Automated Optical Quality Testing Using Pose Tracking
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Solution Overview
Problem
Current quality control methods in production environments are prone to human error, lack adaptability, and are not reproducible, as they rely on manual checks and require extensive training and retraining, especially in the ramp-up phase, and existing automated systems are inflexible and require extensive retraining for each product variant or change.
Innovation Solution
A method using a computer-assisted data model to define test geometry and reference geometry, with a processing apparatus that guides the camera to a specific test pose, allowing for automated and reproducible quality checks by tracking the pose of the test geometry relative to the reference geometry and outputting a quality indicator, enabling reliable and adaptable quality assurance across different product variants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual quality control methods are used with trained workers, then flexibility in adapting to evolving requirements is improved, but human fatigue leads to increased mistakes and reduced reliability
Solution Approach 1:
The patent replaces manual visual inspection by workers with an automated optical measurement system using cameras and image processing algorithms. This substitution eliminates human fatigue while maintaining adaptability through software-based evaluation criteria that can be adjusted for different product variants without retraining personnel.
2Reliability
If physical templates or measuring gauges are used to support quality control, then measurement reliability is improved, but adaptability deteriorates because each product variant requires a dedicated measuring gauge with complex production processes
Solution Approach 1:
The patent implements a universal digital measurement system that can evaluate multiple product variants using the same hardware infrastructure. The system uses configurable evaluation criteria and reference image databases that can be updated software-based to accommodate different product configurations, eliminating the need for dedicated physical measuring gauges for each variant.
Solution Approach 2:
The patent creates digital copies of product specifications and reference images in a computer-readable database. These digital representations replace physical templates and measuring gauges, allowing the system to virtually replicate measurement criteria for different product variants without requiring physical reproduction of templates.
3Productivity
If automated computer vision-based test methods are used, then productivity is improved, but flexibility deteriorates in the ramp-up phase because changes to templates require complex production processes for measuring gauges
Solution Approach 1:
The patent implements a dynamic measurement system where evaluation criteria and reference data can be updated in real-time through software configuration. This allows the system to adapt to new product variants and design changes during the ramp-up phase without requiring time-consuming retooling or template production, maintaining both high productivity and flexibility.
4Measurement precision
If reference images are collected and labelled through user interaction to train classification networks, then measurement precision is improved, but the process becomes very demanding and inflexible as new image data must be used to train for each product variant
Solution Approach 1:
The patent performs preliminary creation of comprehensive reference image databases during the product design phase, capturing various states and configurations of product components. These pre-collected reference images serve as training data for classification algorithms, eliminating the need for extensive user interaction and retraining when new product variants are introduced, as the system can evaluate new variants against the established reference framework.
Data Source
AI summary
The invention relates to a method for testing quality of an object in a real environment using a camera, an optical display device, and a processing apparatus, the method including the following steps: defining a test geometry and a reference geometry in a computer-assisted data mode; defining a test pose, in which the camera should be placed by the user as target positioning for a quality test to be carried out of the object to be tested; and visualizing the test pose on the optical display device. In a second phase, at least one image of the real environment is captured by the camera, the pose of which camera is in a range that includes the test pose, and the test geometry and the reference geometry in the image are tracked. Furthermore, a pose of the tracked test geometry in relation to the reference geometry and at least one parameter are determined on the basis of how the pose of the tracked test geometry is in relation to a target pose of the test geometry defined within the data model. A quality indicator is also determined on the basis of the at least one parameter and is output to the user via a human-machine interface.