Automation State Message Analysis for Root Cause Timing
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Solution Overview
Problem
Manual detection of time parameters for root cause analysis in automation installations is laborious and cannot be performed during normal operation, and deriving these parameters from digital specifications leads to systematic errors when the installation deviates from the planned configuration.
Innovation Solution
A method and device for computer-aided processing of state messages that automatically extract time parameters from data collected during normal operation, using pattern descriptions to identify causative states and calculate propagation times across components, allowing for statistical parameter determination without manual intervention or reliance on digital specifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of time parameters is performed, then measurement precision is improved, but productivity deteriorates due to laborious work and inability to operate during normal production
Solution Approach 1:
The patent replaces manual mechanical time measurement with an automated computer-based system that extracts time parameters from digital state messages. The control device automatically detects state changes, determines time points, and calculates propagation times without human intervention, thereby maintaining measurement precision while dramatically improving productivity and enabling operation during normal production
Solution Approach 2:
The system uses the automation installation's own operational data (state messages) to automatically determine time parameters. The control device leverages existing digital communications infrastructure and state message streams that are already generated during normal operation, eliminating the need for separate manual measurement processes while maintaining accurate time parameter determination
2Productivity
If time parameters are derived from digital specification, then productivity is improved, but measurement precision deteriorates due to systematic errors when installation deviates from planned configuration
Solution Approach 1:
The system continuously monitors actual state messages from the running installation and uses this feedback to determine time parameters. By comparing actual operational states with the digital specification, the system adapts to deviations and corrections in the actual installation configuration, thereby maintaining measurement precision while preserving the productivity benefits of automated parameter determination
Solution Approach 2:
The patent transitions from using fixed parameters in digital specifications to dynamically determined time parameters extracted from actual operational state messages. This parameter change allows the system to adapt to real-world deviations from the planned installation configuration, eliminating systematic errors while maintaining automated high-speed parameter determination
3Device complexity
If root cause analysis is performed without automated time parameter extraction, then device complexity is reduced, but loss of time increases due to inability to perform analysis during normal operation
Solution Approach 1:
The control device performs multiple functions: it manages the automation installation control, processes state messages, extracts time parameters, and performs root cause analysis. By integrating these functions into a single universal system, the patent avoids significant increases in device complexity while enabling continuous time parameter determination and root cause analysis during normal operation, thereby eliminating time loss
Data Source
AI summary
A method for computer-aided processing of state messages in an automation installation, wherein state messages are generated by components and detected with their generation points in time, where causative states present at the generation point of the state message or beforehand in other components are determined for a multiplicity of state messages of a respective component and the current state in the generated state message, where the propagation time between occurrence of the respective causative state and the generation point of the state message is calculated for each causative state, where groups are formed from the causative states, where in a respective group all causative states have at least the common feature that they were determined for the same current state in the respective component, and where at least one statistical parameter is determined from the propagation times which belong to the causative states of the same group and stored.