Product Designs Beyond Human Imagination

Artifical Intelligence

“Simply put, generative design means humans and computers working together to create objects beyond the human imagination alone.”

Product Designs Beyond the Human Imagination

Why future product development with generative design and artificial intelligence will now gain momentum

Paul Haimes, VP, Europe Technical Sales, PTC

The concept of generative design controlled by artificial intelligence (AI) in product development is not ground-breaking innovation. 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. In addition, it was 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.

But, a lot has happened since that time. Thanks to cloud technologies and advances in simulation technology, 3D printing, and, as one of the AI technologies, machine learning, the concept of generative design in product development is facing a broader application in the market. And with that, it is now time to think about the future role of the product developer.

Artificial Intelligence

Issue no 10 - April 2019 industry 4.0

The 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 a new product, component or larger construction - such as a bridge or a house - using the computer and modern CAD software as a tool, generative design turns the computer into the driving creative force.

Human beings first define design parameters and functional requirements such as maximum size (installation space), 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. Thus, 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.

The advantages that companies achieve through the generative design process alone are manifold: The productivity of the product development department in the design phase increases 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 optimization of new products for improved manufacturability, the reduction of material costs and shorter production times, and it allows a high degree of personalization, which will delight customers. Because simulation, analysis and manufacturing are all on the same level, the risk of costly rework is dramatically reduced, which can further reduce time to market.

AI chooses the “winner”

After several thousand design drafts have been developed, using generative design and a possible catalogue of boundary conditions, technology does not leave the human being alone - how should he finally determine which draft fits best? This part of the evaluation is carried out by AI. It selects the most suitable version and thus selects the “winner” 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 ie the lightest model with the greatest possible stiffness. Criteria can also be changed in real time, whether it’s material or design requirements, as well as parameters linked to production costs, such as production volume, are converted immediately by the software.

The technology provides the developer with optimized 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 also greatly increases output. The “aided” in CAD - Computer Aided Design - is finally actually implemented.

industry 4.0 Issue no 10 - April 2019Artificial Intelligence

Generative design is not topology optimization

At this point, it is important to review the difference between generative design and other technologies such as topology optimization, grid optimization or the like, 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 optimization of an already existing design through simulation on the 3D model.

Here, for example, the aim is to reduce the weight without changing the outer shape of the component. However, this does not create completely new design possibilities as in generative design, but only optimized 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 thus also the role of the product developer or engineer himself. In the past, he was the driving creative force that delivered design drafts but in this process, he becomes more of a curator of the results.

Although he remains involved in the design phase from the outset, he only defines the parameters for the computer and then juggles 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 he no longer must defend his models against other decision-makers; after all, all of them have been created using algorithms, whereby the respective optimum can be assumed.

However, 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. Does a car ultimately have an appearance that appeals to the buyer despite its “optimal” design, or does it become a shelf warmer for car dealerships? 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 multisensory 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.

Artificial IntelligenceIssue no 10 - April 2019 industry 4.0

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, in which the ANSYS visualization technology and the Generative Design technology of the company acquired at the end of last year are frustrating. The joint solution shifts the analysis to the beginning of the design process.

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.

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