Vehicle Diagnostic Flowchart Updates From Technician Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle diagnostic systems lack the ability to adapt and improve diagnostic flowcharts based on real-time feedback from technicians, leading to inefficiencies in vehicle diagnosis and repair processes.
Innovation Solution
A system and method that involves a computing server receiving feedback data from diagnostic computing devices, modifying diagnostic flowcharts based on this feedback, and sending updated flowcharts to repair tools for improved vehicle diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If diagnostic flowcharts are manually created and statically maintained, then the initial diagnostic capability is established, but the system cannot adapt to improve based on actual usage feedback
Solution Approach 1:
The system implements feedback loops where diagnostic data collected from vehicle diagnostics is fed back to automatically update and refine diagnostic flowcharts. This continuous feedback mechanism allows the flowcharts to adapt and improve based on real-world diagnostic outcomes, resolving the contradiction between static maintenance and adaptability.
Solution Approach 2:
The diagnostic system performs self-updating through automated analysis of collected diagnostic data. The system autonomously refines flowcharts based on patterns observed in actual diagnostic cases, eliminating the need for manual updates while continuously improving diagnostic accuracy and adaptability.
2Reliability
If diagnostic flowcharts are frequently updated based on feedback, then diagnostic accuracy improves, but system complexity increases
Solution Approach 1:
The system replaces manual flowchart updating mechanisms with automated computational processes. Algorithms automatically analyze diagnostic data, identify patterns, and generate flowchart updates, substituting complex manual procedures with streamlined automated systems that improve accuracy without proportionally increasing complexity.
Solution Approach 2:
The system dynamically adjusts diagnostic parameters and flowchart structures based on analyzed feedback data. By automatically modifying flowchart parameters such as decision nodes, diagnostic paths, and evaluation criteria, the system improves diagnostic accuracy while the automation manages complexity.
3Productivity
If comprehensive feedback data is collected from all diagnostic operations, then flowchart optimization improves, but data processing requirements increase
Solution Approach 1:
The system extracts only the most relevant and actionable feedback data from comprehensive diagnostic operations for flowchart optimization. By filtering and selecting critical data points rather than processing all collected data, the system improves optimization efficiency while reducing unnecessary data processing overhead.
Solution Approach 2:
The system implements selective feedback collection and processing, focusing on specific diagnostic scenarios and outcomes that have the greatest impact on flowchart optimization. This partial action approach processes sufficient data to achieve meaningful optimization without the excessive resource consumption of analyzing every possible data point.
Data Source
AI summary
Methods and system pertaining to modifying a diagnostic flowchart are described. A method can include (i) receiving, from a diagnostic computing device, a request indicative of a vehicle problem, (ii) selecting a first diagnostic flowchart associated with the vehicle problem from a plurality of diagnostic flowcharts. Each diagnostic flowchart includes one or more ordered and performable path elements, where each path element leads to one or more ordered decision elements, where each path element comprises one or more diagnostic steps. The method also includes (iii) sending the first diagnostic flowchart for performance at a diagnostic computing device, (iv) determining first feedback data associated with a performance of the first diagnostic flowchart at the diagnostic computing device, and (v) modifying the first diagnostic flowchart based at least on the first feedback data.