Predefined Shape Libraries for Defect-Controlled Additive Manufacturing
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Solution Overview
Problem
Current additive manufacturing processes face challenges in consistently producing high-quality parts with minimal defects and distortion due to the wide range of energy source power levels and scan speeds required, and the decoupling of scan paths from process parameters, leading to inefficiencies and resource-intensive trial-and-error adjustments.
Innovation Solution
A method involving the segregation of a part's shape into predefined shapes from a library, assembling these shapes into a second model with predefined energy source power levels, scan paths, and scan speeds, and simulating areas between models to adjust parameters for minimal defects and distortion, allowing for efficient additive manufacturing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a broad range of energy source power levels and scan speeds are used to fuse feedstock powder, then flexibility in processing different materials is improved, but defects and distortion increase due to inadequate or excessive energy input
Solution Approach 1:
The scan path is divided into multiple segments, each with independently optimized process parameters (power level, scan speed). This allows different regions of the part to have tailored parameters suited to their specific geometric features and material requirements, preventing both inadequate and excessive energy input in different areas.
Solution Approach 2:
Different process parameters are applied to different regions of the scan path based on local geometric characteristics. Critical areas with complex features receive optimized parameter sets, while simpler regions use standard parameters, ensuring high precision where needed without compromising overall flexibility.
2Ease of operation
If scan path is automatically generated by additive manufacturing system based on CAD file, then ease of operation is improved, but defects and distortion occur due to decoupling from process parameters
Solution Approach 1:
The scan path generation and process parameter selection are merged into a unified system. The system simultaneously determines both the geometric path and the optimal process parameters for each segment, ensuring they are coupled and optimized together rather than independently.
Solution Approach 2:
The system dynamically adjusts process parameters (power level, scan speed) based on the generated scan path geometry. As the scan path encounters different geometric features, the parameters automatically change to match the local requirements, maintaining precision throughout the build.
3Manufacturing precision
If trial-and-error adjustments of CAD model, scan path, energy source power level, and scan speed are performed, then manufacturing precision is improved, but productivity is reduced due to time-consuming iterations
Solution Approach 1:
The system performs preliminary optimization of scan paths and process parameters using simulation and predictive algorithms before actual manufacturing. This preliminary action identifies optimal parameter sets and potential problem areas, eliminating the need for time-consuming trial-and-error iterations during production.
Solution Approach 2:
The system creates virtual copies of the build process through simulation to test and optimize scan paths and parameters digitally. By copying and testing scenarios in virtual space, optimization is achieved without consuming physical materials or machine time, then the validated parameters are applied to actual manufacturing.
Data Source
AI summary
A method includes accessing a first model defining a shape of a part. The shape of the part is segregated into a plurality of predefined shapes selected from a library of predefined shapes. The predefined models for each of plurality of predefined shapes are assembled into a second model defining the shape of the part. The part is additively manufactured according to the second model.