December 1, 2016
It’s the day after Election Day as I write this. After enduring more than a year of promises, political drama and pundits, voters were asked to separate the hype from reality and choose a president. I won’t miss the campaigning, but in a way I won’t get the chance to. The stumping for optimal engineering technologies shows no signs of slowing.
Supporters of new technologies make promises similar to politicians as they campaign for the tools and techniques they say will save you time and money, revolutionize product design and development, and make other technologies obsolete. Which technologies are poised to do just that and which ones are being overhyped? It’s sometimes hard to tell. As the physicist Niels Bohr said: “Prediction is very difficult, especially if it’s about the future.”
So we asked you, our audience of design engineering teams, what you thought the optimal design technologies are and will be. Where are you casting your vote, as it were, by investing in new technologies? Almost 600 of you responded. The results can be found throughout this special year-end issue that delves deeply into how technologies that are poised to change the future of product design are being used today.
Optimal Design Technology
On the whole, survey respondents were a bit more pessimistic than last year. When asked whether you agreed that certain technologies would revolutionize the design engineering process, simulation-led design, design optimization, high-performance computing, the democratization of simulation and Big Data all received fewer votes of confidence than last year. For example, last year 71% of respondents agreed that both simulation-led design and design optimization would revolutionize the design engineering process. This year, those percentages were 52% for simulation-led design and 46% for optimization technologies.
However, those opinions may not be based on real-world experience, especially when it comes to optimization technologies. In this year’s survey, only 6% of respondents said they are currently using design space optimization and only 7% are using topology optimization. However, 15% expected to be using design optimization software within two years and 10% said the same about topology optimization software. It should be noted that 17% of respondents classified their organizations as innovators (among the first to adopt new technologies) and 21% said their organizations were early adopters (among the next to adopt leading-edge technologies).
When asked which technologies would have the biggest impact over the next five years, more than half (56%) of respondents put additive manufacturing/3D printing on that list, followed by simulation (47%) and advanced materials (40%). About a third included high-performance computing, predictive analytics and what is expected to be a huge driver of predictive analytics: the Internet of Things (IoT).
In total, almost half of respondents are already developing products for the IoT (22%) or expect to be within two years (26%). But the jury is still out on the hype is surrounding the IoT. More than a quarter of respondents (28%) say the IoT is more hype than real, while 19% disagree or strongly disagree with that sentiment. The remainder, perhaps wisely, stayed neutral.
Technology Challenges Remain
At DE we believe technology should be used to solve your everyday challenges, so we also asked about those difficulties. Both this year and last year, collaboration, short development deadlines, inadequate budgets, regulatory compliance and inefficient workflows ranked among your top five challenges. The question, then, is which technologies will help solve those challenges?
As one survey taker put it when asked about the future of predictive analytics, the technology meant to quantify prognostication: “Being informed of ‘what is’ can only offer limited benefit compared to the benefits of knowing ‘what is most likely and when.’ The most attractive products of the future will offer the less knowledgeable user the ability to make better decisions or act on recommendations.”
The ability for non-specialists to make informed, sound decisions would go a long way toward removing the bottlenecks that plague design engineering teams and solving the top challenges that our survey respondents listed. But as Bohr said and the presidential election results prove: Prediction is very difficult. It’s still early for predictive analytics and the technologies that surround it, but someday it could be the key to optimal product design.
See more survey responses in our By the Numbers department.
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About the Author
Jamie Gooch is the former editorial director of Digital Engineering.Follow DE