- Engineering Workflow Automation
- Design Space Exploration
id8 decide easily leverages engineering data from disparate sources, including Optimus, connecting and visualizing any data related to physical or virtual prototypes. It accesses, organizes and processes data and results all from within a web browser, enabling users to bring data insights to life in an engineering dashboard by dragging and dropping data widgets onto the dashboard canvas. These engineering dashboards can easily be shared live with peers and managers, who can then access them from any workstation or mobile device.
id8 decide complements Optimus & id8 discover design space exploration, delivering actionable insights and relevant decision metrics to engineering teams - maximizing user productivity while minimizing technology ownership cost. Providing users with access to a wide range of different widget types, id8 decide delivers state-of-the-art visualization of their data. And id8 decide’s intelligent environment takes care of all the hard and tedious work, remembering user preferences to automatically visualize engineering data in the most relevant way.
id8 decide pushes intuitive usage concepts to the limit. Users find id8 decide as easy to use as working with the spreadsheet program they are familiar with. Eliminating non-value add activities such as searching data or duplicating information, id8 decide frees up valuable time engineers can now dedicate to in-depth analysis of their engineering data.The utmost care has been taken to ensure smooth and fast interaction with large sets of engineering data - delivering the interactivity engineering teams need in their daily work.
id8 decide empowers users to process engineering data on-the-fly. Whether this concerns data imported from an external source or data generated by id8 discover’s Design Space Exploration methods, id8 decide provides the capability to perform rapid what-if optimization and feasibility analysis. Different criteria can easily be defined, and then be used to interactively explore the design space. Starting from an initial set of criteria, constraints can for example stepwise be relaxed to identify feasible design points among the set of Pareto-optimal solutions.