Generative design is a fastest way to create new designs to meet specific requirement

 

Generative Design

Generative design is a new approach to design and engineering that relies on the power of computing and artificial intelligence. In this innovative solution, designers input parameters, constraints, intended outputs, requirements, materials, and manufacturing methods into generative design software. This information is then used to create hundreds of innovative design options that meet specified requirements.

The generative design market was valued at US$ 1.88 Bn in 2021 and is forecast to reach a value of US$ 9.04 Bn by 2030 at a CAGR of 20% between 2022 and 2030.

The underlying goal is to find the most viable and best-fitting design alternatives that are then evaluated by designers. In this process, the designer’s role is to continuously modify the model and constraints based on the judgment of the design results until a viable design is found.

Unlike traditional optimization methodologies, the generative design does not rely on finding a single solution but explores the solution space. Using a computational model, generative design algorithms explore different permutations of the solution and determine a set of alternatives that satisfy all the constraints.

It’s a faster way to generative design than the standard iterative processes that are traditionally used. This also reduces the time and effort that engineers and designers have to spend on design work, which in turn gives them more time for research, analysis, and other essential tasks.

In addition, it helps engineers develop lightweight parts that can be manufactured more efficiently and with less waste. This allows engineers to save material, reduce manufacturing costs and reduce CO2 emissions.

The process is very powerful in industrial applications such as automotive and aerospace, but it can be applied to any type of design. For example, it can be used to design patient-specific medical devices or customized footwear and protective sports equipment.

Another benefit is that it can improve the efficiency of manufacturing simulation, which can result in faster production and lower energy consumption. This is especially important in the additive manufacturing industry, where it can significantly reduce part weight and improve a component’s stiffness.