Plant Alarm Message Enrichment Using Topology-Based Rule Inference
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Solution Overview
Problem
Existing systems for generating alarm messages in industrial plants produce generic and default severity messages that require manual adaptation by engineers, leading to an exhausting and error-prone process.
Innovation Solution
A method for generating enriched alarm messages by applying information model rules to the topology of a plant, inferring logical consequences, and combining these to create meaningful and severity-rated alarm messages, utilizing a combination of logic reasoners, semantic reasoners, and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generic alarm messages and default severity values are generated for newly configured plants, then the alarm message generation process is automated and quick, but the alarm messages provide little significant information substance and require manual adaptation
Solution Approach 1:
The system performs preliminary actions by pre-defining information model rules that describe interrelations between plant components and alarm messages. These rules are applied in advance to automatically generate enriched alarm messages with meaningful information substance, eliminating the need for manual adaptation while maintaining high productivity
Solution Approach 2:
An information model serves as an intermediary between the plant configuration and alarm message generation. This model contains rules that automatically enrich generic alarm messages with component-specific information and appropriate severity values, resolving the contradiction between automation speed and information quality
2Reliability
If manual adaptation of generic alarm messages is performed to provide meaningful information, then the alarm messages become informative and useful, but the process becomes exhausting and error-prone
Solution Approach 1:
The system implements self-service by automatically generating enriched alarm messages using pre-defined information model rules. The rules engine autonomously applies component interrelation knowledge to generate meaningful alarm messages with appropriate severity values, eliminating manual adaptation work and associated errors while maintaining high message quality
Solution Approach 2:
The manual mechanical process of adapting alarm messages is replaced by an automated information processing system. The system uses logical inference and rule-based processing to automatically generate enriched alarm messages, substituting human effort with automated intelligence that is both reliable and easy to operate
3Reliability
If manual adaptation of alarm messages is performed, then meaningful alarm messages can be created, but the process takes a lot of effort and time
Solution Approach 1:
The system performs preliminary action by pre-configuring information model rules that capture domain knowledge about plant component interrelations. When alarm messages are generated, these pre-prepared rules are automatically applied through logical inference, producing meaningful enriched messages instantaneously without requiring time-consuming manual adaptation
Solution Approach 2:
The system transforms alarm messages from generic to enriched by changing key parameters automatically. Logical inference engines apply information model rules to modify message content, add component-specific details, and assign appropriate severity values, achieving meaningful messages without time investment
Data Source
AI summary
A method for generating an enriched alarm message associated to an initial alarm message of a concerned component of a plant includes providing a plurality of information model rules related to alarm messages for respective interrelations of components of the plant; applying the plurality of information model rules related to the alarm messages to respective components of a topology of the plant, for generating a system of information model rules related to the respective alarm messages of the plant; inferring logical consequences for the system of information model rules, which are related to the initial alarm message originated by the concerned component; and generating the enriched alarm message by combining the information model rules related to the initial alarm message of the concerned component, based on the inferred logical consequences.