Industrial Facility Fault Checking With Random Chaos Testing
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Solution Overview
Problem
Current methods for checking industrial automation facilities are inadequate in ensuring comprehensive and reliable fault detection, particularly due to the complexity of interactions among numerous components, leading to undetected faults and insufficient testing of fault scenarios during commissioning.
Innovation Solution
A method utilizing a random-based chaos approach, where real and simulated components of an industrial facility are manipulated using a computer program with a random algorithm to induce fault scenarios, allowing for comprehensive and reliable checks, including previously unconsidered faults, during both simulation and real facility commissioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual targeted fault scenarios are tested during commissioning, then specific fault situations can be detected, but comprehensive coverage of all possible faults is insufficient
Solution Approach 1:
The patent transforms static, pre-planned fault scenarios into dynamic, randomly generated fault situations. The testing system automatically generates diverse fault scenarios during commissioning rather than relying on fixed test cases, enabling comprehensive coverage of unexpected fault combinations while maintaining manageable testing complexity through automation.
Solution Approach 2:
The testing system performs self-directed fault scenario generation and execution without requiring extensive manual intervention. The automated system independently identifies, generates, and tests fault scenarios, reducing the burden on commissioning engineers while improving testing thoroughness.
2Reliability
If all possible fault scenarios are comprehensively tested, then system reliability is improved, but the time and effort required for testing increases significantly
Solution Approach 1:
The patent implements preliminary automated testing of fault scenarios during the commissioning phase before actual operation begins. By performing comprehensive fault testing in advance using random scenario generation, the system identifies and resolves potential issues early, preventing time-consuming troubleshooting during operational phases.
Solution Approach 2:
The system varies fault scenario parameters randomly during testing, including different fault types, locations, and combinations. This parameter variation enables comprehensive coverage of the solution space without requiring exhaustive manual testing of each individual scenario, significantly reducing commissioning time while maintaining thoroughness.
3Reliability
If engineers manually design and execute test scenarios, then targeted faults can be identified, but unconsidered faults from system complexity remain undetected
Solution Approach 1:
The patent replaces manual mechanical testing processes with automated computer-based fault scenario generation and execution. The system automatically generates, executes, and analyzes fault scenarios without requiring engineers to manually design and perform each test, significantly improving both fault coverage and operational ease.
Solution Approach 2:
The testing approach transitions from static, pre-defined scenarios to dynamic, adaptively generated fault situations. The system continuously generates new fault scenarios based on system characteristics and previous test results, enabling discovery of previously unconsidered faults while simplifying the testing process through automation.
Data Source
AI summary
A computer program, a computer-readable medium and to a system and method for checking an industrial facility formed as an automation facility, wherein real components of a provided real facility and/or data stemming from the real facility and/or simulated components of a provided simulated facility and/or data stemming simulated facility are manipulated using a computer program that includes at least one random algorithm, in particular during ongoing operation, such that random-based fault situations are caused in the real facility and/or the simulated facility.