The "organic" shape generated from topology optimisation is a good idea. But I think the designer will need to able to edit that later to make the shape more practical to be manufactured, more functional in real life applications, and better in aesthetic look. For example, the optimised shape may collect dust and water, thus prone to corrosions. The designer can put it back for a final FEA later.
The results from the NX Topology Optimizer are fully editable as was mentioned in the video. Additionally, in this particular case additive manufacturing (3D printing) was the intended outcome for this part -- this was covered in the video as well. Lastly, it was mentioned that the user can now select 5-axis milling during the setup of the Topology Optimizer, which will result in a part that can be manufactured using more traditional processes. Refinements may be necessary depending on individual design engineer preferences and/or corporate design standards. Hope this helps.
Hi and thanks for the question. If Jeff isn't available to answer, please note that the best way to get technical support for our products is to open a ticket in our Support Center at sie.ag/44GBtZ. This will ensure your question is quickly routed to the correct technical support resource. ~ Team Siemens
While you are correct that the concept of Topology Optimization has been around for decades, there have been significant advancements through machine learning and deep learning, which are subsets of AI, that improve and accelerate the optimization process. So, Topology Optimization itself is not "AI," but the application of AI methods to Topology Optimization is what we mean by "AI-enabled."
The "organic" shape generated from topology optimisation is a good idea. But I think the designer will need to able to edit that later to make the shape more practical to be manufactured, more functional in real life applications, and better in aesthetic look. For example, the optimised shape may collect dust and water, thus prone to corrosions. The designer can put it back for a final FEA later.
The results from the NX Topology Optimizer are fully editable as was mentioned in the video. Additionally, in this particular case additive manufacturing (3D printing) was the intended outcome for this part -- this was covered in the video as well. Lastly, it was mentioned that the user can now select 5-axis milling during the setup of the Topology Optimizer, which will result in a part that can be manufactured using more traditional processes. Refinements may be necessary depending on individual design engineer preferences and/or corporate design standards. Hope this helps.
Hi and thanks for the question. If Jeff isn't available to answer, please note that the best way to get technical support for our products is to open a ticket in our Support Center at sie.ag/44GBtZ. This will ensure your question is quickly routed to the correct technical support resource. ~ Team Siemens
That's just topology optimisation that's been around for decades. There is no AI for topology optimisation. Don't slap the term "AI" onto everything.
While you are correct that the concept of Topology Optimization has been around for decades, there have been significant advancements through machine learning and deep learning, which are subsets of AI, that improve and accelerate the optimization process. So, Topology Optimization itself is not "AI," but the application of AI methods to Topology Optimization is what we mean by "AI-enabled."
@@jeffmiller6366 What AI has been applied to topology optimisation in this case?
@@youtuberschannel12 so real man , you choose to speak truth