Digital Twin Surrogate Modeling for Additive Part Validation
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Solution Overview
Problem
In industrial manufacturing, especially with additive processes, existing methods fail to effectively quantify and validate performance variances in components, leading to unnecessary scrap and inefficiencies due to destructive testing, which does not account for aggregate influences on operational performance.
Innovation Solution
A digital integrated process that links as-built, as-manufactured, as-designed, as-simulated, as-operated, and as-serviced components through a unique digital twin framework, enabling automated, quantitative, and qualitative assessments of additive manufacturing processes to optimize material usage and reduce destructive testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If destructive testing is used to validate component tolerances, then manufacturing precision can be confirmed, but material loss and productivity decrease due to significant scrap generation
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical component that replicates its geometric and material properties. This digital replica allows for virtual testing and validation of tolerances without destroying the actual component, thereby eliminating scrap generation while maintaining precision validation capabilities
Solution Approach 2:
The patent replaces physical destructive testing with computational simulation and analysis. Instead of physically breaking components to test their limits, the system uses finite element analysis, stress simulations, and other computational methods on the digital twin to validate tolerances and predict performance
2Manufacturing precision
If destructive testing is performed to validate design tolerances, then component quality can be assessed, but loss of time increases due to extensive testing requirements
Solution Approach 1:
The patent performs tolerance validation and performance assessment in advance during the design and manufacturing planning phases using the digital twin. By conducting virtual testing before physical production, the system identifies potential issues early, eliminating the need for extensive time-consuming physical testing later
Solution Approach 2:
The digital twin serves as a virtual replica that can be tested repeatedly and instantaneously without the time constraints of physical testing. Multiple simulation scenarios can be run in parallel, dramatically reducing the time required to validate tolerances and assess quality
3Productivity
If traditional manufacturing methods are used with predetermined tolerances, then production can proceed efficiently, but reliability decreases because as-manufactured parts differ from as-designed parts due to process variations
Solution Approach 1:
The patent establishes a feedback loop where measurement data from actual manufactured components is fed back into the digital twin model. This allows the virtual model to continuously update and reflect real-world process variations, enabling more accurate predictions of actual component performance and informing adjustments to maintain reliability
Solution Approach 2:
The system dynamically adjusts tolerance parameters and performance criteria based on measured process variations. Instead of using fixed predetermined tolerances, the digital twin model incorporates actual manufacturing data to adaptively determine acceptable parameter ranges that maintain reliability despite process variations
4Adaptability or versatility
If additive manufacturing processes are used to produce components, then manufacturing flexibility and customization improve, but measurement and validation complexity increases due to layer-by-layer construction and pre/post treatment steps
Solution Approach 1:
The patent creates a universal digital twin framework that can handle various additive manufacturing processes, materials, and post-treatment steps through a single integrated modeling approach. The system incorporates multiple physics domains (thermal, mechanical, material science) within one platform, reducing validation complexity despite process diversity
Solution Approach 2:
The patent divides the additive manufacturing process into discrete segments (layer deposition, heating, curing, post-treatment) that can be individually modeled and validated in the digital twin. This segmentation allows for systematic validation of each process step while maintaining overall process integration, making the complex validation manageable
Data Source
AI summary
There are provided methods and systems for making or repairing a specified part. For example, there is provided a method for creating an optimized manufacturing process to make or repair the specified part. The method includes receiving data from a plurality of sources, the data including as-designed, as-manufactured, as-simulated, and as-tested data relative to one or more parts similar to the specified part. The method includes updating, in real time, a surrogate model corresponding with a physics-based model of the specified part, wherein the surrogate model forms a digital twin of the specified part. The method includes further updating the surrogate model with a model of manufactured variance associated with at least one of inspection and in-operation data of a similar part. The method includes executing, based on the digital twin, the optimized manufacturing process to either repair or make the specified part.