Optical Metrology Configuration from 3D Models
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Solution Overview
Problem
Optical metrology systems face challenges in achieving an effective configuration without extensive routines, requiring multiple physical adjustments and testing to accurately, comprehensively, and efficiently measure objects.
Innovation Solution
A metrology optimization system determines an optimal configuration for optical sensors based on 3D model and sensor information, minimizing sensor movement and optimizing placement and integration times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive configuration routines with multiple physical adjustments and testing are performed, then measurement accuracy and comprehensiveness are improved, but device complexity and time consumption increase
Solution Approach 1:
The system performs preliminary determination of optimal sensor configuration using 3D model information before actual measurement takes place. The optimization system calculates ideal sensor positions, orientations, and integration times in advance, eliminating the need for extensive physical adjustments and testing during the measurement process itself.
Solution Approach 2:
The system uses a digital 3D model copy of the object to determine sensor configuration instead of requiring physical trial-and-error adjustments on the actual object. This virtual modeling approach allows optimization to be performed computationally, reducing physical complexity and time requirements.
2Measurement precision
If extensive configuration routines with multiple physical adjustments are performed, then comprehensive measurement coverage is improved, but time consumption increases
Solution Approach 1:
The optimal configuration is determined in advance using 3D model information, covering all necessary measurement angles and positions computationally. This preliminary optimization ensures comprehensive coverage without requiring time-consuming physical adjustments during the actual measurement process.
Solution Approach 2:
The system replaces mechanical physical adjustments and testing with computational optimization based on 3D models. The optimization algorithm calculates ideal sensor configurations digitally, substituting time-consuming mechanical trial-and-error with fast computational analysis.
3Productivity
If optimal configuration is determined using 3D model information and optical sensor information, then measurement efficiency is improved, but computational complexity increases
Solution Approach 1:
The optimization system determines specific configuration parameters (positions, orientations, integration times) for each optical sensor based on local requirements derived from the 3D model. This localized optimization approach improves measurement efficiency without requiring overly complex global optimization algorithms.
Data Source
AI summary
In some implementations, a metrology optimization system may obtain three-dimensional (3D) model information associated with an object. The metrology optimization system may obtain optical sensor information associated with a metrology system that is to measure the object. The metrology optimization system may determine, based on the 3D model information and the optical sensor information, an initial configuration for the metrology system. The metrology optimization system may determine, based on the 3D model information, the optical sensor information, and the initial configuration, an optimal configuration for the metrology system. The metrology optimization system may provide the optimal configuration for the metrology system.