3D Print Infill Adjustment for Human-Interaction Stress Points
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Solution Overview
Problem
Existing 3D printing technologies lack the ability to dynamically adjust infill specifications at specific regions of potential stress points in a 3D object design, particularly for factors such as grasp affordance and human manipulation tasks, leading to inefficiencies in material usage and structural integrity.
Innovation Solution
A computer-implemented method and system that utilizes a trained model to identify regions of potential human interaction and mechanical stress in a 3D object, adjusting infill specifications such as pattern, height, and density using a 3D print infill control module integrated with slicer software to optimize print instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If uniform infill specifications are used throughout the entire 3D object, then printing time and material usage are reduced, but strength and resilience at stress points deteriorate
Solution Approach 1:
The patent applies local quality by varying infill specifications (density, pattern, height) specifically at identified stress points and regions of human interaction, while maintaining different specifications in non-critical areas. This allows the object to have enhanced strength where needed without compromising overall printing efficiency and material usage.
2Strength
If infill density is increased throughout the entire object, then strength and structural integrity are improved, but material usage and printing time increase
Solution Approach 1:
The system identifies specific regions requiring enhanced structural integrity (stress points, grasp affordance areas) and applies increased infill density only to those locations. Non-critical regions maintain lower infill density, optimizing the balance between structural integrity and material consumption.
Solution Approach 2:
The 3D object is segmented into different regions based on stress analysis and human interaction predictions. Each segment receives tailored infill specifications, allowing high material usage only where structurally necessary and reduced material usage in less critical areas.
3Strength
If multiple G-code file iterations are generated to fix weak points, then strength and resilience are improved, but development time and complexity increase
Solution Approach 1:
The system performs preliminary stress analysis and identifies potential weak points during the initial G-code generation process, before printing begins. By predicting stress points and adjusting infill specifications in advance, multiple iterative revisions are avoided, reducing software complexity and development time while ensuring resilience from the first print.
Solution Approach 2:
The system incorporates feedback from stress analysis algorithms and human interaction predictions to automatically adjust infill specifications. This closed-loop approach eliminates the need for manual trial-and-error iterations, as the system self-optimizes the G-code based on predicted performance requirements.
Data Source
AI summary
Embodiments of the disclosure provide systems and methods for implementing 3D printing to manufacture 3D print objects with dynamic adjustment of 3D print infill specifications based on determined regions of stress points in a given 3D device design. A disclosed method comprises receiving a 3D object design for a 3D device to be printed; determining, based on the 3D object design and a trained model, a region of the 3D object with a projected likelihood of human interaction above a threshold likelihood; and generating, based on the determined region of the 3D object, instructions to selectively adjust one or more print infill specifications at the region.