Engineers Take on the Big Data Challenge

A new generation of data visualization tools is helping mechanical engineers make sense of Big Data in their everyday lives. In many cases, tools such as the new DataVis data visualization tool available for free to both ASME student and professional members, are helping students make the transition to their early career roles, where they are now expected to be well versed in data analysis and modeling.
“What’s amazing is what you can do with it,” says Anselm Spoerri, assistant professor at Rutgers University in New Brunswick, New Jersey, who was one of three faculty members from around the nation who helped create the DataVis tool. Initially, DataVis was conceived as an interactive teaching tool to help engineering students learn more about the fundamental properties of different materials. When the web-based tool launched, it included 200 core materials and 60 different data variables, as well as a curated dataset.
With DataVis, it’s possible for engineers from various disciplines to compare properties of multiple materials, as well as to find a property value for a specific material. If you’re building a new aerospace structure, for example, you could use the tool to model different composite materials and test them for how well they would perform under a wide variety of exogenous conditions. Or, if you want to construct a new building, you could use the tool to determine if the bending stress and sheer stress of each beam is satisfactory for given safety requirements.
At any time, you can choose how many data variables you are working with and then customize results to gain a better understanding of which materials would work best for certain projects. “Start out simple,” advises Spoerri. “Get an idea of one material’s property. Add a second, a third, a fourth…Then you can start seeing the relationships. DataVis allows you to gain a deeper understanding,” says Spoerri.
At the undergraduate level, one potential use case outside of the classroom would be utilizing DataVis to model possible materials for E-Fests projects. If you’re building a new vehicle, for example, you might model the properties of certain materials to get an early idea of what might work. Also, early career engineers could use similar types of data tools in the corporate sector to improve their overall productivity and complete projects faster.
As much as the tool can be used for analysis, its true power is as a storytelling medium, says Spoerri. “It might be possible on the fly to make a presentation,” says Spoerri, given the ability to customize and manipulate the data from DataVis. That storytelling ability is what could convince an investor to fund a new project, or to convince your boss that a specific material should be used during the engineering process.
The importance of preparing student members for future careers involving Big Data is one reason why ASME decided to make the DataVis tool part of its permanent AccessEngineering offering for both students and early career members. “We really think the tool offers a powerful value proposition for members,” says Noel Netel, membership development coordinator at ASME, who spearheaded the effort at ASME to include the tool as part of AccessEngineering.
While mechanical engineers now face a multitude of Big Data challenges in the real world, the good news is that there are new tools that are equipping ASME members, both students and early career members, to face those challenges head-on.

Dominic Basulto is a business and technology writer based in New York, NY.

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