Wednesday 19 March 2014

How data-driven design could filter down from the McLaren P1 to your next car

What do the McLaren P1 supercar, air traffic control improvements and the fastest road bike have in common? McLaren Applied Technologies has figured out to use data-driven design at lightning fast speeds for all of them. And the company is only just getting started.
Speaking at the Gigaom Structure Data 2014 conference on Wednesday, Geoff McGrath, managing director of McLaren Applied Technologies, said the data-driven design techniques that work really well on automotive design apply to a vast number of other industries. “The convergence of data management, analytics and simulation create high-performance design value at a fast pace,” McGrath noted.
Simulation is a big part of the approach, mainly because it provides digital data before building a physical product, regardless of whether that product is a $500 bike or a million-plus-dollar automobile. But it’s not about saving money, it’s about saving time.
In race cars, the team uses F1 simulators so designers can view a driver and feed that data into models. The design team then gets instant feedback and can make new changes in the models, keeping the design cycle very short.
McGrath said that by instrumenting an object and seeing how it interacts with variables — the road or cyclist on a bike, for example — his company can determine whether a physical design change is even worth considering. Combining the simulation with years of actual data speeds up the process, so much so that the Specialized bike company said it learned more in six months with McLaren than it did in the prior decade.
Product design is just the start of how vast information stores can help, however. McGrath suggested future products that use data-driven smarts to perform better on their own. “Products that can sense how they’re being used, where and in what environment can make intelligent choices,” he noted.
Geoff McGrath, managing director of McLaren Applied Technologies, Structure Data 2014

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