Time-Exposure Melt Path Imaging for Additive Manufacturing Quality
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Solution Overview
Problem
Existing additive manufacturing systems face issues with component quality due to excess heat and heat transfer variations, leading to poor surface finish and dimensional accuracy, especially at overhangs and downward-facing surfaces, and current imaging devices capture only partial melt pool images without reference to specific positions, requiring complex programming.
Innovation Solution
An additive manufacturing system with an imaging device that generates time exposure images of the entire melt pool, allowing for inspection of variations and defects, and using these images in a feed-forward process to improve subsequent component manufacturing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If imaging devices are used to capture melt pool during additive manufacturing, then process monitoring capability is improved, but device complexity and programming requirements increase
Solution Approach 1:
The imaging device captures melt pool images and feeds this information back to the control system, which adjusts processing parameters in real-time to optimize the additive manufacturing process. This feedback loop enables automated process control without requiring complex manual programming.
Solution Approach 2:
The system uses the melt pool imaging data to automatically self-adjust process parameters, reducing the need for external intervention and complex programming. The imaging system serves the dual purpose of monitoring and controlling the process.
2Productivity
If focused energy source is used to melt particulate, then manufacturing efficiency is improved, but component quality deteriorates due to excess heat and heat transfer variations
Solution Approach 1:
The imaging device provides real-time feedback on melt pool characteristics, enabling the control system to adjust energy source parameters to maintain optimal heat input, preventing both excess heat and heat transfer variations that degrade component quality.
Solution Approach 2:
The system dynamically changes processing parameters based on real-time melt pool imaging data, adjusting energy density, scan speed, and other parameters to maintain optimal manufacturing conditions throughout the build process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively captures the entire melt pool, determines light intensity variations, and corrects errors in real-time, enhancing component quality and manufacturing efficiency by providing visual feedback and improved machine control for precise geometries.
Implementation Method 1
generates a time exposure image of a melted particulate forming a melt pool
Implementation Method 2
excess heat and/or variation in heat being transferred to the metal powder by the focused energy source within the melt pool
Data Source
Figure 1~2
Figure 3~4
AI summary
An additive manufacturing system (100) includes a surface (112) holding a particulate (114) and a focused energy source (104) configured to generate at least one beam (132) that moves along the surface to heat the particulate to a melting point creating a melt path. A camera (136) is configured to generate an image (200, 300, 302) of the surface as the at least one beam moves along the surface. The camera has a field of view and is positioned in relation to the surface such that the field of view encompasses a portion of the melt path defining a plurality of rasters (202). The camera generates a time exposure image of at least the portion of the melt path defining the plurality of rasters.