Fast AI DTC Root Cause
Renault Group
Fast AI DTC Root Cause
Renault Group
Global automotive manufacturer in alliance-based EVs
Context :
A single fault can generate many fault codes (DTCs). Their analysis broadens the field of possible causes and slows down the diagnosis in the workshop. The project aims to isolate the relevant DTCs using AI.
Design a prototype diagnostic aid that filters out DTCs and classifies probable root causes. Evaluate the relevance of the results and the analysis time, keeping the validation of the business expert.
Your role :
Analyze the available data and build a set of annotated cases.
Compare a rules-based approach to AI models.
Deliver an explainable prototype, an evaluation report and technical documentation.
Key skills :
Python and Rust
Data preparation
Machine learning
Basics in automotive diagnostics, DTC and embedded computers.
Experimental rigor, analytical skills and ability to interact with business experts.
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Global automotive manufacturer in alliance-based EVs
Renault Group is a global automaker that designs, builds, and sells cars and light commercial vehicles. Through its participation in the Renault–Nissan–Mitsubishi Alliance, it shares platforms, engines, and technology with partner brands to improve efficiency and bring new models to market faster. Renault differentiates itself by operating within a large cross-brand alliance that pools research, development, and manufacturing resources, helping it compete on scale and spread costs across multiple markets. Its goal is to provide a broad range of affordable, reliable vehicles with a strong emphasis on electrification and sustainable mobility, while maintaining profitability through collaboration and global reach.
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