Two very significant things happened last week. First, my son Eric turned 13. Second, I got a new car. These two milestones merged into a singularly great long weekend as Eric and did our very first father-son roadtrip to the great city of Cleveland. The car was the first new car my family had bought in about eight years, and as hard as I tried to maintain meaningful conversation with Eric through the many hours, I have to admit that my attention was frequently diverted to the car … thoughts of “hey … that’s a nice ride”, “so that’s what sport suspension feels like”, or “Yes Eric, that’s a very good question on the American election but … I wonder what that button does”.
Even in the scant eight years, it seems that cars have experienced major transformation. For essentially the same amount of money that I spent on my last car, my new scoot is a lot safer, handles like a dream, is packed with conveniences, and goes like a bullet :-D This machine seemed orders of magnitude better than my last car. As great as my new car is though, the engineers in Detroit, Tokyo, and Munich are starting to express some concerns about future directions. Cars today have to be more than great … they have to be great AND green AND affordable AND great looking AND deploy the absolute latest technology. Moore’s law predicted that computing power accelerates at exponential rates. With the sheer amount of electronics in the modern car I suspect that Moore is approaching in the rearview mirror at an alarming speed and all auto companies are beginning to assess their ability to innovate at 21st century speeds.
I’ve tossed around the phrase “math matters” for many years now and in general, I’ve used it in context of the growing importance of mathematics in industry. As design challenges become more complex engineers are discovering the inherent limits of the current software toolchain deployed for the analysis and design of engineering systems. The automotive industry has historically been at the forefront of innovative application of software. CAD, PLM (product lifecycle management), MBD (model based design), are clear examples of this segment’s foresight in the past. Increasingly, auto industry leaders are looking to reboot the toolchain with fresh software thinking. And mathematics has emerged to be a major dimension in the emerging toolchain. Direct access and manipulation of the underlying model equations, advanced mathematical transformations and algorithms, are all becoming much more prevalent. The theory is, more clever and efficient management of foundational math will lead to solutions of more complex design problems and ultimately reduce the design time. And of course, shorter design time correlates directly to competitive advantage as amazing new features and functionality can roll out faster.
MapleSim, our newest offering fully embraces this movement towards a more sophisticated application of mathematics in engineering. By making the math more accessible and manageable, engineers can develop and optimize more advanced and higher-fidelity models in significantly less time. Since the announcement of MapleSim, I’ve had countless occasions to present the merits of our new approach to modeling to engineers and it has been nothing short of amazing to see the reaction. People just “get it”. With the traditional toolchain, the development of the required system model equations was a highly manual, or extremely abstract process. A survey that Maplesoft undertook with two thousand engineers, showed that the majority still wrestle with paper and pencil to deal with the underlying math for their simulations and models. MapleSim is a pretty straight forward concept: it automates the model derivation AND solution process. Through a combination of a graphical interface and new symbolic algorithms to manage the modeling math, it effectively reduces or eliminates the dependence on manual processes. This simple message seems to be resonating with industry.
As part of our roadtrip, we stopped by to meet a few magazine editors representing auto industry publications. Part of it was the demands of my job, of course, but secretly more of it was to show my son what his dad did for a living and what kind of exciting things the old man was involved in. I thought the meetings went very well with good dialog emerging. I asked Eric what he’d thought of the meetings and whether he had learned anything. He commented “that was a disaster! All the guy did was ask a million questions and you guys just ended up talking for over an hour.” Working engineers aside, the reaction of the press has been another source of pride for us. They have seen software come and go and they have a good sense of what’s truly new and what is spin and so far, they have been genuinely impressed and interested in following the evolution of these new techniques. So those “million” questions, to me, was the greatest expression of interest and the best I could hope for in a meeting with the press. All indications are that you’ll hear a lot more from them in the near future.
Perhaps it’s too much to expect a 13 year old to fully appreciate how the introduction of a non-linear term in a differential equation will leads to better stability control or acceleration in his car a decade from now. But it was very heartening to have some meaningful conversation about work issues with this young man. Perhaps if I had shifted the focus of my MapleSim examples away from suspension systems to signal processing innovations in car audio that will truly capture the transcendental heavy metal nuances of Metallica, I could have gotten a bit more of a positive reaction from my son.