Digital Twin Feedback for Additive Manufacturing Quality Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In industrial manufacturing, especially with additive manufacturing, existing methods fail to effectively quantify and validate performance variances in components, leading to unnecessary scrap due to destructive testing and inability to assess fitness for operation, and do not consider operational characteristics throughout a component's life cycle.
Innovation Solution
Integration of operational characteristics with design and manufacturing processes through a digital integrated process that creates a digital twin of hardware components, allowing for continuous data collection and analysis across a component's life cycle, including additive manufacturing aspects, to optimize manufacturing and repair processes while reducing material waste and 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 waste increases significantly
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical component that replicates its geometry, material properties, and manufacturing process. This digital replica can be tested and validated without destroying the physical component, thereby confirming manufacturing precision while eliminating material waste from destructive testing
Solution Approach 2:
The patent replaces physical destructive testing with computational simulation and analysis in the digital twin environment. Instead of physically breaking components to validate tolerances, the system uses virtual modeling, finite element analysis, and digital simulation to confirm manufacturing precision without material loss
2Manufacturing precision
If traditional manufacturing validation methods are used, then component tolerances can be checked, but the fitness for operation under real operating conditions cannot be assessed
Solution Approach 1:
The patent performs preliminary validation of component fitness for operation during the design and manufacturing planning stages using the digital twin. By simulating operating conditions, thermal cycles, and mechanical loads in the virtual environment before physical production, the system identifies potential issues early and optimizes the manufacturing process to ensure reliability without requiring extensive physical prototyping
Solution Approach 2:
The patent establishes a feedback loop where operational data from actual component performance is continuously fed back into the digital twin model. This allows the virtual model to be refined and updated with real-world data, improving its accuracy in predicting fitness for operation and enabling continuous validation of both manufacturing precision and reliability throughout the component lifecycle
3Manufacturing precision
If components are scrapped due to unquantifiable variance influences, then manufacturing quality control is maintained, but productivity decreases
Solution Approach 1:
The patent introduces the digital twin as an intermediary between manufacturing processes and quality assessment. This virtual model quantifies the influence of manufacturing variances by simulating how specific deviations affect component performance and fitness for operation. Instead of scrapping components based on unquantifiable uncertainty, the digital twin provides data-driven insights that allow quality control while maximizing useful life utilization
Data Source
Figure 1
Figure 2
Figure 3
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 by a system configured to make or repair the specified part and from a machine communicatively coupled with the system, a set of sensor data and/or inspection data associated with at least one of an additive and a reductive manufacturing or repair process or with at least one of a pre-treatment and a post-treatment step. The method includes creating an optimized manufacturing process to make or repair the specified part, the creating including. 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 the sensor data and/or inspection data. The method includes executing, based on the digital twin, the optimized manufacturing process to either repair or make the specified part.