Build Part Orientation Simulation for Additive Surface Quality
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Solution Overview
Problem
Current additive manufacturing techniques often result in suboptimal surface and sub-surface quality, leading to costly and labor-intensive post-processing requirements, with potential degradation of the build part's quality and increased scrap rates due to inadequate positioning of build parts during the manufacturing process.
Innovation Solution
An additive manufacturing system that determines geometrical characteristics of build part segments and generates a simulation model with quality scores, allowing for the optimization of part positioning to improve surface quality by adjusting the angle of incidence relative to the energy source, thereby reducing the need for post-processing and enhancing dimensional accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If build part positioning is determined without considering surface quality effects, then manufacturing process is simple and fast, but surface quality and sub-surface quality deteriorate leading to costly post-processing
Solution Approach 1:
The system performs preliminary analysis of build part positioning effects on surface quality before the actual manufacturing process. By evaluating geometric characteristics and predicting quality outcomes in advance, the system enables optimization of positioning parameters without adding complexity to the manufacturing execution phase.
Solution Approach 2:
The system creates a virtual simulation model that copies and replicates the expected surface quality outcomes of different positioning scenarios. This digital twin approach allows evaluation of multiple positioning options without physical trial builds, eliminating the need for complex physical testing while predicting quality results.
2Manufacturing precision
If post-processing is performed to improve surface quality, then surface roughness is reduced, but manufacturing time and labor costs increase significantly
Solution Approach 1:
The system applies preliminary anti-action by predicting and preventing poor surface quality outcomes through optimized positioning selection. By identifying and avoiding positioning configurations that would produce rough surfaces requiring post-processing, the system eliminates the need for corrective post-processing operations while ensuring high surface quality from the start.
3Productivity
If build parts are positioned to maximize platform utilization, then production capacity increases, but surface quality may be compromised due to suboptimal positioning
Solution Approach 1:
The system applies local quality by evaluating and optimizing positioning for each individual build part or segment separately. By analyzing geometric characteristics of specific segments and their interaction with the energy source, the system determines optimal positioning for each local region, ensuring high surface quality even when multiple parts are arranged to maximize platform utilization.
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
The system enables the production of build parts with improved surface and sub-surface quality, reducing post-processing needs and scrap rates by predicting and optimizing the positioning of build parts before manufacturing, thus enhancing manufacturing efficiency and reducing production costs.
Implementation Method 1
The deposited layers are selectively fused via the application of a focused energy source, such as a laser, which heats and bonds the material.
Data Source
AI summary
An additive manufacturing system includes one or more processors configured to determine one or more geometrical characteristics of each of multiple segments of a build part at a candidate position of the build part relative to a platform. The one or more processors are configured to generate a quality score for each of the segments at the candidate position based on the one or more geometrical characteristics, The one or more processors are also configured to generate a simulation model of the build part at the candidate position for display. The simulation model includes graphic indicators corresponding to each of the segments. The graphic indicators are representative of the quality scores of the corresponding segments.