Adaptive Component Measurement for Efficient Quality Sampling
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Solution Overview
Problem
Existing quality check processes for components are inefficient, requiring significant time and resources, which can reduce production yield and increase costs.
Innovation Solution
A system and process for measuring components that dynamically adjusts selection parameters, such as sample frequency, based on production parameters and measurement data analysis, to ensure reliable quality checks with reduced time and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If regular quality monitoring is performed on all components, then quality assurance is ensured, but production yield is reduced due to time consumption
Solution Approach 1:
The inspection frequency is made dynamic rather than static. The system automatically adjusts the inspection frequency based on measured quality data, production parameters, and risk assessments. When quality is stable, inspection frequency decreases; when quality varies or risk increases, frequency increases. This dynamic adaptation resolves the contradiction by ensuring quality assurance only when necessary, thereby maintaining production yield.
Solution Approach 2:
The system changes the parameter of inspection frequency based on multiple factors including quality data trends, production parameter changes, and risk assessments. By adjusting this parameter dynamically, the system ensures quality assurance is maintained while minimizing the time spent on inspections, thus resolving the contradiction between reliability and productivity.
2Reliability
If inspection frequency is increased to ensure reliable quality testing, then quality reliability is improved, but time required for quality testing increases
Solution Approach 1:
The inspection frequency is dynamically adjusted based on quality data analysis and risk assessment. When quality is stable and risk is low, the system reduces inspection frequency to minimize time loss. When quality varies or risk increases, the system increases frequency to maintain reliability. This dynamic approach resolves the contradiction between reliability and time consumption.
Solution Approach 2:
The system performs preliminary risk assessment and quality data analysis before determining inspection frequency. By anticipating quality issues through trend analysis and risk evaluation, the system can proactively adjust inspection frequency, ensuring reliable quality testing only when necessary, thereby reducing overall time consumption while maintaining reliability.
3Adaptability or versatility
If manual definition of test criteria is used, then flexibility in quality control is maintained, but time and expertise requirements increase
Solution Approach 1:
The system automatically determines test criteria and inspection parameters based on quality data analysis, production parameters, and risk assessment, without requiring manual definition. The system serves itself by autonomously adjusting inspection strategies, which maintains flexibility while eliminating the time and expertise burden of manual criterion definition. This resolves the contradiction between adaptability and time consumption.
Solution Approach 2:
The system uses feedback from quality data and production parameters to automatically adjust test criteria and inspection frequency. This closed-loop approach maintains flexibility by adapting to changing conditions while eliminating manual intervention, thereby resolving the contradiction between adaptability and time/expertise requirements.
Data Source
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AI summary
The invention relates to a method and system for measuring components (B) which are produced by a production device (1), comprising: a) selecting (S1) components (B) to be measured from a plurality of components (B), wherein the selection is made according to at least one selection parameter (p), b) generating (S2a) component-specific measurement data (MD) by measuring the selected components (B) using a coordinate measurement device (2) and evaluating (S2b) the measurement data (MD) and/or c) determining (S3) at least one production parameter (m), d) adapting (S4) the at least one selection parameter (p) according to a result (r) of the evaluation and/or according to the production parameter (m) or a change to the production parameter (m), and to a program.