Additive Manufacturing Scan Parameter Optimization by Segment
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Solution Overview
Problem
Additive manufacturing processes face challenges in optimizing process variable values, such as energy beam parameters and hatching strategies, to achieve desired component properties like mechanical strength and productivity, as existing methods lack efficient methods for determining optimized settings that balance competing objectives like construction speed and component quality.
Innovation Solution
A method that involves defining segments within the manufacturing area, optimizing process parameter sets, and determining segment scanning direction distributions using a target function to achieve specific macro properties like stiffness and construction rate, while minimizing parameter set changes and segment boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If process parameter values are optimized for construction speed, then productivity is improved, but component quality and mechanical strength deteriorate
Solution Approach 1:
The manufacturing area is divided into multiple segments, allowing different process parameter sets to be applied to different segments. This enables optimization of construction speed in non-critical segments while maintaining quality in critical segments, resolving the contradiction between productivity and component quality.
Solution Approach 2:
Different process parameter sets are assigned to different segments based on their specific quality requirements. Critical segments receive parameter sets optimized for quality, while non-critical segments use parameter sets optimized for speed, allowing local optimization rather than uniform settings across the entire build area.
2Manufacturing precision
If process parameter values are optimized for mechanical strength, then component quality is improved, but construction speed and productivity deteriorate
Solution Approach 1:
The build area is segmented to distinguish between critical and non-critical regions. Critical segments use parameter sets optimized for mechanical strength, while non-critical segments use faster parameter sets, thereby maintaining overall productivity while ensuring required strength in essential areas.
Solution Approach 2:
Each segment is assigned process parameter values tailored to its specific requirements. Segments requiring high mechanical strength receive corresponding parameter optimization, while other segments use parameters optimized for speed, achieving local quality differentiation.
3Stability of the object's composition
If the number of parameter set changes is reduced, then process stability is improved, but adaptability to different segment requirements deteriorates
Solution Approach 1:
The manufacturing area is divided into segments that can be assigned different parameter sets. This segmentation allows the system to adapt to different segment requirements while maintaining stability within each segment by using consistent parameter sets throughout each segmented region.
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
This approach enables the generation of optimized process variable values that improve the property profile of additively manufactured components, balancing competing objectives and ensuring compliance with quality requirements, thereby enhancing productivity and cost-effectiveness.
Implementation Method 1
the construction material is selectively solidified by spatially limited irradiation of the points that are to be part of the manufacturing product to be manufactured after production in a kind of 'welding process', in which the powder grains of the construction material are partially or completely melted with the help of the energy introduced locally by the radiation at this point
Implementation Method 2
After cooling, these powder grains are then bonded together to form a solid
Data Source
AI summary
Disclosed is a method and device for generating optimized process variable values for an additive manufacturing process of a manufactured product. Requirement data of the manufactured product is provided and includes at least geometric data of the manufactured product. A region is then defined which encompasses the manufactured product. The manufactured product includes at least one segment. An optimization process is then carried out for the at least one segment in the defined region to select at least one optimal parameter set, which includes a defined group of process parameter values, from candidate parameter sets, to ascertain an optimized segment scanning direction distribution using a defined target function and the requirement data. The optimal parameter set and the optimized segment scanning direction distribution are provided in the form of optimized process variable values.