Dynamic Threshold Baseline Detection for Process Monitoring
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Solution Overview
Problem
Existing methods lack effective means to dynamically determine and monitor threshold baselines for process measurements, leading to inadequate detection of state changes in processes, such as from normal to abnormal states, which can result in delayed alerts and inefficient process control.
Innovation Solution
A method and apparatus that receive and analyze data sets of process values over time, perform statistical calculations on subsets of these values to determine threshold baselines, and alert users when these baselines are crossed, allowing for dynamic recalculations based on changing mean and standard deviation values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods are used to monitor process measurements, then the system structure remains simple, but the detection accuracy of state changes is insufficient
Solution Approach 1:
The patent implements dynamic threshold baselines that automatically adjust based on statistical analysis of process data. The system calculates mean and standard deviation from received measurements and updates threshold baselines accordingly, allowing the monitoring system to adapt to changing process conditions without requiring manual reconfiguration or complex fixed-threshold setups
Solution Approach 2:
The system performs self-service by automatically calculating statistical parameters (mean, standard deviation) from the process data it receives and using these to determine dynamic threshold baselines. This eliminates the need for external manual threshold configuration while improving detection accuracy, resolving the contradiction between simplicity and precision
2Adaptability or versatility
If dynamic recalculations are performed on statistical parameters, then the adaptability to changing data patterns improves, but the calculation time increases
Solution Approach 1:
The system performs preliminary calculations by maintaining running statistics (mean and standard deviation) as data is received, rather than recalculating from scratch. This allows the system to quickly adapt to changing patterns while minimizing computation time by building on previously calculated values
Solution Approach 2:
The patent implements continuous statistical calculation and threshold updating as process data flows in. Rather than periodic batch processing, the system continuously updates mean, standard deviation, and threshold baselines, ensuring immediate adaptability to pattern changes without significant time loss through uninterrupted useful action
3Reliability
If threshold baselines are set statically, then the system complexity is reduced, but the reliability of process control deteriorates
Solution Approach 1:
The system implements feedback by continuously monitoring process measurements, calculating statistical parameters, and using these to dynamically adjust threshold baselines. This closed-loop approach improves reliability by ensuring thresholds reflect actual process behavior while managing complexity through automated feedback-driven adjustment rather than manual intervention
Data Source
AI summary
A method and apparatus can be configured to receive a data set of values relating to a process. The data set of values correspond to values measured while the process is performed over a duration of time. The method also includes performing first statistical calculations on a first data subset of values. The values of the first data subset is a subset of the entire received data set of values. The values of the first data subset of values correspond to values that are of a first timeframe of the duration of time. The method also includes displaying first calculated results of the first statistical calculations. The method also includes determining whether performing the process has crossed a first threshold baseline. The first threshold baseline is based on the first statistical calculations. The method also includes transmitting a first alert to a user if the process is determined to have crossed the first threshold baseline.