RPA Failure Evaluation Using Execution Step Commonality
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Solution Overview
Problem
Current robotic process automation systems fail to detect and address changes in processes or screen configurations, leading to operational failures without determining the nature of the failure.
Innovation Solution
A system and method that includes a task queue database, a robotic process automation unit, a failed tasks queue database, and a failure evaluation processor to collect and analyze failed tasks, record successful execution steps, and provide updated execution steps to prevent future failures by calculating a commonality score for execution steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic process automation systems operate without failure detection mechanisms, then operational simplicity is maintained, but system reliability deteriorates due to undetected failures
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring task execution and comparing actual outcomes against expected results. The failure evaluation processor receives feedback from the robotic process automation unit about task failures, analyzes the discrepancies, and generates corrective actions that are fed back to the system to prevent future failures.
Solution Approach 2:
The system performs preliminary actions by proactively identifying potential failures through pattern recognition in failed tasks and implementing preventive measures before actual failures occur. The failure evaluation processor analyzes historical failure data to predict and prevent future task failures.
2Measurement precision
If the system implements comprehensive failure analysis, then measurement precision of failure causes improves, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system segments the failure analysis process into distinct functional modules: the robotic process automation unit executes tasks, the failure evaluation processor analyzes failures, and the system separately stores and processes task type information. This segmentation allows comprehensive analysis while managing complexity through modular architecture.
Solution Approach 2:
The failure evaluation processor acts as an intermediary between the robotic process automation unit and the overall system. It receives detailed failure information, performs comprehensive analysis to identify root causes with high precision, and translates findings into actionable corrective measures, thereby enabling precise failure detection without requiring the entire system to be overly complex.
3Loss of information
If the system collects and analyzes all failed tasks per task type, then information completeness improves for failure detection, but loss of time increases due to data processing requirements
Solution Approach 1:
The system performs preliminary organization of failed tasks by task type, maintaining ready-to-analyze structured data. When failures occur, the evaluation processor can immediately access relevant historical data for comparison without requiring time-consuming data collection or organization, thus achieving complete information analysis with minimal time loss.
4Productivity
If the system implements real-time failure detection and correction, then productivity is improved by preventing failures, but device complexity increases due to monitoring and evaluation components
Solution Approach 1:
The failure evaluation processor serves multiple functions: it detects failures, analyzes their causes, identifies patterns across task types, generates corrective actions, and updates the system to prevent future failures. This multi-functionality enables real-time failure detection and correction while avoiding the need for separate specialized components for each function, thereby managing architectural complexity.
Data Source
AI summary
A system and method for detecting and fixing robotic process automation failures, including collecting tasks from at least one client computerized device, processing the tasks via robotic process automation, collecting tasks that failed to complete per task type, recording successful execution steps per each of the failed tasks, evaluating the recorded successful execution steps with respect to the failed task types, and providing selected execution steps that best fix the failed tasks, thereby fixing the robotic process automation failures.