Digital Twin Fixture Design for Additive Manufacturing
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Solution Overview
Problem
Fixtures in manufacturing often prematurely fail due to lifecycle loading events and environmental characteristics, leading to abrupt stops in manufacturing processes, highlighting a need for robust and rapid fixture design that existing technologies fail to adequately address.
Innovation Solution
A method utilizing additive manufacturing and digital twin analysis, where historical fixture usage characteristics are applied to new designs through machine learning and Finite Element Analysis to simulate lifecycle usage, identify potential failures, and automatically modify the design to mitigate these failures, resulting in improved fixture performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fixture design methods are used, then manufacturing processes can proceed with standard design practices, but fixtures prematurely fail due to lifecycle loading events and environmental characteristics
Solution Approach 1:
The patent applies preliminary action by performing digital twin simulations and lifecycle analysis before the actual fixture is manufactured. The system predicts potential failure points and tests design modifications virtually, allowing designers to address reliability issues before production, thereby extending fixture lifespan without requiring extensive physical prototyping and testing cycles.
Solution Approach 2:
The patent creates a digital copy (digital twin) of the physical fixture that mirrors its geometry, material properties, and expected usage conditions. This digital replica allows for virtual testing and analysis of lifecycle loading events and environmental characteristics, enabling prediction of failure modes and optimization of the actual fixture design to improve reliability and extend lifespan.
2Reliability
If digital twin analysis and simulation are implemented, then fixture failure points can be predicted and prevented, but design and analysis complexity increases
Solution Approach 1:
The patent implements self-service by enabling the digital twin to automatically simulate lifecycle usage, identify failure points, and suggest design modifications without requiring extensive manual intervention. The system autonomously performs the complex analysis and prediction tasks, reducing the burden on designers while improving fixture reliability.
Solution Approach 2:
The patent manages design complexity by systematically varying and analyzing multiple parameters in the digital twin model, including material properties, geometric features, loading conditions, and environmental factors. This structured parameter exploration allows comprehensive reliability assessment while providing clear guidance on which specific parameter modifications will most effectively improve fixture performance.
3Duration of action of stationary object
If automated design modification is used to mitigate failure points, then fixture lifespan is extended, but manufacturing process complexity increases
Solution Approach 1:
The patent applies local quality by automatically modifying specific localized areas of the fixture design where failure points are predicted, rather than redesigning the entire fixture. The system targets particular geometric features, material distributions, or structural elements that need adjustment, making localized improvements that extend lifespan while minimizing changes to the overall manufacturing process.
Data Source
AI summary
Described are techniques for improved fixture design. The techniques include generating a digital twin of a new fixture using design information and usage characteristics of similar historical fixtures. The techniques further include simulating lifecycle usage of the new fixture using the digital twin. The techniques further include identifying a simulated failure point in the new fixture based on the simulated lifecycle usage. The techniques further include modifying the design information of the new fixture to mitigate the simulated failure point.