3D Printing Slice Data Generation Using Tree Data Structures
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Solution Overview
Problem
Existing 3-D printing technologies are limited to printing objects with a single material, requiring time-consuming manual assignment of materials and lacking the ability to handle complex or large datasets, and are unable to provide continuous gradation between multiple materials.
Innovation Solution
A system that generates slice data from a tree data structure by independently defining the shape and material specifications of a 3-D object, allowing for the creation of models that can be scaled to match printer resolution, enabling the use of multiple materials and continuous gradation through a computing device with modules for specification, merging, scaling, and slicing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual assignment of materials to each unstructured surface mesh is performed, then material distribution can be achieved, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent segments the material definition process from the shape definition process. Instead of manually assigning materials to each mesh, the system uses a tree data structure where shape and material are defined independently at different levels of the hierarchy, enabling automated material distribution without manual mesh-by-mesh assignment
Solution Approach 2:
The patent performs preliminary action by defining material specifications and shape specifications separately before merging them. The tree data structure is constructed with material information pre-defined at parent nodes, which is then automatically propagated to child nodes, eliminating the need for time-consuming manual material assignment after mesh creation
2Productivity
If CPU-based desktop applications are used to generate 3-D print data, then data processing can be performed, but the applications cannot handle large datasets that exceed printer hardware memory
Solution Approach 1:
The patent segments the 3-D object representation into a hierarchical tree data structure with parent and child nodes. This segmentation allows the large dataset to be divided into manageable portions that can be processed and stored efficiently, with only necessary data loaded into printer memory during operation
Solution Approach 2:
The patent transitions from a traditional flat data structure to a hierarchical tree structure with multiple levels. This dimensional change in data organization allows for efficient memory management by enabling the system to navigate and process data in a hierarchical manner, reducing the memory footprint required in the printer
3Ease of operation
If a single material is assigned to each unstructured surface mesh, then material assignment is simple, but continuous gradation between multiple materials cannot be achieved
Solution Approach 1:
The patent applies local quality by allowing different material properties to be defined at different levels of the tree data structure hierarchy. Parent nodes can define base material properties while child nodes can modify or refine these properties, enabling continuous material gradation while maintaining the simplicity of structured assignment
Solution Approach 2:
The patent introduces dynamics by enabling material specifications to be defined independently and then dynamically merged with shape specifications in the tree structure. This allows the material distribution to be flexible and adaptable, supporting continuous gradation between materials while maintaining ease of operation through structured definitions
4Adaptability or versatility
If shape and material specifications are defined independently, then scaling to match printer resolution becomes possible, but the data structure becomes more complex
Solution Approach 1:
The patent segments the specifications into independent shape and material components organized in a tree structure. This segmentation allows each component to be scaled and processed independently, enabling flexible adaptation to different printer resolutions while the hierarchical structure manages the complexity through organized separation of concerns
Data Source
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AI summary
An example technique for generating slice data from the tree data structure representation of a three dimensional (3-D) object can include obtaining a shape specification of the 3-D object and obtaining a material specification of the 3-D object. The example technique for generating slice data from the tree data structure representation of a 3-D object can also include merging the shape specification and the material specification to create a tree data structure representation of the 3-D object. The example technique for generating slice data from the tree data structure representation of a 3-D object can also include generating slice data from the tree data structure.