- Engineering Workflow Automation
- Design Space Exploration
Huge amounts of engineering data are being generated while exploring the design space and optimizing product designs. Effective data mining technologies are therefor needed to help engineering teams gain deeper insights and visualize the design space in a limited time window, to ultimately help them make informed decisions.
Once too often, engineering teams get buried under massive amounts of data generated through simulation and physical testing. While they have access to extremely powerful virtual and physical prototyping software, they often face major issues translating the huge amounts of data delivered by those tools into clear decision metrics.
Some studies rate the time spent by engineers in non-value added activities such as searching data, duplicating information, manually updating models, etc. at 40% of their total time. Our engineering data analytics technologies make it easy for them to access, organize and process engineering data and results from disparate sources – freeing up valuable time they can dedicate to in-depth analysis of their data.
As a result, they spend a lot of time and effort to retain the information that matters most. Engineering data analytics makes it a lot easier for them. They can interpret the available information, and evaluate results through the different stages of the development process. This helps them acquire valuable insights into their data, and learn the lessons on which to base critical engineering decisions.
Leveraging engineering data from disparate sources, our technology solutions deliver actionable insights and relevant decision metrics to engineering teams. State-of-the-art visualization widgets that run in a web browser are part of that, as they deliver unlimited flexibility to process data and share charts with peers and managers. Intuitive interaction enables engineering groups to make smarter and better informed decisions – as part of fast-paced development cycles.