Abstract

It is well known that Additive Manufacturing offers excellent potential to achieve functional integration through new levels of component complexity that would have been inconceivable before. Simultaneously, this complexity has only a minor impact on the time and costs required for the manufacturing process. Yet, the current challenge is to exploit these technical advantages not only for individual components but also for complex applications. Reducing the part count has considerable potential for higher efficiency in manufacturing and operations and often offers an improved functionality. It also comes with less assembly, a lower part number to handle, less storage and overall decreased complexity amongst the weight reductions usually gained. But it takes currently a considerable manual effort in the component's design phase to take advantage of the possible complexity for achieving function integration. Also, in-depth knowledge of this process is often required to achieve good results. This presentation will show how current design generation tools can lead to an accelerated and simplified process. For this, simulation is applied at the beginning of the product development to gain more insights early in the process. This gives the designers a fast response to how the given requirements affect the design. The steady exchange between concept decisions and Generative Design simulations throughout the whole process can prevent wrong decisions due to lack of information in early phases. This process will be demonstrated using an example assembly from industry, in which a reduction of the components is carried out with the support of Generative Design. Special attention is paid to exploit the advantages of additive manufacturing, particularly its extensive design freedom. At the same time, the targeted application of generative design improves usability and enables the user to make critical design decisions early in the process. Ultimately, both the component reduction and the presented approach avoid unnecessary errors and costs while improving manufacturability.