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SciArt Software helps companies get rid of unwanted weight

The Madison-based startup provides software that allows design engineers to simulate different product designs before they’re ever made to reduce weight and part counts, which saves companies time, money, and raw materials.

The part pictured above is a support link for suspension part that transfers load back and forth between chassis and the wheel assembly of a vehicle. The redesign was an effort to create a lighter more efficient part that would meet the requirements for the Sheffield Formula Racing Team in the United Kingdom. Formula SAE is a design challenge where university teams from all over the globe compete. Top teams are graded on performance metrics based on design, cost effectiveness, and on track vehicle performance (which includes timed laps, ride and handling, acceleration, top speed, fuel efficiency, etc.). This was one of four parts the Sheffield team redesigned to lower the weight of their Formula SAE car.

The part pictured above is a support link for suspension part that transfers load back and forth between chassis and the wheel assembly of a vehicle. The redesign was an effort to create a lighter more efficient part that would meet the requirements for the Sheffield Formula Racing Team in the United Kingdom. Formula SAE is a design challenge where university teams from all over the globe compete. Top teams are graded on performance metrics based on design, cost effectiveness, and on track vehicle performance (which includes timed laps, ride and handling, acceleration, top speed, fuel efficiency, etc.). This was one of four parts the Sheffield team redesigned to lower the weight of their Formula SAE car.

Image courtesy: SciArt Software

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There are a lot of cool things happening around Greater Madison — innovative local companies are breaking new ground every day — but few have as much potential to reshape a multitude of industries as SciArt Software.

Simply put, the Madison-based startup company’s software provides a new analysis and optimization tool to generate options for design engineers who are looking to explore the design space while reducing weight and part count. SciArt Software sells to companies that are under pressure to lower the weight of their products while meeting strength, stiffness, and part-fatigue requirements: these include companies in the aerospace, automotive, defense, handheld tools, and performance vehicle industries. Reducing the weight of the average car by 100 pounds improves automobile miles per gallon by about 1 percent, and new, lighter cargo carriers saved United Airlines $1.4 million annually.

Helping spur these kinds of innovations was enough to recently land SciArt $530,000 in seed funding from the Idea Fund of La Crosse.

The idea for Pareto, SciArt Software’s proprietary analysis and optimization engine, emerged from over 10 years of consulting and research, during which Chief Science Officer Krishnan Suresh encountered several deficiencies with current design optimization methods. “The slow nature of current methods translates into longer product development cycles, and increased product cost,” says Suresh. “Based on our research, I knew we could develop a radically different, and significantly better method.”

The kernel for the SciArt Software product is licensed from the Wisconsin Alumni Research Foundation (WARF). SciArt built several computer-aided design (CAD) plug-in tools so design engineers can explore the design space within the framework of their existing CAD application, which gives customers the ability to control all aspects of their design process and expands simulation tools beyond the specialized analysis team.

New CEO joins team

Following a national search, Karen Caswelch joined the company in August as CEO. Caswelch brings 10 years of experience in the C-suite of four technology startup companies after retiring from a 24-year, award-winning career at General Motors. She has a mechanical engineering degree from MIT and an MBA from Harvard Business School.

Explaining how SciArt’s Pareto system works, Caswelch says users set up a design space with known loading scenarios, and then add their own manufacturing process or geometric constraints. They can do that using any one of the SciArt Pareto suite of products. It could be a CAD-integrated solution, which means the engineers don’t have to leave their design environment, or they can use CAD agnostic tools, which add a step of importing design space over the CAD-integrated solutions.

“Once the problem is set up, a single click will assign the job to the Pareto engine,” notes Caswelch. “This is where the magic happens. Pareto will start analyzing and optimizing material removal based on all of the constraints. The material is removed step by step, each step providing a viable solution that will meet all the requirements identified in the problem set up — all the way to the lightest possible weight.

“At the end of a single run, Pareto will provide anywhere between eight to 15 viable solutions that all meet the constraints with different outcomes of strength and stiffness. Our customers can then choose which designs make the most sense moving forward for part consolidation or straight-up manufacturing and testing.”

Computer-aided engineering, or simulation, is becoming more and more important, according to Caswelch, because companies realize that if they simulate and solve potential failures up front, it is significantly less expensive than fixing the problems when they are in the field.

However, the issue with expanding CAE is that the current practitioners are of retirement age and typically the analysts have advanced degrees — master’s level at the very least. SciArt has streamlined the process to allow design engineers the ability to explore the design space while applying simple and easy analysis tools, freeing time for the analysts to be able to conduct more complex simulations and minimizing iterations between the design group and the analysis group because the initial designs are closer to the requirements.

“When you can minimize the number of prototype rounds, you will save money and the environment,” explains Caswelch. “If you were able to run enough simulations, you might be able to run a fleet of 10–20 prototype vehicles vs. 30–50 prototype vehicles. Additionally, the cost of failure in the field leads to additional costs — building and validation of the replacement products, transportation to replace products, and the replacement of products, all of which will impact the environment due to wasted energy and materials.”

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