Plant Operator Assistance for Abnormal Situation Recognition
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Solution Overview
Problem
Complex industrial plants face challenges in recognizing abnormal situations and reacting to them effectively, particularly due to the complexity of operations and the need to distinguish relevant from irrelevant information among diverse data sources.
Innovation Solution
An assistance system comprising a plant topology repository, monitoring subsystem, aggregation subsystem, identification subsystem, and evaluation subsystem, which analyzes signals from industrial plant components, identifies abnormal situations, and outputs predefined actions, utilizing technologies like ANN for pattern matching and data orchestration to minimize false alarms and focus human operators on critical issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If comprehensive monitoring of all plant components is implemented, then detection capability is improved, but information overload and cognitive load increase
Solution Approach 1:
The system segments the complex plant monitoring task into distinct functional modules: a monitoring subsystem that collects signals, an aggregation subsystem that organizes data, an identification subsystem that detects patterns, and an evaluation subsystem that assesses abnormalities. This segmentation allows comprehensive monitoring while managing information flow systematically to prevent overload.
Solution Approach 2:
The assistance system acts as an intermediary between the complex plant components and human operators. It processes, filters, and presents information in a manageable format, reducing the cognitive load on operators while maintaining comprehensive detection capability across all plant components.
2Ease of operation
If manual analysis of plant operations is performed, then flexibility is maintained, but response time and productivity decrease
Solution Approach 1:
The system enables self-service operation by automatically monitoring plant components, identifying abnormal situations, and evaluating potential actions without requiring continuous manual intervention. This automation maintains operational flexibility while significantly improving response time and productivity.
Solution Approach 2:
The system performs preliminary analysis and evaluation of plant operations automatically, preparing information and potential actions in advance. This allows human operators to make decisions more quickly when needed, improving overall response time while maintaining the flexibility of human judgment.
3Measurement precision
If diverse data sources are integrated, then measurement completeness is improved, but system complexity increases
Solution Approach 1:
The assistance system is designed with universal functionality to handle diverse data sources through standardized interfaces. The monitoring subsystem can collect signals from various plant components, and the aggregation subsystem organizes this diverse information uniformly, achieving measurement completeness without proportionally increasing system complexity.
Data Source
AI summary
An assistance system comprises a plant topology repository comprising a representation of the components of the plant and relations between the components; a monitoring subsystem configured for monitoring signals from the components and for monitoring a related event, as a key for the monitored signals; an aggregation subsystem configured for storing a plurality of the monitored signals and the related events, wherein at least one of the events is the abnormal situation; an identification subsystem configured for comparing currently monitored signals to stored monitored signals and the related event; and an evaluation subsystem configured for outputting a predefined action, if the currently monitored signals match to the event that is the abnormal situation.