirty our shirts), problem narrowing tells use to put something between the knife and the front of your shirt, or to put on your new shirt after you make your sandwich, or to do something creative to keep the jelly away from our shirt.
Problems narrow as knowledge deepens. Work through your fears, try something new, and advance your knowledge. Then define your problems narrowly, and solve them.
Innovate.
It really is a big job not doing the same things over again that worked in the past, to look, instead, at these earlier experiences as foundational but not unchangeable. New tool-sets combine well with new mind-sets to accomplish this. I would recommend that designers take a look at the current generation of FEA-related optimization programs, such as Isight. One can define all sorts of parameters and have these programs display alternatives and best scenarios–including new geometries. This approach also addresses risk very well.
At the initial period of design, brain-storming is highly encouraged! When some potential problems or risk looming,the general principle in that field should be followed and one’s past experience should be paid attention; So that risks could be partialy reduced, and possible winding trying be avoided. One useful way is: eliminate those factors or seeming solutions thoes correlation ratios are relatively small to the key target of design.
In the last few years engineering simulation is becoming more and more an important tool for engineers to reduce risk. Improvements as the possibility to couple physics so to simulate a whole prototype and the increase in speed coming from HPC are giving designers a way to predict with confidence the behavior of their products and optimize the design without losing quality. Moreover, through simulation is possible to analyse a big number of hypothesis and make an extensive design exploration just importing a parametric CAD file and let the software calculating the best options for a given output goal. There are some interesting papers here http://www.productintegrity.com