Voxel Data Mapping for Additive Manufacturing Quality Assurance
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Solution Overview
Problem
Industrial additive manufacturing processes, particularly powder-bed-fusion methods like selective laser melting, face challenges in quality assurance and certification due to the complexity of managing large amounts of data generated during the process, which often leads to insufficient data handling and manual, time-consuming quality observation.
Innovation Solution
A computer-implemented method that provides structured data by mapping three types of coded data—about the machine setup, build area, and quality monitoring—into a voxel field, allowing for efficient data handling and quality assurance. This method enables the correlation of quality-relevant information with specific voxels, facilitating the identification and classification of defects during the additive manufacturing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive process monitoring is implemented to detect flaws and defects, then quality assurance capability is improved, but data management complexity and supervision effort increase
Solution Approach 1:
The patent segments the continuous manufacturing process data into discrete voxel units, where each voxel represents a specific spatial location and contains relevant quality information. This segmentation transforms the overwhelming continuous data stream into manageable discrete units that can be independently analyzed and stored, reducing data management complexity while maintaining comprehensive quality monitoring capability
Solution Approach 2:
The patent introduces an intermediary data structure layer between the raw sensor data and the quality assurance evaluation. This intermediary structure processes and organizes raw monitoring data into structured voxel information, automatically filtering and categorizing data before it reaches the quality evaluation system, thereby reducing supervision effort while preserving reliability
2Measurement precision
If detailed process data is recorded for every layer and sensor reading, then quality control precision is improved, but data storage requirements and processing time increase
Solution Approach 1:
The patent extracts only the quality-relevant information from the comprehensive process data and stores it within the voxel structure. Instead of retaining all raw sensor readings and process parameters, the system selectively extracts and stores only those data elements that are critical for quality assessment, thereby maintaining measurement precision while significantly reducing data storage requirements and processing time
Solution Approach 2:
The patent implements partial action by recording detailed data for only those voxels that contain quality-relevant information, rather than processing and storing exhaustive data for every single voxel. This selective approach maintains quality control precision for critical areas while reducing overall processing time and storage requirements
Data Source
AI summary
A computer-implemented method of providing structured data of an additive manufacturing process includes providing a first type of data (i) with coded information about a machine set up and/or about a prepared build job, providing a second type of data (ii) with coded information about a build area, providing a third type of data (iii) with coded information about a quality monitoring during the manufacturing process, the information from each type of data being different from one another, and mapping the first, the second and the third type of data to a voxel field (Vn). Each voxel of the field, representing a three-dimensional portion of a 3D-model of the component to be manufactured, is correlated to the first, second and third type of data in a coded way. A related data structure product, apparatus, communication apparatus, and additive manufacturing device are provided.