Additive Manufacturing Quality Assessment via Process Irregularity Frequency
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Solution Overview
Problem
Existing methods for assessing the quality of objects produced by additive layer construction methods, such as laser sintering or melting, often lead to incorrect classification of defects, making the process complex and costly.
Innovation Solution
A method and device that determine a quality indicator by analyzing the relative frequency of process irregularities across successive layers, assigning quality indicator values based on these frequencies, and using weighting factors to assess component quality, allowing for more precise evaluation of object quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods for assessing quality are used, then quality assessment is performed, but incorrect classification of defects occurs and the process becomes complex and costly
Solution Approach 1:
The patent changes the assessment parameters from complex multi-dimensional quality metrics to a simplified relative frequency calculation. By monitoring the relative frequency of process irregularities (RFPI) rather than attempting to classify each defect type, the system achieves more accurate quality assessment while reducing computational complexity. The key parameter transformation is from detailed defect classification to aggregate frequency measurement.
Solution Approach 2:
The patent extracts the essential quality indicator from complex process data by isolating the relative frequency of process irregularities as the sole critical parameter. Instead of analyzing multiple defect characteristics simultaneously, the method extracts and monitors only the frequency aspect, thereby simplifying the assessment process while maintaining or improving accuracy.
2Loss of information
If detailed defect classification is performed, then comprehensive quality information is obtained, but the assessment process becomes more complex and costly
Solution Approach 1:
The patent transforms the quality information representation from detailed defect classification data to a single relative frequency parameter. This parameter change maintains the essential quality information needed for decision-making while eliminating the complexity of multiple classification categories and their associated analysis procedures.
Solution Approach 2:
The patent applies local quality assessment by focusing on the specific aspect of process irregularity frequency rather than attempting to assess all possible defect characteristics uniformly. This localized approach to quality measurement provides sufficient information for quality control without the overhead of comprehensive classification.
Data Source
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AI summary
The invention relates to a method for determining a quality indicator of an object produced by means of an additive layer construction method comprising at least the following steps: a step (S1) of providing a first data set (1010), which is associated with a process-monitoring device, wherein in the first data set (1010), for each of a plurality of consecutive layers, process irregularity information determined by the process-monitoring device is associated with a number of solidified points, a step (S2) of determining a relative frequency of the presence of a process irregularity for the plurality of consecutive layers and assigning a quality indicator value (Ri, Si) to the solidified object cross-section in accordance with the determined relative frequency, wherein different value ranges of the relative frequencies are assigned different quality indicator values (Ri, Si), which indicate different quality levels, a step (S3) of generating a second data set (1020), in which a quality indicator value is assigned to the object cross-section in each of the plurality of consecutive layers, and a step (S4) of determining a quality indicator (Q) indicating the quality of the produced object by using the second data set (1020).