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Generative design is an automated method of creating Computed Aided Design (CAD) geometry for part and assembly models using machine learning. Rather than defining the shape using feature-based or direct modeling methods, a user specifies the design space (like an envelope, including areas to be preserved or excluded), operating environment conditions, materials, and manufacturing constraints. An algorithm then computes one or more potential solutions. The user can then filter down the results to select an optimal choice. Generative design is faster and, in many ways, more reliable than traditional iterative human-driven methods.

What Makes Generative Design Better?
Generative design and closely related topology optimization tools have been available for several versions in Creo. Let’s look at four aspects that make generative design different and better than traditional CAD workflows.

You’re building requirements into the design. All products start with requirements. The top-level requirements are decomposed into subsystem requirements, which are then distilled into component requirements. Even though we may know the structural requirements for a part or a subassembly, in the past, those requirements weren’t validated until the design was complete. With generative design, we set up our design by applying load cases to our model. This ensures that the solution meets the criteria from the beginning.