Runtime Process Anomaly Detection and Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing process monitoring systems fail to proactively identify and correct anomalies during process execution, allowing errors to persist and hinder improvements.
Innovation Solution
A system for monitoring process instances that includes a sensor definition to detect anomalies and a correction mechanism to intervene and rectify them in real-time, using a process protocol to store data and generate process intervention instances to address deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If retrospective analysis of previously executed process instances is performed, then information about process weaknesses can be obtained, but proactive intervention in currently running process instances is not possible
Solution Approach 1:
The patent implements preliminary action by continuously monitoring process instances during their execution and detecting anomalies as they occur, rather than waiting for retrospective analysis. The sensor monitors process logs in real-time, identifies deviations from expected patterns, and triggers corrective actions before the process instance completes, thereby eliminating the time loss between detection and intervention.
2Reliability
If real-time monitoring and correction of process instances is implemented, then proactive intervention becomes possible, but system complexity increases
Solution Approach 1:
The patent applies self-service by enabling process instances to self-monitor and self-correct through automated anomaly detection and correction mechanisms. The sensor automatically detects anomalies in process logs and triggers corrective actions without requiring external intervention, thereby improving reliability while minimizing the operational complexity of the monitoring system.
Solution Approach 2:
The implementation incorporates feedback loops where the sensor continuously monitors process execution, compares actual behavior against expected patterns, and automatically triggers corrective actions when deviations are detected. This closed-loop feedback mechanism ensures reliable process control while maintaining manageable system complexity through automation.
3Reliability
If continuous monitoring of process logs is performed, then process anomalies can be detected during execution, but data processing requirements increase
Solution Approach 1:
The patent implements partial monitoring by focusing computational resources on detecting specific anomaly patterns rather than analyzing all process data in equal detail. The sensor is configured to monitor for predefined anomaly types and triggers corrective actions only when specific deviation patterns are detected, thereby maintaining reliable anomaly detection while reducing overall computational resource consumption.
Data Source
Figure 1~3
Figure 4
Figure 5~6
AI summary
The invention relates to a method for monitoring process instances that are being executed and for eliminating process anomalies in said process instances, wherein (a) in a monitoring step a sensor, using a sensor definition, monitors a process log with respect to the process anomaly described in the sensor definition and detects process instances or processes comprising a plurality of process instances, that have the process anomaly described in the sensor definition, and (b) in a correction step, for a process instance detected in the monitoring step, the process anomaly is eliminated at the runtime of said process instance.