Split-Level Octree Layout for Scalable 3D Print Data
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Solution Overview
Problem
Additive manufacturing techniques face challenges in efficiently processing and storing large, complex three-dimensional object data models, particularly when high resolution is required, as existing methods like octree representations can overwhelm processing and storage resources, leading to scalability issues and increased processing times.
Innovation Solution
The method involves generating a split-level octree representation by subdividing volumetric space into a regular grid, building sub-volume octrees, and merging them to create a global volume octree, using a 'Z-first' ordering and serializing data to optimize storage and processing, allowing for efficient data extraction and layer generation in additive manufacturing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a traditional octree representation is used to store three-dimensional object data at high resolution, then the data precision and object detail are improved, but the processing time and computational resource requirements increase significantly
Solution Approach 1:
The patent divides the three-dimensional object data into multiple layers, where each layer contains a subset of the total voxels. This segmentation allows the processing system to handle smaller data portions sequentially rather than loading and processing the entire high-resolution dataset at once, thereby reducing peak memory requirements and processing time while maintaining data precision through systematic layer-by-layer reconstruction.
2Manufacturing precision
If high resolution three-dimensional object data is stored and processed, then the manufacturing precision and object quality are improved, but the storage resources and computational complexity increase
Solution Approach 1:
The patent segments high-resolution three-dimensional object data into multiple manageable layers, each containing a subset of voxels. This segmentation reduces the computational complexity by allowing sequential processing of smaller data portions rather than handling the entire high-resolution dataset simultaneously, while maintaining manufacturing precision through systematic reconstruction of complete object geometry from layered data.
Solution Approach 2:
The patent introduces a layer dimension to organize three-dimensional voxel data, transforming the storage and processing approach from a monolithic 3D structure to a hierarchical 3D-layered structure. This dimensional organization enables efficient memory management and computational processing by allowing the system to access and process only the necessary voxel subsets for each layer, reducing overall computational complexity while preserving complete object quality.
Data Source
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AI summary
In an example, a method includes receiving a first data model of an object to be generated in additive manufacturing, at a processor. Using the processor, a second data model may be determined. Determining the second data model may include generating for each of plurality of contiguous, non-overlapping sub-volumes of a volume containing the object, a sub-volume octree characterising the sub-volume and having a root node. Determining the second data model may further include generating a volume octree characterising the volume containing the object, the volume octree characterising in its lowest nodes the root nodes of the sub-volume octrees.