Calibration Model Monitoring for Process Drift and Quality Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing PAT systems struggle to effectively monitor and adjust manufacturing processes in real-time to ensure consistent product quality, particularly in the face of process drift and variability, leading to inefficiencies and potential quality issues.
Innovation Solution
A method and system that utilizes a calibration model to map process parameters to product quality attributes, enabling real-time monitoring and adjustment of processes to maintain desired quality, with mechanisms for continuous improvement through unclustered inlier detection and adaptive calibration models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional PAT systems monitor process parameters using fixed thresholds, then simple detection is achieved, but they fail to detect process drift and variability leading to quality issues
Solution Approach 1:
The patent transforms fixed threshold monitoring into dynamic range-based monitoring by implementing calibration models that define expected ranges for process parameters. The system continuously adapts monitoring criteria based on calibrated relationships between process parameters and product quality attributes, enabling detection of process drift while maintaining measurement precision.
Solution Approach 2:
The system establishes closed-loop feedback by mapping process parameters to product quality attributes through calibration models. When parameters deviate from expected ranges, the system provides feedback signals to adjust process conditions, ensuring product quality consistency while maintaining detection accuracy.
2Reliability
If real-time monitoring of all process parameters is implemented, then product quality is improved, but system complexity and cost increase
Solution Approach 1:
The patent creates a universal calibration model framework that can be applied across different manufacturing processes and product types. The system uses a standardized approach to mapping process parameters to quality attributes, reducing the need for process-specific complex monitoring solutions while maintaining product quality.
Solution Approach 2:
The system performs preliminary calibration during the setup phase, establishing the relationship between process parameters and product quality attributes before production begins. This pre-calibration work reduces the complexity of real-time monitoring by pre-defining expected ranges and detection criteria, eliminating the need for complex real-time analysis algorithms.
3Ease of manufacture
If fixed calibration models are used for process monitoring, then initial setup is simple, but they cannot adapt to process drift and variability
Solution Approach 1:
The patent transforms static calibration models into dynamic adaptive models that continuously update expected parameter ranges based on observed process variability. The system maintains simplicity by using incremental updates to calibration parameters rather than complete recalibration, allowing adaptation to process drift while keeping the implementation approach straightforward.
Solution Approach 2:
The calibration model system performs self-updates by automatically detecting process drift and adjusting expected parameter ranges without requiring external intervention. The system uses accumulated process data to refine calibration parameters autonomously, maintaining ease of implementation while achieving continuous adaptation to process variability.
Data Source
AI summary
Aspects and embodiments relate to a method of monitoring, a monitoring unit (300) configured to perform the monitoring method and a computer program product configured to perform the monitoring method. The method of monitoring is a method of monitoring at least one device configured to perform one or more process (110, 120, 130, 140) to produce a product (200). At least one process is associated with at least one process parameter. The product producible by the one or more process has at least one product quality attribute which is modifiable in dependence upon the at least one process parameter. The method of monitoring comprises: receiving an indication of the at least one process parameter; checking the indication against a calibration model to determine whether the at least one process parameter results in a product quality attribute within a preselected range (650). The calibration model comprises: a mapping between the at least one process parameter and the at least one product quality attribute; the mapping defining: a first range of the at least one process parameter indicative that a product will have a product quality attribute within the preselected range (650); and a second range (1050, 1060) within the first range, the second range of the at least one process parameter being indicative that the at least one process parameter is within an expected range. The method of monitoring further comprising: initiating one or more action