Autonomous Alarm Response Benchmarking for Industrial Equipment
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Solution Overview
Problem
Industrial autonomous systems face challenges in effectively responding to alarm events generated by deviations in equipment operation parameters, leading to potential prolonged operation with suboptimal parameters, affecting production quality and efficiency.
Innovation Solution
A method and system for evaluating the performance of industrial autonomous systems by detecting alarm events, initiating corrective actions, comparing these actions to benchmark actions, and generating a performance rating based on the differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If industrial autonomous systems operate continuously without human intervention, then productivity increases and operational costs decrease, but the system's ability to effectively respond to alarm events deteriorates
Solution Approach 1:
The patent implements a performance evaluation system that continuously monitors alarm events and corrective actions taken by the autonomous system. The system compares actual corrective actions against benchmark actions, generates performance ratings, and provides feedback for optimizing future responses. This closed-loop feedback mechanism enables the autonomous system to maintain reliable alarm response while operating without human intervention.
Solution Approach 2:
The patent establishes benchmark corrective actions in advance for various alarm scenarios. These pre-defined benchmark actions serve as reference standards that the autonomous system can compare against its actual responses. By having preliminary benchmarks ready, the system can quickly evaluate and improve its alarm response effectiveness without requiring real-time human decision-making.
2Loss of time
If corrective actions are automatically initiated in response to alarm events, then response time decreases, but the precision of corrective actions deteriorates
Solution Approach 1:
The performance evaluation system provides continuous feedback by comparing automated corrective actions against benchmark standards. This feedback loop allows the system to learn from past performances and refine its automated decision-making algorithms, thereby improving the precision of corrective actions over time while maintaining rapid response times.
Solution Approach 2:
The patent replaces human mechanical decision-making with automated systems enhanced by performance evaluation and benchmark comparison. The automated system uses algorithmic decision-making supported by benchmark data to achieve both rapid response and high precision in corrective actions, substituting human operator judgment with data-driven automated intelligence.
3Reliability
If more alarm monitoring parameters are tracked, then system reliability improves, but device complexity increases
Solution Approach 1:
The performance evaluation system serves multiple functions simultaneously: it monitors alarm events, evaluates corrective actions, compares performance against benchmarks, generates ratings, and provides optimization recommendations. This multi-functional approach enables comprehensive monitoring of multiple parameters without proportionally increasing system complexity, as a single integrated system handles diverse evaluation tasks.
Data Source
AI summary
Techniques for evaluating performance of an industrial autonomous system are described. In an example, a corrective action initiated by the industrial autonomous system is identified, where the corrective action is initiated for responding to an alarm event associated with an equipment at an industrial facility. The alarm event is generated upon detection of a deviation beyond threshold, where the deviation is associated with at least one operation parameter of the equipment. Further, the industrial autonomous system is utilized for monitoring operation parameters of the equipment and initiating the corrective action by modifying a first set of operation parameters. The corrective action is then compared with a benchmark corrective action. A performance rating of the industrial autonomous system is then generated based on a difference between the corrective action and the benchmark corrective action.