In the classic design process, a prototype is the test of whether the design will stand up to reality. Can this be replaced by simulation?
Prototypes will continue to play a key role in the series production process in the long term and will not be completely replaced by the software-based simulation process. However, simulation is a key element in speeding up production and makes an important contribution to reducing the number of prototypes required for series production. This is because designers are faced with new challenges and complex workflows when it comes to material availability, quality and validation as well as the development of process parameters for a design. These include the preparation of 3D models and the seamless orchestration of workflows. The integration of advanced additive functions such as process simulation directly into the CAD environment is central to this. Cumbersome data conversions are a thing of the past. In addition, robust simulation tools not only uncover potential problems during the simulation, but also suggest appropriate solutions. An example from the software sector: Fusion 360 recognizes deformations that occur during 3D printing and simultaneously provides solutions. This is done even before the product is printed in order to avoid faulty prints and thus material loss. The simulation therefore saves time and material - and ultimately money.

So will physical prototypes one day become superfluous in the manufacturing industry - even for more complex products?
Technologies such as generative design and additive manufacturing or 3D printing make it possible to increase the consolidation of parts in manufacturing. Fewer individual construction parts mean a lighter, less complex and less failure-prone and simpler design. Reducing the complexity and number of parts in a unit usually leads to a simplification of prototyping. However, this does not mean that prototyping is no longer necessary. We see the trend that simulation helps to identify problems before moving on to prototyping. This means that there are fewer problems when creating the prototype and with the prototype itself. But: A complete elimination of the prototyping phase is not likely. Just think of the complexity of the production process or of complex, interdisciplinary machines, which would also require correspondingly complex, networked and mutually influencing simulation models. This is also where a compromise comes into play from a commercial perspective in terms of time-to-market.

To what extent are humans still needed at all to assess the quality of a simulated or even a real prototype?
In design, manufacturing, prototyping and production, the computer is a tool that supports humans in carrying out simulations, in generative design or in generating design scenarios. It is useful for making suggestions, identifying trends and efficiently developing the optimum solution thanks to its measurement technology and computing power. Powerful and accurate computer models, such as simulations, take the burden of calculation off the designer. The result: the designer has more time for creative and innovative work. Humans are still needed - think of haptics, aesthetic assessments or even just dealing with tolerances of any kind, which represent the striking difference between the perfect, virtual world and the real, actual world.

Are production processes conceivable in which the end customer orders and ultimately receives a product that has been automatically designed, tested and produced according to certain specifications?
Future design and manufacturing process technologies such as automation, additive manufacturing, 3D printing, generative design and simulation will make it possible for customers to order precisely tailored products that are also unique due to the individual combination of parameters. More sustainable materials support these scenarios. They all contribute to intelligent manufacturing. In order to keep the customer's individual, possibly varying requirements for the product up to date at all times, devices and machines with intelligent sensors upload the product data to the cloud for analysis so that feasibility and parameters are constantly checked and sources of error are identified and eliminated.

One example: Decathlon's concept bike, which was developed using generative design in Autodesk Fusion 360. It has the potential to be produced individually for each customer from aluminum using 3D printing to conserve resources. Generative design can solve various extremely complex challenges here in order to guarantee the quality and safety of the racing bike.