A Distributed Task Scheduler for Cuttlefish::Web to Optimize the Cost and Runtime
Darmstadt, TU, Master Thesis, 2019
The ability to mass produce customized products by additively layering materials has placed 3D printing in the spotlight of the manufacturing industry. Cuttlefish is a 3D printer driver which generates printable files from a 3D mesh. When executed at scale, the driver consumes a considerable amount of computing resources. This highlights the need for a distributed system that is capable of efficiently scaling up or down depending on the type of input while operating under cost and time constraints. Through this master thesis, an intelligent task scheduler which runs print jobs on suitable computers and optimizes cost and runtime based on the user’s preference is implemented. Several Machine Learning algorithms are evaluated to build the system classification and running time prediction models, and the best performing model is deployed as a service. The realized architecture highlights methods to develop an Intelligent task scheduler. They also form a baseline for Cuttlefish::Web to be used on Cloud Infrastructure.
Continuous Property Gradation for Multi-material 3D-printed Objects
Solid Freeform Fabrication 2018: Proceedings of the 29th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference
Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference <29, 2018, Austin, TX, USA>
Modern AM processes allow for printing multiple materials. The resulting objects can be stiff/dense in some areas and soft/porous in others, resulting in distinct physical properties. However, modeling material gradients is still tedious with current approaches, especially when smooth transitions are required. Current approaches can be distinguished into a) NURBS-BReps-based and b) voxel-based. In case of NURBS-BReps, discrete material distributions can be modeled by manually introducing separate shells inside the object; smooth gradation can only be approximated in discrete steps. For voxel representations, gradation is discrete by design and comes along with an approximation error. In addition, interacting on a per-voxel basis is tedious for the designer/engineer. We present a novel approach for representing material gradients in volumetric models using subdivision schemes, supporting continuity and providing elegant ways for interactive modeling of locally varying properties. Additionally, the continuous volumetric representation allows for on-demand sampling at any resolution required by the 3D printer.