3D Printed Support Removal Using Adaptive Vision-Guided Cutting
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Solution Overview
Problem
Current 3D printing technologies face limitations in automation, leading to high costs and inefficiencies due to manual pre-and post-processing steps, particularly in removing support structures from 3D printed components, which results in inconsistent and time-consuming processes.
Innovation Solution
An autonomous system that uses a vision system with machine learning algorithms to identify and separate 3D printed components from their support structures by generating cutting paths based on CAD models and real-time data, incorporating markers for encoding information and enabling automated post-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated removal of support structures is performed using pre-programmed path trajectories, then automation level increases, but cutting accuracy decreases due to physical deformations causing inconsistent cuts
Solution Approach 1:
The system performs preliminary scanning of the actual component geometry before generating cutting paths. This preliminary action captures the real positions of support structures and connection points, allowing the cutting path to be adapted to actual physical deformations rather than relying on theoretical CAD models alone.
Solution Approach 2:
The system implements feedback by comparing actual component geometry (scanned after printing) with the planned cutting paths. The scanning system provides real-time information about support structure positions, enabling dynamic adjustment of cutting trajectories to maintain precision despite physical deformations during printing.
2Manufacturing precision
If manual post-processing steps are performed, then cutting accuracy can be maintained, but productivity decreases and costs increase
Solution Approach 1:
The system enables self-service automation where the component itself provides the information needed for its own processing. Scanning the actual component geometry allows the system to automatically generate appropriate cutting paths without manual intervention, making the process self-adapting and eliminating the need for manual programming while maintaining precision.
Solution Approach 2:
The patent replaces manual mechanical operations with an automated system combining scanning technology and adaptive path generation. Instead of manual measurement and path planning, the system uses automated scanning to capture geometry and algorithmically generates cutting paths, substituting human skill with automated sensing and computation.
3Ease of manufacture
If support structures are physically cut to separate components, then removal effectiveness improves, but quality consistency decreases due to unpredictable deformations
Solution Approach 1:
The system performs preliminary scanning to identify the actual positions of support structures and connection points before cutting. This preliminary detection ensures that cutting paths are based on real geometry rather than theoretical models, improving both removal effectiveness and consistency across different components.
Solution Approach 2:
The system dynamically adjusts cutting path parameters based on scanned geometry data. By changing the cutting trajectory parameters to match actual support structure positions and account for printed deformations, the system maintains consistent quality across different components while ensuring effective separation.
4Adaptability or versatility
If 3D printing is used for high flexibility and customization, then adaptability improves, but automation level remains limited due to manual pre- and post-processing steps
Solution Approach 1:
The system enables 3D printed components to self-identify their geometry through scanning, automatically generating the information needed for post-processing. This self-service capability eliminates manual measurement and path planning, allowing high customization while maintaining automation throughout the workflow.
Solution Approach 2:
The scanning and path generation system serves multiple functions: it captures geometry for cutting path generation, identifies support structure locations, and adapts to various component designs. This universal approach handles different geometries and materials through the same automated process, maintaining both customization and automation.
Data Source
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AI summary
A system and method are described for post-processing 3D printed components. Post-processing may include removing support structures for the 3D printed components and may also include other processes like assembling 3D printed components into finished products. In the system and method, post-processing strategies are iteratively generated and performed on 3D printed components. Performance metrics of the post-processing strategies are compared with a user-defined performance indicator in a learning process to improve the post-processing strategy over a number of 3D printed components.