3D Printing Quality Assessment via Parameter Range Comparison
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Solution Overview
Problem
3D printing processes often result in objects that fail to meet required specifications due to calibration losses, leading to costly errors in complex part production that consume significant time and materials.
Innovation Solution
A computer-implemented method for quality assessment of 3D printed objects, using input data from production parameters compared to predefined ranges, with machine learning techniques to determine optimal parameter settings, and real-time quality determination to prevent inferior product completion, allowing for calibration or abortion of the printing process as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If 3D printing processes are used to produce objects, then productivity and manufacturing capability are improved, but manufacturing precision and reliability deteriorate due to calibration losses and multiple error sources
Solution Approach 1:
The system performs preliminary quality assessment by comparing production parameters against predefined ranges before the printing process completes. This early detection prevents inferior objects from being fully produced, resolving the contradiction by maintaining precision through advance intervention while preserving productivity by avoiding rework of completed parts.
Solution Approach 2:
The system implements continuous feedback by monitoring production parameters during the printing process and providing quality assessment results that can trigger calibration or abortion actions. This closed-loop feedback mechanism maintains manufacturing precision while allowing the high productivity of 3D printing to continue through automated quality control.
2Manufacturing precision
If quality assessment is performed after printing completion, then manufacturing precision can be verified, but loss of time and materials increases due to discarding inferior objects
Solution Approach 1:
The quality assessment is performed preliminarily during the printing process rather than after completion. By monitoring production parameters and comparing them to predefined ranges in real-time, the system can detect quality issues before they result in fully printed inferior objects, thereby verifying precision without wasting time and materials.
Solution Approach 2:
The system enables skipping the remainder of the printing process when quality issues are detected. By aborting the printing operation upon detecting parameter deviations, the system rushes through the quality assessment phase and avoids completing the production of defective objects, thus preventing time and material loss.
3Manufacturing precision
If quality assessment is performed after printing completion, then manufacturing precision can be verified, but loss of substance increases due to discarding materials
Solution Approach 1:
The system performs preliminary quality assessment by monitoring production parameters during the printing process. By detecting deviations from predefined parameter ranges before the printing completes, the system verifies manufacturing precision without consuming additional raw materials on defective parts.
Solution Approach 2:
The system enables skipping the remainder of the printing process when quality issues are detected, thereby rushing through the assessment phase and preventing further consumption of raw materials on objects that will ultimately be discarded.
4Manufacturing precision
If real-time quality assessment is implemented, then manufacturing precision is maintained, but device complexity increases
Solution Approach 1:
The system implements quality assessment by establishing feedback loops that compare production parameters against predefined ranges. This feedback mechanism maintains manufacturing precision through automated monitoring and decision-making, managing device complexity by using rule-based comparisons rather than complex real-time analysis systems.
Solution Approach 2:
The system enables self-service quality control where the printing system automatically monitors its own parameters and makes decisions about continuing or aborting prints. This self-monitoring capability maintains precision while managing complexity by eliminating the need for external quality control systems.
Data Source
AI summary
BASF SE 202490WO01 13 B16999WO ABSTRACT A computer-implemented method (100) for quality assessment of an object (3) produced by at least one 3D printer (1) using 3D printing processes is provided. The method (100) comprises receiving (101) input data, in particular via an input unit (4), of at least one production parameter pertaining to the production of the object (3). It further comprises comparing (102), in particular via a processing unit (5), the received at least one production parameter to at least one predefined demanded production parameter range and determining (103), in particular via the processing unit (5), printing quality based on the degree of agreement between the at least one production parameter and the at least one predefined demanded production parameter range. The quality assessment results of the object (3) are provided (104), in particular via an output unit (6). Further, an apparatus (2) for quality assessment of an object (3) produced by at least one 3D printer (1), a system for providing quality assessment of an object (3) produced by at least one 3D printer (1), a computer program and a computer-readable storage medium are provided. (FIG. 4)