On September 5, as I walked into an enormous garage in General Motors' sprawling Vehicle Engineering Center (VEC) in Warren, Michigan, GM engineers were tearing apart the competition. Literally. A Mercedes sport utility vehicle stripped of its body panels and chassis sat on a platform like a cadaver on an autopsy table, components of its exhaust system arranged neatly on a cart for examination.

The room is the VEC's Teardown Area, the workshop of GM's Competitive Benchmarking team. Nearby, dozens more vehicles were in various stages of deconstruction. Some were past model years from GM, but more were current models from other manufacturers. All of them were in the process of being digitized. Like Jeff Bridges in TRON, they were being converted from metal, plastic, and glass into "math," reverse-engineered into computer models for benchmark trials on GM's simulation grid. The result is data that's almost as good as having direct access to competitors' original engineering data.

GM isn't looking to steal the design of the Mercedes or other vehicles, at least not blatantly. The computer models of the vehicles being carefully stripped down in the Teardown Area will be used as a reference point for designers. They'll be pitted in simulation-based benchmarks against GM's own designs. The lessons learned will inform GM's engineering of future vehicles and help them understand the competition better. It will also help them cycle through their own design choices faster to catch up with or leapfrog over competitors' innovations within a single design cycle.

What's done in this space is the product of more than a decade of work by GM to accelerate the company's development cycle and make it more like software development. And the technology is being used by GM not just to reverse-engineer the products of its competitors but to improve the quality of its own products and accelerate the design cycle for new vehicles.

Return to the grid

Both the VEC and General Motors have changed a great deal since 2002, the last time I was issued a GM visitor badge. I came to Warren 11 years ago to see the early results of GM's attempt to use simulation and modeling tools to restore its competitive edge. In 1998, under the direction of GM Vice President of Engineering Jay Wetzel, the company was transitioning every aspect of the design and engineering process into digital tools. The company was trying to speed up its time to market with new vehicles and boost the productivity of its vast engineering workforce.

Wetzel wanted car design and engineering to be more like software development, where vehicles were conceived and largely debugged well before the first prototypes were built. That required GM to lean heavily on high-performance computing for rendering how cars would look, how they would perform, and how they would handle crash-testing. At the time, the company was also using computer modeling and simulation to plan out manufacturing for new vehicles. As a result, by 2002, Warren was home to the 15th largest supercomputing center in the world.

The first vehicle to come fully from the new digitally driven engineering process was the 2003 Chevrolet SSR roadster-pickup truck. It went straight from the digital drawing board (a surface model in Alias StudioTools, now Autodesk Alias) to fabrication as a prototype for the 2000 Detroit Auto Show floor. Only 60 full prototypes were built before it started coming off the assembly line at GM's Lansing Craft Centre in September 2002.

Over the past decade, "our use of simulation has grown exponentially," said Martin Isaac, GM's Engineering General Manager of Global CAE Strategy. "And the model sizes and types of simulation have increased dramatically. On the crash test side, for example, for front and side impact, we've added a few more million elements and degrees of freedom to the models."

At the same time, the technology has both improved and become cheaper—now relying on clusters of Linux servers in GM's new Warren Enterprise Data Center. It takes 36 current-generation Intel processors to run a crash test now instead of the supercomputing resources it demanded in 2002.

Simulation has greatly reduced both the number of prototypes that GM needs to create for each new design and the number of physical models used for testing. There are some areas, such as wind tunnel testing, that are still highly dependent on the use of models—generally made from milled clay. But many of the tests with physical prototypes are simply final checks after long, iterative tests in GM's compute farm.

GM engineers simulate crash tests from every angle, testing restraint and airbag performance and running pedestrian impact digital trials to help improve pedestrian safety. Engineers run aerodynamic and airflow models and simulate air conditioning, heating and electrical systems, and the interactions between all of them. GM has even digitized the road surfaces at its proving grounds at Milford, Michigan to use in ride and handling simulations.

"The technology has enabled us not only to reduce development time but to get a much better engineering solution," Isaac said. "You can spin the engine cycle many, many more times than you can in the physical world to collect data to improve upon the solutions. You can do more variant designs and can get a cloud of answers to engineering problems to choose from. CAE helps us get back in front of the design process, and the chance of a flawless design validation process is greatly increased as a result."

Simulation and modeling also allows GM to measure its new designs against those of competitors before a single weld is made or body panel is stamped. But in order to benchmark against the competition in the virtual realm, GM needs accurate engineering data on its vehicles—something competitors aren't exactly willing to give up themselves.