1. Home

Generative design

Generative design in engineering enables design collaboration with artificial intelligence. Computer algorithms explore a range of possible design solutions based on specified criteria and constraints to generate potential designs for new products or improvements of current product design.

What is generative design?

At a high level, Generative design is relatively simple. It is a capability of CAD generative engineering applications that autonomously generates a number of design alternatives given a set number of constraints. This can be done without an engineer’s guidance or interaction, freeing them up for other tasks. Once complete, the engineers can choose which designs they want to explore more completely. In all, this accelerates the design process without detailed attention from the engineer.

Generative design in computer-aided design (CAD) is an innovative approach that involves using algorithms and artificial intelligence (AI) to generate multiple design options based on specified parameters and constraints. It allows designers and engineers to explore a wide range of potential solutions and optimize designs for various objectives such as weight reduction, material efficiency, cost minimization and performance enhancement. Generative design in CAD is particularly valuable for complex engineering challenges where traditional design methods may be limited by time, resources or human creativity. By leveraging computational power and generative engineering algorithms, generative design empowers designers to create optimized, innovative solutions that push the boundaries of what is possible in product design and engineering.

Key characteristics of generative engineering in CAD

Algorithmic optimization in generative design:

Generative design algorithms analyze input parameters such as functional requirements, material properties, manufacturing constraints and performance criteria to generate design solutions.

Iterative exploration in generative design:

Designers can explore numerous design alternatives quickly and efficiently. Generative design tools typically generate a multitude of design options, which can then be evaluated based on specific criteria.

Complex geometry in generative design:

Generative design often produces complex geometric shapes and structures that may be difficult to conceive manually. These designs can leverage the full potential of advanced manufacturing techniques such as additive manufacturing (3D printing).

Multi-disciplinary optimization in generative design:

Generative design can optimize designs across multiple disciplines, such as structural analysis, fluid dynamics, thermal management and electromagnetic simulations, to achieve optimal performance across various criteria.

Human-in-the-loop in generative design:

While generative design algorithms automate the creation of design alternatives, human designers play a crucial role in specifying design requirements, evaluating generated options and refining the final design.

Exploration of design space in generative design:

Generative design allows designers to explore the entire design space, uncovering innovative solutions that may not have been considered through traditional design methods.

Parametric modeling in generative design:

Generative design often utilizes parametric modeling techniques, where design parameters are defined and manipulated to drive the generation of design alternatives.

Generative design and topology optimization

Generative design supports key capabilities like topology optimization for performing structural simulation and removing load-weight from empty area in materials. Siemens NX 12 is the only generative design software that embeds topology optimization powered by convergent modeling technology which enables unified 3D modeling capability on combinations of Facet and B-rep data. This results in lighter components without sacrificing design intent or integrity.

Empowering engineers with generative design and facet modeling

Generative design is a CAD engineering software function in which a designer collaborates with artificial intelligence algorithms to generate and evaluate hundreds of potential designs for a product idea. The generative design process starts with defining the goals and constraints of the project. These include, but are not limited to, design parameters such as:

  • product size or geometric dimensions
  • permissible loads and operating conditions
  • target weight
  • materials
  • manufacturing methods
  • cost per unit

Related products: NX CAD

Multiple design options generated from a generative design process.

Benefits of building with a generative design process

By using generative design, engineers can create and simulate thousands of designs (many of which they may not have envisioned on their own) in a fraction of the time it would normally take. As an additional benefit, the generative design process can yield highly customized complex shapes as the best solutions – which can be cast or processed through high-resolution additive manufacturing.

Try free software

NX X software trial

Developed for product designers of all experience levels, NX X CAD delivers unparalleled power. Leverage all the powerful features and functionality of NX with the advantages of the cloud, even in the absence of an internet connection.

Learn more

Generative design empowers designers to create optimized, innovative solutions that push the boundaries of what is possible in product design and engineering.

Watch

Siemens NX software includes capabilities that enable a multidisciplinary team approach to consumer product design that brings design, prototyping, planning and validation into a single digital workspace.

Read

Produce an organic, reduced-mass geometric solution of a specific material optimized within a defined space, accounting for permissible loads and constraints.

Explore

Hall Designs offers design, fixturing and reverse engineering services for the motorsports industry, turning ideas and samples into manufacturing-ready CAD formats. Learn how they reduce product revision time by 20 to 25 percent.