Generative Design Market Size

Generative Design Market Analysis

The Generative Design Market size is estimated at USD 3.81 billion in 2024, and is expected to reach USD 7.80 billion by 2029, growing at a CAGR of 15.41% during the forecast period (2024-2029).

The upcoming trend of designing toolsets with machine learning capabilities contributes to the growth of the market studied. Significant investments made during last year aimed at empowering designers to reduce the number of errors, thereby saving considerable time, are expected to produce results in the future.

• The growing demand for advanced manufacturing with complex designs and the need to reduce the size while improving the performance of automotive compels automotive manufacturers to increase their R&D investments and adopt generative designing.
• Companies such as Airbus, Black & Decker, Under Armour, and other massive corporations embrace generative design as a trend molding the future of the engineering industry. It enables engineers to hand the reins off to their CAD software to naturally find the best solutions to a given set of constraints. It augments the engineer's imagination.
• Generative design is in the initial development stage, meaning that early users may come across specific challenges. For instance, defining a design problem in computable terms, which generative design software has to solve, will include a steep learning curve. Engineers need to be more experienced with revealing the design problem as a set of parameters may end up with loosely defined structural restraints or loads, ultimately resulting in a failed design.
• There are over 30,000 parts in an average car, and creating all these pieces and then putting them together requires an incredibly complex supply chain and manufacturing capabilities. However, General Motors and the San Francisco-based software company Autodesk plan to upend how cars are designed, reducing the number of car parts that go into each vehicle while making cars both lighter and more robust.
• Another point to consider with the generative design is that efficient methods can only sometimes be manufactured. For instance, in a Renishaw case study, engineers topologically optimized a suspension bell crank. They should have considered the optimized part's manufacturability. It resulted in a design that demanded a lot of supports to be printed, whereas a good practice is to design pieces with fewer supports as needed as possible. Such instances are anticipated to lay a negative impact on the market.
• However, generative design is used to help address the risks related to COVID-19. For instance, Digital Blue Foam is developing a tool to help address the risks associated with the use and occupancy of interior spaces due to COVID-19. Covid Space Planner analyses factors such as total occupancy and proximity, airflow and ventilation, and the duration of activity in the space. Based on these factors, the tool applies Digital Blue Foam's generative design capabilities to recommend spatial planning strategies, such as the location of entry points, work areas, furniture placement, and retrofits, to mitigate the risk.