Additive Manufacturing Quality Control via Overlapping Sensor Fusion
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Solution Overview
Problem
Powder bed fusion technologies face challenges in build quality and process repeatability due to variations in energy input and thermal characteristics, leading to fusion defects in 3D objects, which existing quality assurance systems struggle to address effectively with high data processing demands and inherent delays in feedback control.
Innovation Solution
An additive manufacturing system utilizing multiple image sensors with overlapping fields of view to capture a single, spatially resolved image of the energy input during consolidation, reducing data processing requirements and enabling real-time feedback control, while allowing for scalable high image resolution and noise calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling rate image sensors are used to monitor the build process, then measurement precision is improved, but data processing requirements and device complexity increase significantly
Solution Approach 1:
The patent extracts only the essential information needed for quality control by comparing images against reference images to identify deviations, rather than processing all captured image data. This selective extraction of critical defect information reduces the data processing burden while maintaining monitoring precision.
Solution Approach 2:
Reference images are captured and stored before the build process begins, establishing a baseline for comparison. This preliminary action enables real-time defect detection during building without requiring complex real-time analysis of all process parameters, simplifying the control processor requirements.
2Measurement precision
If high sampling rate image sensors are used to capture build process images, then measurement precision is improved, but feedback control time delay increases due to vast data volumes
Solution Approach 1:
The system extracts only the critical deviation information by comparing current layer images against reference images, identifying only areas that differ from the expected build pattern. This selective extraction eliminates the need to process vast volumes of complete image data, enabling real-time feedback control without significant time delays.
Solution Approach 2:
The patent applies partial action by monitoring only the critical regions where deviations from the reference image are detected, rather than analyzing every pixel of every captured image. This partial monitoring approach maintains defect detection accuracy while dramatically reducing processing time for feedback control.
3Manufacturing precision
If multiple image sensors with overlapping fields of view are used, then manufacturing precision is improved through comprehensive coverage, but device complexity increases
Solution Approach 1:
The build area is segmented into multiple zones, each monitored by a dedicated image sensor with a specific field of view. This segmentation allows comprehensive coverage of the entire build area while enabling the control processor to focus on analyzing only the relevant region for each sensor, reducing overall system complexity.
Solution Approach 2:
Multiple image sensors perform the same function of capturing build layer images, but with different fields of view. This multi-functionality provides redundant coverage and ensures that critical features are captured from multiple angles, improving manufacturing precision without requiring each sensor to perform different specialized functions.
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
This approach significantly reduces data processing power needs, provides accurate defect identification, and enables real-time feedback control, improving build quality and process repeatability by capturing energy input data during consolidation rather than relying on cooling characteristics, thus enhancing the precision and consistency of 3D object fabrication.
Implementation Method 1
a plurality of image sensors, each of the image sensors having a corresponding field of view covering at least part of the layer of material... to provide a single, spatially resolved image of the energy being input
Data Source
AI summary
An additive manufacturing system and method is provided for fabricating 3D objects (16) from successive layers (14) of material. The additive manufacturing system (10) has an energy projection assembly (20) for inputting energy (22) into a specified area within the layer (18) to consolidate the material; a plurality of image sensors (30, 32, 34), each of the image sensors having a corresponding field of view (35, 40, 42) covering at least part of the layer (18) of material, such that each of the fields of view at least partially overlap with the field of view of at least one other of the image sensors; and an image processor (56) to capture image data from each of the image sensors (30, 32, 34). The image processor (56) controls exposure times for each of the image sensors (30, 32, 34) and combines the image data from the image sensors to provide a single, spatially resolved image of the energy being input throughout the specified area for each layer (14) of material respectively for comparison against threshold data values to locate potential consolidation defects in the specified area.