Additive Component Builds Using Submodel-Specific Processing Strategies
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional additive manufacturing methods use a single processing strategy, which can be slow and wasteful, and fail to meet the diverse design specifications of different features within a component.
Innovation Solution
Decompose a component model into submodels based on preselected metrics, assign specific build parameters to each submodel, and use multiple processing strategies to manufacture the component in a single build, ensuring each subcomponent meets its designated quality metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a single processing strategy is used to build up each layer of the component, then the manufacturing process is simple and easy to control, but the manufacturing speed is slow and material deposition is wasteful
Solution Approach 1:
The component model is decomposed into multiple submodels based on different features and their associated quality metrics. Each submodel is then assigned a specific processing strategy optimized for its requirements. This segmentation allows different regions of the component to be manufactured using appropriate methods, improving overall productivity while maintaining ease of control through systematic organization.
Solution Approach 2:
The system dynamically selects and switches between different processing strategies during the manufacturing process based on the current submodel being manufactured. The controller automatically transitions between strategies without manual intervention, enabling the system to adapt to different feature requirements while maintaining operational simplicity.
2Manufacturing precision
If build parameters are selected to ensure one feature meets its quality metric, then that feature achieves the required quality, but other features with different metrics may not achieve their design specifications
Solution Approach 1:
Different build parameters and processing strategies are assigned to different submodels based on their specific quality requirements. For example, features requiring high precision may use parameters optimized for accuracy, while other features may use parameters optimized for different metrics. This local optimization ensures each feature achieves its specific design specifications without compromising others.
Solution Approach 2:
The system changes build parameters dynamically based on the active submodel. When transitioning between submodels with different quality metrics, the controller adjusts parameters such as laser power, scan speed, and layer thickness to match the requirements of the current feature, enabling multiple design specifications to be fulfilled within a single build.
3Productivity
If multiple processing strategies are used in a single build, then manufacturing efficiency and design intent are optimized, but the system complexity increases
Solution Approach 1:
The component is divided into submodels with clearly defined boundaries and associated quality metrics. This segmentation creates a structured framework that manages complexity by organizing the manufacturing process into discrete, manageable units, each with its own optimized processing strategy.
Solution Approach 2:
The controller uses feedback from the model decomposition and quality metric associations to automatically determine the appropriate processing strategy for each submodel. This closed-loop approach manages system complexity by using information from the design stage to guide manufacturing decisions, reducing the need for complex real-time decision-making.
Data Source
AI summary
Systems, methods, and non-transitory computer-readable medium are provided that enable a component to be additively manufactured in a single build with multiple processing strategies. In one example aspect, a model representing a component is decomposed into submodels that each correspond to a subcomponent of the component. Each of the subcomponents can have a preselected metric associated therewith. The model can be decomposed into the submodels based at least in part on the preselected metrics. A set of build parameters is selected or assigned to each of the submodels based at least in part on the preselected metrics associated with the subcomponents. Overlap regions can be defined at each interface between adjacent subcomponents. The build parameters selected for adjacent subcomponents can be used to blend the build parameters for the defined overlap regions. The submodels and the blended build parameters can be used to additively manufacture the component.