LPBF Printer Control Using In-Situ Surface Profiling
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Solution Overview
Problem
The laser powder bed fusion (LPBF) process faces challenges in maintaining product consistency and minimizing defects due to deviations from optimal processing conditions, particularly due to the complex thermal dynamics and unaccounted geometry/height dependency in existing control paradigms, leading to inconsistent densification across and within builds.
Innovation Solution
A controller and method that utilize in-situ surface profiling through imaging technologies like low coherence scanning interferometry to calculate height difference (HD) and surface smoothness (SS), correlating these metrics with process parameters using machine learning algorithms to adjust laser beam power and velocity in real-time, ensuring optimal densification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If fixed process parameters are used for LPBF printing, then the printing process is simple to control, but the densification rate becomes inconsistent across different build geometries and heights
Solution Approach 1:
The patent implements dynamic adjustment of process parameters (laser power, scan speed, hatch spacing) based on real-time build geometry and height. The system transitions from static fixed parameters to dynamic adaptive parameters that change during the printing process to maintain consistent densification across different build configurations.
Solution Approach 2:
The system incorporates feedback mechanisms where imaging data (optical or X-ray) is collected during printing, processed to determine actual build geometry and height, and used to adjust process parameters for subsequent layers. This closed-loop feedback ensures densification rate consistency despite geometric variations.
2Manufacturing precision
If real-time imaging and parameter adjustment is implemented, then densification consistency is improved, but the device complexity and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimal process parameters based on the known build model geometry before printing begins. This allows the system to anticipate required parameter changes rather than reacting to them in real-time, reducing processing delays.
Solution Approach 2:
The patent implements partial monitoring and adjustment by selecting specific key layers or critical build regions for imaging and parameter adjustment rather than continuously monitoring all layers. This selective approach maintains build quality while reducing the overall processing time and computational burden.
3Manufacturing precision
If geometry-dependent process parameters are used, then densification rate consistency across different builds is improved, but the ease of operation decreases
Solution Approach 1:
The system implements self-service by automatically extracting build geometry information from the CAD model or build file, calculating optimal process parameters, and configuring the printing parameters without requiring manual intervention or expert knowledge from the operator. The system self-adjusts based on the specific build geometry.
Solution Approach 2:
The patent creates a universal process control system that can handle different build geometries, sizes, and configurations using the same underlying methodology. The system performs multiple functions including geometry analysis, parameter optimization, real-time monitoring, and dynamic adjustment within a single integrated platform.
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
Achieves real-time optimization of build characteristics by dynamically controlling process parameters, improving densification rate and minimizing thermal stresses, thereby enhancing the quality and consistency of LPBF prints.
Implementation Method 1
utilize in-situ surface profiling through imaging technologies like low coherence scanning interferometry
Implementation Method 2
laser powder bed fusion (LPBF) process
Implementation Method 3
The laser powder bed fusion (LPBF) process... is intricately linked to the set process parameters (e.g., laser power and beam velocity)
Data Source
AI summary
A controller for a laser powder bed fusion (LPBF) printing apparatus receives imaging data obtained during printing of at least one layer of a build by the printing apparatus, processes the imaging data, and generates a surface profile of the at least one layer. The controller calculates values representing in situ height difference (HD) and in situ surface smoothness (SS) of the surface profile of the at least one layer. The HD and SS values are input to an algorithm trained to determine a densification rate of the at least one layer based on a correlation of HD and SS values with one or more printing process parameters. Based on the HD and SS values the algorithm outputs one or more control signals corresponding to the one or more printing process parameters to the LPBF printing apparatus to control printing according to a target densification rate in real time.