Real-Time Batch Data Alignment with Statistical Models
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Solution Overview
Problem
Batch process control systems face challenges in accurately determining the operational state of an ongoing batch process in real-time, as existing methods require completion of the batch run to align data with a statistical model, leading to delayed identification of quality issues and inefficient resource utilization.
Innovation Solution
A computationally inexpensive data alignment technique is implemented to align on-going batch process data with a batch model, enabling real-time analysis using partial least squares and principle component analysis, allowing for timely quality assessments and potential adjustments during the batch run.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional batch data alignment methods are used, then data can be aligned with the statistical model, but the batch process must be completed first, causing delayed quality assessment and loss of real-time monitoring capability
Solution Approach 1:
The patent applies preliminary action by pre-aligning batch data to the statistical model before the batch process completes. The system continuously aligns incoming batch data points to the pre-established statistical model, enabling real-time quality assessment without waiting for batch completion. This allows operators to detect quality deviations early and take corrective actions during the batch process.
2Productivity
If batch processes continue running without real-time quality monitoring, then productivity is maintained, but resources are wasted on producing out-of-spec products
Solution Approach 1:
The patent implements feedback by continuously comparing real-time batch process data against the statistical model and providing immediate feedback on quality status. When quality parameters deviate from specifications, the system generates alerts or自动控制 responses to correct the deviation, preventing the production of out-of-spec products while maintaining continuous batch operation.
3Measurement precision
If complex alignment algorithms are used to improve alignment accuracy, then measurement precision improves, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts and uses only the essential features needed for batch data alignment, avoiding unnecessary computational complexity. The system identifies key process variables and parameters that most significantly impact quality, focusing the alignment algorithm on these critical factors rather than processing all available data, thereby achieving accurate alignment with reduced computational burden.
Data Source
AI summary
A batch modeling and analysis system uses a simple and computationally inexpensive technique to align data collected from an on-going, currently running or on-line batch process with a batch model formed for the batch process so as to enable the reliable determination of the current operational state of the on-line batch process with respect to the batch model. This data alignment technique enables further statistical processing techniques, such as projection to latent sources (PLS) and principle component analysis (PCA) techniques, to be applied to the on-line batch data to perform analyses on the quality of the currently running batch. These analyses, in turn, provide useful information to a user, such as a batch operator, that enables the user to determine the quality of the batch at the present time, based on the batch model, and the likelihood that the desired batch output quality metrics will be reached at the end of the batch run.