Post-repair data comparison for vehicle diagnostics
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Solution Overview
Problem
Vehicle repair diagnostics often rely on skilled technicians to interpret data from tools like scan tools and DVOMs, which lack contextual information and require manual interpretation, leading to potential unsuccessful repairs and increased comeback rates.
Innovation Solution
A computing device compares post-repair data from a vehicle to a set of recorded successful and unsuccessful repair data to determine the success of a repair, providing an indication and suggesting additional repairs if necessary, thereby aiding technicians in verifying repair success and reducing comeback rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If skilled technicians manually interpret data from scan tools and DVOMs, then data interpretation capability is maintained, but repair verification accuracy decreases and comeback rates increase
Solution Approach 1:
The system automatically compares post-repair diagnostic data against historical successful repair patterns and provides immediate feedback on whether the repair was successful. This feedback mechanism eliminates manual interpretation and provides objective verification of repair success, thereby improving both measurement precision and reliability.
Solution Approach 2:
The patent replaces the mechanical manual interpretation process with an automated computer-based comparison system. The computing device automatically compares diagnostic data against stored historical patterns, substituting human skill with automated algorithms that provide consistent and accurate repair verification.
2Measurement precision
If automated data comparison is implemented, then repair verification accuracy improves, but device complexity increases
Solution Approach 1:
The computing device performs multiple functions: it receives diagnostic data, compares it against historical patterns, determines repair success, and provides feedback. By consolidating these functions into a single system, the patent improves verification accuracy without proportionally increasing complexity, as the same device handles all tasks.
Solution Approach 2:
The system creates a digital copy of historical successful repair data and compares it with current post-repair data. This copying approach allows automated verification without requiring complex real-time analysis systems, as the comparison is made against pre-stored reference patterns.
3Productivity
If manual data interpretation is used, then ease of operation is maintained, but productivity decreases due to increased comeback rates
Solution Approach 1:
The system performs self-verification of repair success by automatically comparing diagnostic data against historical patterns. This self-service capability eliminates the need for technician judgment in verification, improving productivity by preventing comeback repairs while maintaining ease of operation through automated decision-making.
Data Source
AI summary
Methods and apparatus are provided for repairing vehicles. A computing device can receive post-repair data regarding a first vehicle. The computing device can compare the post-repair data to a post-repair dataset regarding at least one vehicle other than the first vehicle. The post-repair dataset can include at least one of an instance of successful post-repair data and an instance of unsuccessful post-repair data. The computing device can determine that a repair to the first vehicle is successful if the post-repair dataset matches an instance of successful post-repair data of the post-repair dataset. The computing device can determine that the repair to the first vehicle is unsuccessful if the post-repair dataset matches an instance of unsuccessful post-repair data within the post-repair dataset. The computing device can indicate whether the repair is successful or unsuccessful.