Some years ago, there was the first hype around this topic, but there was still no real breakthrough in this field. The scepticism towards AI algorithms seemed to be too great a driving force in product design. It was also difficult for suppliers of 3D CAD technology to get engineers and developers enthusiastic about the early and frequent use of simulation technology in the design process, as the technological challenges such as the lack of application speed often seemed too great.
A lot has happened since then. Thanks to cloud technologies and advances in simulation, 3D printing, and machine learning, the concept of generative design in product development is facing a broader application in the market. Now it is time to think about the future role of the product developer.
True ‘Computer Aided Design’
Simply put, generative design means humans and computers working together to create objects beyond the human imagination alone. While product developers and engineers have been actively thinking and creating new products, components and larger constructions using the computer and modern CAD software as a tool, generative design turns the computer into the driving creative force.
Operators first define design parameters and functional requirements such as maximum size, weight, type of material, load capacity, manufacturing process or costs. It is even possible to define further design parameters that consider purchasing decisions, manufacturing capacities, the status of the supply chain and regionally required product variants. Then the computer takes over, but it not only calculates an optimal geometry – it also creates thousands of design drafts that meet the specified criteria catalogue, pushing it in all possible directions. In this way, simulation is integrated into the development process through generative design. So, for example, the system only generates designs suitable for the CNC milling machine or the 3D printer, although differing production methods can be proposed for selection.
There are many advantages that companies achieve through generative design. The productivity of the product development department in the design phase can increase immensely, as well as the gain in creativity and innovation if more time can be invested in researching conceptual designs. For example, it is possible to develop more powerful designs with lower weight and improved durability.
At the same time, this type of development promotes the optimisation of new products for improved manufacturability, the reduction of material costs and shorter production times, and it allows a high degree of personalisation.
AI chooses the ‘winner’
After several thousand design drafts have been developed, using generative design and boundary conditions, AI selects the most suitable version based on the specifications.
The developer, on the other hand, can have several design variants selected at this point, using various parameters – such as the best suggestions for different materials, i.e. the lightest model with the greatest possible stiffness. With generative design, criteria can also be changed in real time, whether it’s material or design requirements, while parameters linked to production costs, such as volume, are converted immediately by the software.
The technology provides the developer with optimised designs for several targets simultaneously, in a very short time. Once the possibilities have been explored, the first prototypes can be produced in milling machines or 3D printers, or the results can be automatically incorporated into tests based on other company findings, including cost calculations, supply chains and quality data. This not only saves an enormous amount of time, but can also greatly increase output. The ‘aided’ in CAD - Computer Aided Design - is finally actually implemented.
Not topology optimisation
It is important to review the difference between generative design and other technologies such as topology optimisation and grid optimisation, which are often listed under one name. While generative design is based on a ‘white sheet of paper’ for which the product developer only defines a few framework criteria, all other technologies refer to the optimisation of an already existing design through simulation on the 3D model. However, this does not create completely new design possibilities as in generative design, but only optimised variations of a known solution.
The product developer remains the last instance
As already described, generative design and AI change the entire product development process and also the role of the product developer or engineer. In the past, they were the driving creative force that delivered design drafts, but in this process, they become more of a ‘curator’ of the results. Although they remain involved in the design phase from the outset, they only define the parameters for the computer and then juggle with a few objectives such as the fastest production variant, the most cost-effective model in production or the variant with the best product characteristics. Compared to today's reality, this has the advantage, among other things, that they no longer have to defend models against other decision-makers – after all, all of them have been created using algorithms, so the respective optimum can be assumed.
An important role remains - the examining eye, in terms of optics and aesthetics. The computer does not yet possess this. It calculates all given parameters and implements the optimal design according to technical aspects. What about colour and people's aesthetic sense of form? Does a material feel ‘better’ in the calculation despite its poor performance, and is it more likely to be bought?
These are all questions that demand the product developer's broad set of capabilities and experience. There is a difference whether it is a component within a machine, car or airplane that no one will see later, or whether it is a component or a product that is visible later and whose shape, colour or sound can be decisive for the purchase.
Ready for daily use
Generative design and AI have now reached a maturity that makes a wide range of applications possible. This is also ensured by new application packages, such as PTC who offer it within its future Creo portfolio, which uses the ANSYS visualisation technology. Using the integrated functions of Frustum and ANSYS, Creo can recommend design methods with generative design, guide users through the iterative design process with ANSYS Discovery Live and validate the complete product to scale with the more comprehensive ANSYS Discovery package. These Creo-integrated features provide product developers with world-class opportunities to rapidly drive product innovation.
Gone are the days of slow applications that cost more time than they save. As a result, generative design and AI are likely to be more widely adopted very soon as companies increasingly discover the benefits of this method in conjunction with available technology – especially the first users who will be able to design and manufacture products faster, and offer them with improved features or at a lower price.
Content published by Professional Engineering does not necessarily represent the views of the Institution of Mechanical Engineers.