Vehicle Service Database Modification via Statistical Symptom Correlation
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Solution Overview
Problem
Vehicle diagnostic tools often fail to provide comprehensive solutions for vehicle problems, as diagnostic trouble codes (DTCs) may not cover all possible remedies, leading to repeated visits by technicians before the issue is fully resolved.
Innovation Solution
A method that modifies vehicle service databases by statistically analyzing past symptom text and solutions, using clustering algorithms to correlate additional solutions with existing data, and associating them with symptom text and DTCs, thereby providing a broader range of potential solutions to technicians.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the database provides only DTC-associated solutions, then the database structure remains simple and easy to query, but the completeness of solutions is insufficient leading to repeated technician visits
Solution Approach 1:
The patent combines multiple data sources including DTC associations, symptom text correlations, and past service inquiry data into a unified database structure. This merging allows the system to provide comprehensive solutions by integrating structured DTC data with unstructured text analysis results, thereby improving solution completeness without requiring separate independent systems
Solution Approach 2:
The patent introduces statistical analysis mechanisms and natural language processing components as intermediaries between the DTC database and the solution retrieval process. These intermediaries analyze symptom text, identify correlations with past inquiries, and bridge the gap between raw DTC data and comprehensive service solutions, enabling enhanced completeness without direct structural complexity in the core database
2Loss of information
If statistical analysis of past service inquiries is implemented, then additional relevant solutions are identified and associated with symptom text, but the data processing time and computational resources increase
Solution Approach 1:
The patent performs statistical analysis and correlation identification in advance during database population and maintenance phases. By pre-processing service inquiry data, pre-computing correlations between symptom text and solutions, and pre-associating additional solutions before actual diagnostic queries, the system minimizes processing time during critical service operations while maximizing solution coverage
Solution Approach 2:
The patent replaces traditional manual or rule-based solution matching with automated statistical analysis and natural language processing mechanisms. This substitution enables efficient processing of large volumes of service inquiry data through computational algorithms rather than manual analysis, reducing processing time while improving the accuracy and comprehensiveness of solution identification
Data Source
AI summary
A system and method of modifying a vehicle service database includes: accessing a database containing previously-received symptom text that has been associated with a vehicle identifier and one or more vehicular service solutions for the previously-received symptom text; determining a statistical likelihood that one or more additional vehicular service solutions apply to previously-received symptom text based on a correlation between the previously-received symptom text and additional vehicular service solutions; determining that the statistical likelihood is above a predetermined threshold; and associating the previously-received symptom text with the additional vehicular service solutions.