Rule-Based Control System Health Assessment
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Solution Overview
Problem
Complex control systems in industrial processes face challenges in predicting and maintaining reliability, leading to unexpected stoppages and maintenance issues due to outdated hardware and software, which are typically addressed through corrective maintenance rather than preventative measures.
Innovation Solution
A system comprising a data collection module, configuration management, a rule engine, and a rule editor that analyzes data to provide real-time health assessments and recommendations for upgrades, replacements, and configuration management, enabling predictive maintenance and minimizing process stoppages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complex control systems with numerous interrelated components are used to control industrial processes, then the control capability and functionality are improved, but the difficulty of recognizing or predicting system reliability increases and becomes time-consuming
Solution Approach 1:
The patent segments the complex control system into individual components and subsystems, creating separate health assessment rules for each component. This allows the system to evaluate reliability by analyzing discrete elements rather than attempting to assess the entire complex system as a whole, thereby reducing the cognitive and computational burden while maintaining comprehensive coverage.
Solution Approach 2:
The patent introduces an intermediary health assessment system that acts as a mediator between the complex control system and reliability prediction. This intermediary layer collects data from various components, applies standardized assessment rules, and synthesizes reliability information, thereby simplifying the process of predicting system reliability without reducing the control capability of the underlying system.
2Ease of manufacture
If corrective maintenance is used to address outdated hardware and software issues, then the approach is simple to implement, but unexpected stoppages and maintenance issues occur
Solution Approach 1:
The patent implements preliminary action by continuously monitoring system components and predicting potential failures before they occur. Health assessment rules evaluate component conditions and generate early warnings, allowing maintenance to be scheduled proactively rather than reactively. This prevents unexpected stoppages while maintaining the simplicity of maintenance operations through structured assessment protocols.
Solution Approach 2:
The patent establishes a feedback mechanism where health assessment results from monitoring system components are continuously analyzed and used to update maintenance decisions. The system collects data on component performance, applies assessment rules to evaluate reliability, and feeds this information back to maintenance planners, enabling data-driven decisions that improve reliability while maintaining operational simplicity.
3Reliability
If continuous health monitoring and predictive maintenance are implemented, then system reliability and operational duration are improved, but the complexity of the monitoring system increases
Solution Approach 1:
The monitoring system is segmented into modular health assessment rules that can be independently developed, configured, and maintained. Each rule focuses on specific components or failure modes, allowing the monitoring system to scale with the control system without becoming overwhelmingly complex. This modular approach enables continuous health monitoring while maintaining system manageability.
Solution Approach 2:
The patent creates a universal health assessment framework that can be applied across multiple components and subsystems using standardized rules. This multi-functional approach allows the same monitoring infrastructure to assess diverse components (hardware, software, networks) through unified assessment protocols, reducing the need for separate monitoring systems for each component and thereby limiting the increase in overall system complexity.
Data Source
AI summary
In one embodiment, a system includes system includes a data collection system configured to collect a data from a control system. The system further includes a configuration management system configured to manage a hardware configuration and a software configuration for the control system based on the data. The system additionally includes a rule engine configured to use the data as input and to output a health assessment by using a rule database configured to store at least one rule, and a report generator configured to provide a health assessment for the control system. The system also includes a rule editor configured to create the at least one rule, update the at least one rule, delete the at least one rule, or a combination thereof.