Cloud DTC Data Standardization for Fleet Root Cause Analysis
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Solution Overview
Problem
Existing vehicle diagnostic trouble code (DTC) systems face inefficiencies in data collection, processing, and analysis, leading to time-consuming manual reporting processes and difficulties in detecting and determining the root cause of issues across different vehicle models and years, which affects vehicle safety and warranty costs.
Innovation Solution
A cloud-based platform server that centralizes and standardizes DTC data from multiple vehicles, using artificial intelligence to parse, format, and analyze data, enabling automated reporting and root cause detection, with features like data logging, debugging, and blacklisting to enhance efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data collection and processing methods are used, then system complexity is low, but processing time increases and productivity decreases
Solution Approach 1:
The patent replaces manual mechanical data collection and processing methods with an automated cloud-based platform that uses electronic data transmission, parsing, and analysis systems. This substitution dramatically increases processing speed while managing complexity through standardized automated workflows.
Solution Approach 2:
The patent introduces a cloud-based platform server as an intermediary between data sources (vehicles, service tools) and end users. This intermediary centralizes data collection, parsing, and analysis functions, improving productivity while containing complexity within the intermediary system rather than distributing it across multiple manual processes.
2Measurement precision
If comprehensive DTC data from multiple vehicles is collected, then measurement precision improves, but data processing complexity increases
Solution Approach 1:
The patent creates a universal cloud-based platform that handles multiple vehicle types, models, and data sources through standardized parsing and analysis functions. This multi-functional system achieves comprehensive data collection across diverse vehicles while managing complexity through unified processing protocols and standardized data formats.
Solution Approach 2:
The patent transforms raw DTC data from multiple vehicles into standardized formats through parsing and conversion processes. By changing the parameters and structure of the data during processing, the system maintains measurement precision across diverse sources while simplifying subsequent analysis through consistent data representation.
3Ease of operation
If standardized data formats are implemented across different vehicles, then ease of operation improves, but initial processing time increases
Solution Approach 1:
The patent performs preliminary parsing and standardization of DTC data during the initial collection phase. By preprocessing and converting data to standardized formats upfront, the system eliminates the need for manual formatting during analysis, significantly improving ease of operation for subsequent queries and reports despite the initial processing investment.
Solution Approach 2:
The patent creates standardized copies of raw DTC data in uniform formats while preserving the original data. This copying approach allows the system to maintain ease of operation through consistent data structures for analysis while the initial processing time is invested only once during the standardization phase, not during each subsequent analysis operation.
Data Source
AI summary
A cloud-based platform server includes a memory, a receiving module, and a reporting module. The memory stores a DTC configuration table including DTC rules and a DTC data table. The receiving module: receives DTC configuration information transmitted from a configuration server to the cloud-based platform server and DTC data uploaded from a data server to the cloud-based platform server, where at least some of the DTC data was originally generated by multiple vehicles; based on one or more selected vehicle platforms, parse the DTC configuration information and the DTC data; convert the parsed DTC configuration information to a standardized format and the parsed DTC data having different formats to a standardized format; generate or update the DTC configuration table based on the parsed and converted configuration information; and generate or update the DTC data table based on the parsed and converted DTC data and the DTC rules.