Process Anomaly Monitoring With Real-Time Runtime Correction
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Solution Overview
Problem
Existing methods for analyzing processes cannot detect or eliminate errors or anomalies in real-time during the execution of process instances, limiting proactive intervention and requiring post-execution analysis for improvements.
Innovation Solution
A method that monitors process instances using sensor definitions to detect anomalies and execute corrective actions in real-time, involving a monitoring step to identify anomalies and a correction step to apply specific generic actions to address them, allowing for active intervention during process execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If process instances are monitored in real-time during execution, then errors or anomalies can be detected and eliminated immediately, but the complexity of the system increases due to the need for continuous monitoring and intervention mechanisms
Solution Approach 1:
The patent introduces a sensor as an intermediary component that monitors process instances and detects anomalies. The sensor acts as a mediator between the process execution and the analysis system, enabling real-time detection without directly complicating the core process execution mechanisms.
Solution Approach 2:
The patent implements a feedback mechanism where process data is continuously monitored during execution, analyzed in real-time, and used to trigger corrective actions. This closed-loop feedback system enables immediate detection and elimination of errors while maintaining process reliability.
2Productivity
If continuous monitoring and real-time intervention are implemented, then process efficiency improves through immediate corrective actions, but the loss of time increases due to the overhead of monitoring and intervention mechanisms
Solution Approach 1:
The patent defines sensor definitions and anomaly detection rules in advance before process execution begins. This preliminary configuration allows the monitoring system to operate efficiently during execution without requiring complex real-time decision-making, reducing monitoring overhead time.
Solution Approach 2:
The system automatically detects anomalies and triggers corrective actions without requiring continuous human intervention. The automated self-service mechanism reduces the time overhead associated with manual monitoring while maintaining high process efficiency.
3Measurement precision
If detailed process data are collected and stored for real-time analysis, then measurement precision of process parameters improves, but the quantity of data to be processed increases, leading to higher computational load
Solution Approach 1:
The patent extracts only the specific process parameters that are relevant to anomaly detection based on pre-defined sensor definitions. Rather than processing all possible process data, the system selectively extracts and monitors only the critical parameters, reducing data volume while maintaining measurement precision.
Solution Approach 2:
The patent applies different monitoring precision and data collection frequency to different process parameters based on their importance. Critical parameters are monitored with high precision, while less critical parameters use lower monitoring intensity, optimizing the balance between measurement precision and data quantity.
Data Source
AI summary
A method for monitoring process instances that are being executed and for eliminating process anomalies in the process instances is provided. In a monitoring step, a sensor, using a sensor definition, monitors a process log with respect to a process anomaly described in the sensor definition, and detects process instances or processes that have the process anomaly described in the sensor definition. In a correction step, for a process instance detected in the monitoring step, the process anomaly is eliminated at the runtime of the process instance.