Selective Laser Sintering Powder Composition Tracking
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Solution Overview
Problem
The quality of objects produced in selective laser sintering processes is often compromised due to unknown powder composition, particularly when using 'old powder' from previous manufacturing processes, as existing methods like the Melt Volume Rate Method are time-consuming and not suitable for all cases.
Innovation Solution
A method that tracks and documents the percentage of new and old powder used in each layer, utilizing an Integrated Quality Management System (IQMS) to ensure all powder components are known, allowing for precise calibration of the laser sintering machine and quality control, enabling reproducible and certified production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Melt Volume Rate Method is used to determine powder properties, then information about powder age and melting temperature is obtained, but the process becomes time-consuming and not suitable for all cases
Solution Approach 1:
The system performs preliminary tracking and documentation of powder composition (new vs. old powder percentages) from the moment powder is introduced into the manufacturing system. This preliminary action eliminates the need for time-consuming Melt Volume Rate Method tests later, as the composition data is already known and stored in the database for immediate use in quality control and calibration processes.
2Productivity
If old powder from previous manufacturing processes is reused, then material utilization is improved, but the composition of the powder becomes unknown and quality deteriorates
Solution Approach 1:
The system implements continuous feedback tracking of powder composition throughout the manufacturing process. When old powder is reused, the system automatically records and updates the composition data in the database, providing real-time feedback on the percentage of new versus old powder. This feedback mechanism ensures that quality control measures can be applied based on known composition data, maintaining manufacturing precision while enabling material reuse.
3Ease of manufacture
If the composition of powder is not known, then the manufacturing process is simpler, but the quality of produced objects cannot be verified and certification is compromised
Solution Approach 1:
The manufacturing system performs self-service quality documentation by automatically tracking and recording powder composition data throughout the manufacturing process. The system autonomously collects data on new and old powder percentages, stores it in the database, and makes it available for quality verification and certification without requiring external manual tracking or complex additional procedures, thus maintaining process simplicity while ensuring reliability.
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
Ensures the quality of manufactured objects is comprehensively documented and improved, allowing for reliable machine operation, quick identification of issues, and cost-effective problem-solving, particularly in industries with strict safety regulations like the aircraft industry.
Implementation Method 1
a laser 700 is also provided, which generates a laser beam 700a
Implementation Method 2
the laser beam 700a solidifies the powder 3 selectively at the points corresponding to the cross section of the object 2
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In a method for providing a material volume for a generative production method, a three-dimensional object (2) is formed by selective compacting of layers of a material at points corresponding to the cross-section of the object (2) in the respective layer. The present invention aims to provide a method with which the quality of the produced objects can be verifiably documented and thus further improved. Said method is characterized by the following steps: providing at least one first material volume that is characterized by at least one attribute, capturing data that relate to the at least one attribute of the first material volume, and storing the data relating to the at least one attribute of the first material volume.