Beam Lattice Modeling for Data-Efficient 3D Printing
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Solution Overview
Problem
Current additive manufacturing techniques face challenges in efficiently processing complex lattice-type structures, as polygon mesh models become large and inefficient with increasing complexity, leading to increased file sizes and computational costs, especially when trying to model and generate objects with intricate patterns and properties like density and strength.
Innovation Solution
The use of beam lattice models, which represent objects as vertices connected by beams with varying radii, allows for precise specification of infill patterns and object properties, transforming beam lattice data into volumetric data models that categorize sub-volumes as interior, exterior, or boundary, enabling data-efficient representation and generation of complex shapes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If polygon mesh models are used to represent lattice structures, then manufacturing precision can be maintained, but file size and computational costs increase significantly
Solution Approach 1:
The patent segments the lattice structure representation into two distinct data models: polygon mesh models for external surfaces and beam lattice models for internal structures. This segmentation allows each model type to be optimized for its specific purpose, with beam lattice models using fewer vertices and edges to represent infill patterns, thereby reducing overall data complexity while maintaining manufacturing precision for the lattice portions
Solution Approach 2:
The patent introduces a new dimensional aspect by adding beam-specific properties (radius, material composition, structural characteristics) to the traditional polygon mesh vertices and edges. This dimensional enrichment allows the data structure to capture lattice-specific information more efficiently, reducing the need for excessive geometric detail while preserving manufacturing precision
2Manufacturing precision
If complex infill patterns are modeled with high detail, then object properties like density and strength are precisely controlled, but file size increases
Solution Approach 1:
The patent changes the parameter set used to represent lattice structures by introducing beam-specific parameters (radius, material composition, structural properties) rather than relying solely on traditional mesh parameters. This parameter transformation allows complex infill patterns to be defined with fewer data points, as beam properties can be specified along continuous paths rather than requiring dense vertex networks, thereby controlling object properties with reduced data volume
Solution Approach 2:
The patent applies local quality by allowing different beam elements within the lattice structure to have different properties (radius, material, density) based on local structural requirements. This enables precise control of object properties like density and strength in specific regions without requiring high-detail modeling throughout the entire structure, thus reducing overall data volume while maintaining where needed
3Productivity
If beam lattice models are used instead of polygon mesh models, then data efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent creates a universal data structure that can represent both traditional polygon mesh objects and beam lattice structures within a single unified format. This multi-functionality allows the system to process beam lattice models more efficiently when appropriate, as the unified structure enables specialized optimization for lattice representations without sacrificing compatibility with conventional mesh processing, thereby improving overall data processing efficiency
Data Source
AI summary
In an example a method includes receiving, at processing circuitry, beam lattice data modelling at least part of a three-dimensional object to be generated using additive manufacturing as a beam lattice. A volumetric data model may be determined from the beam lattice data. Determining the volumetric data model may comprise dividing a volume containing the beam lattice data into sub-volumes and categorising the sub-volumes into (I) interior sub-volumes, which are wholly within a beam of the beam lattice; (ii) exterior sub-volumes which are wholly outside the beams of the beam lattice; and (ii) boundary sub-volumes which partially coincide with a beam of the beam lattice. The method may further comprise subdividing boundary sub-volumes and categorising the subdivided sub-volumes until a threshold volume size of boundary sub-volume is reached.