Locomotive Root Cause Determination via Keyword Similarity
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Solution Overview
Problem
Current methods for determining the root cause of equipment failures, such as locomotive road failures, rely heavily on subjective expert opinions, which are time-consuming, inefficient, and prone to human error, often taking weeks or months and resulting in unreliable conclusions.
Innovation Solution
A cloud-based system that analyzes historical equipment failure data and keywords to automatically determine the root cause of current failures by calculating similarities between textual data from various sources, providing instant and accurate recommendations that can supplement or replace expert opinions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subject matter experts manually review failure information and repair logs to determine root cause, then expertise-based analysis can be applied, but the process takes weeks and produces unreliable results due to subjective opinion
Solution Approach 1:
The patent replaces the mechanical system of human expert review with an automated computer-based system that uses natural language processing and machine learning algorithms to analyze failure information, repair logs, and maintenance notes, thereby eliminating subjective opinion and significantly reducing analysis time while improving accuracy
Solution Approach 2:
The system creates a digital copy of the expert knowledge base by training machine learning models on historical failure data and expert determinations, allowing the system to replicate expert-level analysis capabilities without requiring actual human experts to perform each review
2Adaptability or versatility
If multiple experts review the same failure information, then diverse perspectives can be considered, but different conclusions are reached due to subjectivity
Solution Approach 1:
The patent replaces multiple human experts with a single automated system that applies consistent algorithms and criteria to all failure analyses, eliminating the variability and subjectivity inherent in human judgment while maintaining the ability to consider multiple factors through comprehensive data analysis
Solution Approach 2:
The system incorporates feedback loops where historical failure data and expert determinations are continuously used to train and improve the machine learning models, ensuring that the system learns from past performance and continuously refines its analysis capabilities while maintaining consistency
3Measurement precision
If comprehensive failure information is manually analyzed, then thorough evaluation can be performed, but the complexity of reviewing hundreds of factors overwhelms human experts
Solution Approach 1:
The patent replaces human cognitive processing with computer-based automated analysis systems that can efficiently process and analyze hundreds of failure factors simultaneously using natural language processing, data mining, and machine learning algorithms without being overwhelmed by complexity
Solution Approach 2:
The system segments the complex analysis process into distinct computational modules including data collection, natural language processing, pattern recognition, and root cause ranking, allowing each module to handle specific aspects of the analysis independently and efficiently
Data Source
AI summary
The example embodiments are directed to a device and method for determining a root cause of equipment failure. In one example, the method includes storing a plurality of root causes of previous equipment failures, receiving textual data associated with a current equipment failure, determining a root cause for the current equipment failure by determining a similarity of keywords of each root cause with respect to the received textual data of the current equipment failure and selecting at least one root cause based on the determined similarities of the plurality of root causes, and displaying the at least one determined root cause for the current equipment failure via a display device. The example embodiments provide a system and method that automatically determine a root cause of equipment failure rather than rely on a subject matter expert.