Disney Research produces 3D-printed objects with variable elasticity using single material
Additive manufacturing technique uses small-scale structures to create soft or stiff zones in a printed object.0
At SIGGRAPH 2015 in Los Angeles next week, Disney Research announced it will present a unique 3D printing technique that allows designers to create various levels of elasticity in a printed object using a single build material.
Rather than change the material itself, the technique relies on printing clusters of compatible microstructures – each measuring 8mm on a side – that work together to produce varying levels of elasticity in each region of the 3D printed object.
“Many functional objects in our everyday life consist of elastic, deformable material, and the material properties are often inextricably linked to function,” said Christian Schumacher, a Ph.D. computer graphics student at ETH Zurich and at Disney Research. “3D printing usually involves only a single material or a very small set of materials. However, 3D printing easily produces complex, 3D microstructures which we can use to create metamaterials with properties beyond those of standard printer materials.”
To develop the technique, the researchers began by sampling a number of microstructures to determine their properties. These were then grouped into families of similar structures that represent a range of elastic behaviours. They then created an algorithm for optimizing microstructure combinations, making sure that microstructures of different shapes connect properly.
In the demonstration objects, the team showed that this method could be used to produce fully articulated figures, with joints that bend even through the remainder of each limb was stiff. In addition, the team created a simple, two-fingered manipulator developed for a soft robot featured two tubes designed to bend only in one direction when a balloon inside was inflated or deflated.
In addition to Schumacher, the Disney team included Bernd Bickel and Markus Gross. Other members were Jan Rys and Chiara Daraio of ETH Zurich and Steve Marschner of Cornell University.