by: Anthony Garland
After a previous post about "What should we print?", I received feedback that the post was not clear. The central theme of the last post is that "To take full advantage of additive manufacturing we must think of designs as a process rather than a final geometry." To take the full benefits of additive manufacturing, design automation must be used.
In this example, the left side of the design is clamped to a wall. A load is put on the right side. Also, a heat source is applied everywhere in the design area, and a heat sink is applied in the middle. The green material is strong and stiff but does not conduct heat well. In contrast, the blue material conducts heat very well but is flexible. The optimizer seeks to find the optimal placement material verse space, and it attempts to find the optimal placement of the two materials with different properties.
The challenge of designing one-off parts with additive manufacturing is testing and evaluation. Since one-off parts can not be tested with destructive tests, the physical simulations of the product and the manufacturing (3D printing in this case) must be highly accurate to ensure the product behaves property. The current lack of a complete understanding and simulation of the physical processes during 3D printing is one of the challenges holding 3D printing back. However, many researchers are working on solving this problem. In the videos above, the question is, "will the materials behave like the simulation predicts".
The future is exciting when we consider the possibility of using machine learning to mine information from our personal devices coupled with design automation to generate personalized products instead of mass producing one-size fits most products.
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