Sensor Drift Detection for Real-Time Composite Prepreg Quality
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Solution Overview
Problem
Current methods for testing unconsolidated composite components, such as prepreg rolls, are inefficient as they require testing multiple portions to identify out-of-tolerance sections, leading to time-consuming quality assessments and potential waste, and cannot determine the cause of quality issues in real-time during manufacturing.
Innovation Solution
A system comprising a computer system and sensor data analyzer that receives real-time sensor data from a composite material manufacturing system to detect inconsistencies and predict properties of unconsolidated composite materials, allowing for immediate action to adjust manufacturing parameters and reduce waste by identifying in-tolerance and out-of-tolerance portions during production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple portions of prepreg rolls are tested to identify out-of-tolerance sections, then quality assessment accuracy is improved, but testing time and manufacturing efficiency deteriorate
Solution Approach 1:
The system performs preliminary quality assessment during the manufacturing process itself, rather than after completion. Sensors monitor parameters such as resin temperature, fiber orientation, and consolidation pressure in real-time, enabling early detection of out-of-tolerance sections before the entire prepreg roll is finished, thus avoiding wasted testing time and maintaining high manufacturing efficiency
Solution Approach 2:
The system implements continuous feedback loops where sensor data from the manufacturing process is immediately analyzed and used to adjust process parameters. This real-time feedback enables the system to maintain quality without requiring multiple post-manufacturing tests, resolving the contradiction between assessment accuracy and manufacturing efficiency
2Measurement precision
If multiple portions of prepreg rolls are tested to identify out-of-tolerance sections, then quality assessment accuracy is improved, but time consumption increases
Solution Approach 1:
Quality assessment is performed preliminarily during manufacturing through continuous sensor monitoring of critical parameters. This eliminates the need for multiple post-manufacturing tests, achieving both high accuracy and rapid assessment by detecting out-of-tolerance sections as they form during the manufacturing process itself
Solution Approach 2:
The system replaces traditional mechanical sampling and laboratory testing methods with automated sensor-based monitoring and data analysis. This substitution enables continuous, real-time quality assessment that is both highly accurate and time-efficient, eliminating the time-consuming nature of multiple physical tests
3Measurement precision
If traditional testing methods are used to determine quality issues, then comprehensive quality assessment is achieved, but the ability to determine cause in real-time deteriorates
Solution Approach 1:
The system implements real-time feedback mechanisms where sensors continuously monitor manufacturing parameters (resin temperature, fiber orientation, consolidation pressure) and immediately analyze deviations. This enables both comprehensive quality assessment and real-time determination of quality issue causes, as the system tracks the entire manufacturing history and can correlate defects with specific process conditions
Solution Approach 2:
The system introduces data analytics and process monitoring systems as intermediaries between the manufacturing process and quality assessment. These intermediaries capture and analyze process data in real-time, enabling the determination of quality issue causes while maintaining comprehensive quality evaluation, thus resolving the information loss problem
4Measurement precision
If out-of-tolerance sections are identified after manufacturing, then quality sorting is achieved, but material waste increases
Solution Approach 1:
The system performs preliminary identification of out-of-tolerance sections during manufacturing through continuous sensor monitoring. By detecting quality issues as they occur rather than after completion, the system enables selective removal or rework of only the affected portions, preventing waste of the entire prepreg roll and achieving both accurate quality sorting and reduced material waste
Data Source
AI summary
An inconsistency detection system comprises a computer system and a sensor data analyzer. The sensor data analyzer is configured to receive sensor data from a sensor system monitoring a composite material manufacturing system manufacturing an unconsolidated composite material in real time. The sensor data analyzer is configured to determine whether an inconsistency that is out of tolerance is present in the sensor data received in real time using an inconsistency detector. The determination of whether the inconsistency that is out of tolerance is present is performed in real-time during manufacturing of the unconsolidated composite material. The sensor data analyzer is configured to perform a number of actions in real time in response to detecting the inconsistency that is out of tolerance in the sensor data.