Abstract: A method of partitioning a model to facilitate printing of the model on a 3D printer includes identifying partition sensitive locations on the model and creating a binary tree with a root note representative of the model. An iterative partitioning process is applied to divide the model into objects by selecting a node of the binary tree without any children nodes, identifying a portion of the model corresponding to the node, and determining candidate cutting planes on the portion of the model based on the partition sensitive locations. During the process, analytic hierarchical processing (AHP) is applied to select an optimal cutting plane from the candidate cutting planes based on partitioning criteria. The optimal cutting plane is used to segment the portion of the model into sub-portions, and two children nodes representative of these sub-portions are created on the node of the binary tree.

Abstract: A computer-implemented method for ranking design parameter significance includes a computer receiving an input dataset representative of a physical object. This input dataset includes a baseline parameters and associated probabilities. The computer also receives performance requirements. For each respective baseline parameter, the computer performs an analysis process. During this analysis process, a range of parameter values are selected for the respective baseline parameter based on its corresponding probability distribution. The range of parameter values are segmented into parameter subsets and multiple instances of a simulation are executed using the performance requirements to yield snapshots. A Proper Orthogonal Decomposition (POD) basis is derived using the snapshots. A sensitivity analysis is performed based on the POD basis to yield a sensitivity measurement representative of an effect of variation of the respective parameter on the performance requirements.

Abstract: A method for processing a three-dimensional (3D) mesh model includes receiving a 3D mesh model. One or more regions including a potential sharp cusp are automatically detected. The automatically detected one or more regions are displayed to a user and an active region of the 3D mesh model is defined by the user. Sphere fitting and Laplacian smoothing are applied to the designated active region to remove a sharp cusp therefrom and to obtain a modified 3D mesh model.

Abstract: Systems and methods for support structures for additive manufacturing of solid models. A method includes receiving a solid model, for a physical object to be manufactured, that includes a plurality of boundary representation surfaces. The method includes analyzing the b-rep surfaces to generate point samples for potential support locations. The method includes clustering points on the solid model, corresponding to at least some of the point samples, to create support locations. The method includes generating column supports in the solid model that connect to the original solid model at the support locations. The method includes storing the solid model, including the column supports.

Abstract: Methods for structure preserving topology optimization of lattice structures for additive manufacturing. A method includes receiving an initial lattice model, a physical objective of the initial lattice model to be optimized, forces to be applied to the initial lattice model and their respective locations, and an optimal volume ratio for an optimized lattice model, computing a bounding box of the initial lattice model and an axis-aligned voxel grid, computing an implicit scalar field representation of an initial volume ratio of the initial lattice model, mapping the loads to their respective locations in the axis-aligned voxel grid, performing an additive topology optimization on the initial lattice model to create the optimized lattice model until the initial volume ratio satisfies the optimal volume ratio, and storing the optimized lattice model.

Abstract: A computer-implemented method of optimized lattice partitioning of solid 3-D models for additive manufacturing includes a computer receiving a 3-D model of an object to be printed and functional specifications indicating desired mechanical properties for portions of the object. The computer generates a plurality of lattice template structures based on the 3-D model and a uniform grid structure of an internal surface of the object. The computer determines material behaviors for each of the plurality of lattice template structures using the functional specifications and assigns the lattice template structures to locations in the uniform grid structure based on the material behaviors of the lattice template structures, thereby yielding a printable lattice.

Abstract: A method for designing a personalized medical device includes receiving a template design of a medical device. An image including a patient anatomical geometry is acquired. The template design is combined with the image including the patient anatomical geometry to create a custom medical device design. A region of interest encompassing the sharp concave edge is automatically identified within the custom medical device design using one or more seed points received from a user. Surface smoothing of the custom medical device design is performed within the region of interest to bolster a thickness of the custom medical device design. A 3D-printable model is obtained from the surface smoothed custom medical device design.

Abstract: A computer-implemented method for optimizing manufacturing of a product based on total life cycle energy consumption includes receiving manufacturing parameters associated with manufacturing the product according to a manufacturing process and a candidate hybrid manufacturing plan for implementing the manufacturing process using a first combination of additive manufacture techniques and non-additive manufacture techniques. An energy consumption dataset is generated comprising (i) first energy consumption data corresponding to a non-additive manufacturing process, (ii) second energy consumption data corresponding to an additive manufacturing process, and (iii) energy intensity data associated with manufacturing materials. Next, the total life-cycle energy consumption for the candidate hybrid manufacturing plan is computed.

Abstract: A computer-implemented method for ranking design parameter significance includes a computer receiving an input dataset representative of a physical object. This input dataset includes a baseline parameters and associated probabilities. The computer also receives performance requirements. For each respective baseline parameter, the computer performs an analysis process. During this analysis process, a range of parameter values are selected for the respective baseline parameter based on its corresponding probability distribution. The range of parameter values are segmented into parameter subsets and multiple instances of a simulation are executed using the performance requirements to yield snapshots. A Proper Orthogonal Decomposition (POD) basis is derived using the snapshots. A sensitivity analysis is performed based on the POD basis to yield a sensitivity measurement representative of an effect of variation of the respective parameter on the performance requirements.

Abstract: A method for processing a three-dimensional (3D) mesh model includes receiving a 3D mesh model. One or more regions including a potential sharp cusp are automatically detected. The automatically detected one or more regions are displayed to a user and an active region of the 3D mesh model is defined by the user. Sphere fitting and Laplacian smoothing are applied to the designated active region to remove a sharp cusp therefrom and to obtain a modified 3D mesh model.

Abstract: A method for designing a personalized medical device includes receiving a template design of a medical device. An image including a patient anatomical geometry is acquired. The template design is combined with the image including the patient anatomical geometry to create a custom medical device design. A region of interest encompassing the sharp concave edge is automatically identified within the custom medical device design using one or more seed points received from a user. Surface smoothing of the custom medical device design is performed within the region of interest to bolster a thickness of the custom medical device design. A 3D-printable model is obtained from the surface smoothed custom medical device design.

Abstract: Systems and methods for support structures for additive manufacturing of solid models. A method includes receiving a solid model, for a physical object to be manufactured, that includes a plurality of boundary representation surfaces. The method includes analyzing the b-rep surfaces to generate point samples for potential support locations. The method includes clustering points on the solid model, corresponding to at least some of the point samples, to create support locations. The method includes generating column supports in the solid model that connect to the original solid model at the support locations. The method includes storing the solid model, including the column supports.

Abstract: Methods for structure preserving topology optimization of lattice structures for additive manufacturing. A method includes receiving an initial lattice model, a physical objective of the initial lattice model to be optimized, forces to be applied to the initial lattice model and their respective locations, and an optimal volume ratio for an optimized lattice model, computing a bounding box of the initial lattice model and an axis-aligned voxel grid, computing an implicit scalar field representation of an initial volume ratio of the initial lattice model, mapping the loads to their respective locations in the axis-aligned voxel grid, performing an additive topology optimization on the initial lattice model to create the optimized lattice model until the initial volume ratio satisfies the optimal volume ratio, and storing the optimized lattice model.