3D Print Slice Adjustment Using Meso-Skeleton Feature Sizing
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Solution Overview
Problem
Additive manufacturing technologies face challenges in printing complex shapes with small features due to minimum printable feature size limitations, leading to poor quality or failed prints, as existing methods fail to accurately account for manufacturing constraints during the design stage.
Innovation Solution
A method that divides a 3D object into slices, applies a thinning algorithm to construct a meso-skeleton, and adjusts each slice to a slice-specific printable feature size, ensuring the print head can traverse the maximal allowable region, thereby modifying the design to accommodate the manufacturing process and minimize shape alterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the minimum printable feature size is used to ensure manufacturability, then complex shapes with small features can be printed, but the design fidelity and shape accuracy deteriorate
Solution Approach 1:
The patent applies different feature sizes locally across the build plate based on spatial distribution analysis. The build plate is divided into multiple zones, and each zone is assigned a specific feature size optimized for the local geometry. This allows small features to be printed with higher precision in critical areas while using larger features in less critical areas, thereby maintaining shape accuracy where needed while ensuring overall manufacturability.
Solution Approach 2:
The patent dynamically adjusts the feature size parameter during the printing process based on the spatial location being printed. Rather than using a fixed minimum feature size throughout, the system varies the feature size dynamically according to the local geometric requirements of different regions of the model, optimizing both manufacturability and shape accuracy for each local area.
2Reliability
If a fixed minimum feature size is applied throughout the build plate, then manufacturing reliability is improved, but the ability to print complex shapes with varying feature requirements deteriorates
Solution Approach 1:
The system divides the build plate into multiple spatial zones and assigns different feature sizes to each zone based on the local geometric complexity and feature requirements. This localized approach maintains printing reliability by ensuring each zone uses an appropriate feature size for its specific geometry, while simultaneously improving adaptability to handle diverse complex shapes with varying feature requirements across different regions.
Solution Approach 2:
The build plate is segmented into multiple zones with distinct feature size requirements. Each zone is independently analyzed and assigned a feature size optimized for its local geometry. This segmentation allows the system to maintain high printing reliability in each zone while achieving versatile capability to print complex shapes with varying feature requirements across the entire build plate.
3Manufacturing precision
If variable deposition size is used to optimize print quality, then shape accuracy is improved, but the complexity of the manufacturing process increases
Solution Approach 1:
The system performs preliminary spatial distribution analysis and zone division before the actual printing process. The build plate is pre-segmented into zones with assigned feature sizes based on geometric analysis. This preliminary preparation simplifies the printing process itself, as the variable feature sizes are predetermined and automatically applied during printing, reducing real-time decision complexity while maintaining high print quality.
Solution Approach 2:
The patent systematically varies the deposition size parameter across different spatial zones based on pre-analyzed geometric requirements. This controlled parameter change approach improves print quality by matching feature sizes to local geometry, while the systematic nature of the variation (based on predefined zones) keeps the process complexity manageable through automation.
Data Source
AI summary
A three-dimensional object model is divided into slices that are targeted for an additive manufacturing process operable to deposit material at a variable deposition size ranging between minimum and maximum printable feature sizes. For each of the slices, a thinning algorithm is applied to contours of the slice to form a meso-skeleton. Topological features of the thinned slice are reduced over a number of passes such that a portion of the meso-skeleton is reduced to a single pixel wide line. Based on the number of passes, a slice-specific printable feature size within the range of the minimum and maximum printable feature sizes is determined. An adjusted slice is formed by sweeping the meso-skeleton with the slice-specific printable feature size. The adjusted slices are assembled into an object model which is used to create a manufactured object.