Mechanical design based on a generative algorithm inspired by nature and its complex and functionally optimized geometries.
In recent years, the Generative design concept has increased its importance. The generative process is based on more or less complex algorithms, which can be supported by artificial intelligence, machine learning and cloud service. There are tools more or less automated however we are still a long way from the concept of having an autonomous generation just pushing a button.
Actually some of these new tools are advanced topological optimization algorithms.
Topology Optimization is one of the best-known optimization methodologies in the Design for Additive Manufacturing (DfAM), obtaining greater importance than in the classic design context. Both Generative and Topology Optimization takes inspiration
from the natural dynamics of generation or of optimization: some from a global or macroscopic aspect, others more on the particular or microscopic.
Generative design is a macro-group of techniques and methodologies combined together to make the modelling process more efficient and to obtain improved performance. All the variables must be considered to obtain the maximum from this methodology, understanding how you can take advantage of the total component shape control.
In the mechanical field, in an elastic solid, every geometric discontinuity alters the distribution of the tensions in its surroundings, generally causing an increase in maximum tension.
Structural components often contain localized shape variations, realized for functional and construction reasons. Using generative design help control the distribution of tensions by controlling the form, “relaxing” the flow-lines of tensions.
The generative process and the programming of generative workflows are part of our daily modelling and designing, this is a tool that does not add to our choices but is an integral part of it.
Design for Additive Manufacturing