Industrial Plant State-to-Action Sequencing for Abnormal Conditions
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Solution Overview
Problem
Existing industrial plant monitoring systems struggle to automatically remedy abnormal operating conditions by providing operators with the correct sequence of actions, as they often require human intervention and may worsen safety-critical situations if incorrect actions are taken.
Innovation Solution
A computer-implemented method using trained state encoder and action decoder networks to encode plant state variables into a low-dimensional representation, which is then mapped to a sequence of actions, aiding operators in rectifying abnormal situations by highlighting necessary actions or automating them when possible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated remediation systems are implemented to remedy abnormal conditions, then productivity is improved, but reliability deteriorates due to potential incorrect actions worsening safety-critical situations
Solution Approach 1:
The patent introduces an expert system as an intermediary between the automated detection of abnormal conditions and the execution of remediation actions. This expert system validates and guides the automated actions, ensuring they are appropriate for safety-critical situations while maintaining automation benefits.
Solution Approach 2:
The system implements feedback mechanisms where the results of remediation actions are monitored and evaluated. This allows the system to learn from outcomes and adjust future actions, improving reliability while maintaining productivity through automated decision-making.
2Reliability
If complex sequences of actions are provided to operators, then reliability is improved by ensuring correct remediation, but ease of operation deteriorates due to increased complexity
Solution Approach 1:
The patent segments complex remediation procedures into discrete, manageable action steps with clear prerequisites and outcomes. Each action is broken down into individual components that can be executed and verified independently, reducing operator cognitive load while maintaining accuracy.
Solution Approach 2:
The system performs preliminary analysis and validation of action sequences before presenting them to operators. By pre-processing the remediation logic and validating action appropriateness in advance, the system reduces the complexity operators must handle during critical situations.
3Measurement precision
If comprehensive monitoring of state variables is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts and focuses monitoring resources on the most critical state variables and abnormal conditions. By identifying and prioritizing key parameters that most significantly impact safety and operations, the system achieves high measurement precision for critical variables without the complexity of comprehensive monitoring of all possible parameters.
Data Source
AI summary
A method for determining an appropriate sequence of actions to take during operation of an industrial plant includes obtaining values of a plurality of state variables that characterize an operational state of the plant (or a part thereof); encoding by at least one trained state encoder network the plurality of state variables into a representation of the operating state of the plant; mapping by a trained state-to-action network the representation of the operating state to a representation of a sequence of actions to take in response to the operating state; and decoding by a trained action decoder network the representation of the sequence of actions to the sought sequence of actions to take.