Interlock Rule Visualization on Topology Models for Verification
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Solution Overview
Problem
Industrial process interlock specifications, often automated, lack trustworthiness among safety engineers and service personnel, leading to laborious and error-prone manual specifications, and result in costly inconsistencies and potential equipment or human safety risks due to complex P&IDs and insufficient user feedback.
Innovation Solution
A method for visualizing industrial process rules using a topology model, where sensors and actuators are attributed with cause-effect relations, allowing for intuitive marking and approval/rejection of interlock specifications, reducing errors and inconsistencies through a computer-implemented visual interface, and utilizing machine learning to refine rule generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated interlock specification algorithms are used, then productivity is improved, but reliability deteriorates due to lack of trustworthiness among safety engineers
Solution Approach 1:
The system provides visual feedback by overlaying interlock rules on the topology model, allowing safety engineers to verify that automated algorithms have correctly identified sensors, actuators, and their relationships. This visual confirmation restores trust while maintaining automation benefits.
Solution Approach 2:
The topology model serves as an intermediary representation that bridges automated algorithm output and human verification. By visualizing interlock rules on the topology model, the system creates a trusted intermediate step between automation and final specification approval.
2Reliability
If manual interlock specification is performed, then reliability is improved through human verification, but productivity deteriorates due to laborious and error-prone processes
Solution Approach 1:
The automated algorithm performs preliminary identification of sensors, actuators, and potential interlock relationships before human verification. This preliminary action reduces the manual workload to primarily verification tasks rather than complete manual specification, improving productivity while maintaining reliability.
Solution Approach 2:
The visual feedback mechanism allows safety engineers to efficiently verify automated results by reviewing highlighted elements on the topology model, rather than manually specifying each interlock from scratch. This feedback loop maintains accuracy while significantly reducing time investment.
3Measurement precision
If complex P&IDs are used for interlock specification, then measurement precision is improved through detailed process representation, but device complexity deteriorates making verification difficult
Solution Approach 1:
The system segments the complex P&ID information into a simplified topology model that retains essential process relationships while removing unnecessary visual complexity. This segmentation maintains measurement precision for interlock specification while reducing verification complexity through cleaner visual representation.
Solution Approach 2:
The system extracts only the essential elements (sensors, actuators, and their relationships) needed for interlock specification from the complex P&ID, discarding extraneous visual details. This extraction maintains the precision needed for safety engineering while eliminating the visual complexity that hinders verification.
4Productivity
If insufficient user feedback is provided in automated systems, then productivity is improved through automation, but reliability deteriorates due to inability to verify correctness
Solution Approach 1:
The system provides comprehensive visual feedback by highlighting sensors, actuators, and interlock relationships on the topology model, enabling users to verify automated results. This feedback mechanism maintains automation efficiency while restoring verifiability and user confidence.
Solution Approach 2:
The system uses color coding and visual highlighting to provide intuitive feedback about automated interlock specifications. Different colors indicate different rule types, sensor/actuator states, and relationship strengths, making verification easy while maintaining automation benefits.
Data Source
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AI summary
The invention relates to the field of methods for industrial processes, particularly for industrial plants and/or processes, particularly to a method for visualizing a rule of an industrial process, the method comprising the steps of: providing a topology model of the industrial process, wherein the industrial process comprises at least one sensor and at least one actuator; attributing the topology model with a rule (R), wherein the rule (R) comprises a triple < cause (C), traversal (T), effect (E) >, wherein the cause (C) comprises a range of values from the at least one sensor, the effect (E) comprises an action performed by the at least one actuator, and the traversal (T) comprises a relation between the cause (C) and the effect (E); marking the cause (C), the traversal (T) and/or the effect (E); and visualizing the elements of the rule (R) in the topology model.