FAST AI DTC ROOT CAUSE

Project context

A single fault can generate many Diagnostic Trouble Codes (DTCs). Their analysis broadens the field of possible causes and slows down diagnosis in the workshop. This PFE project aims to use AI to isolate the relevant DTCs.

Objective

Design a prototype diagnostic aid that filters out DTCs and classifies probable root causes. Evaluate the relevance of the results and the analysis time while keeping validation by the business expert.

Scope of work

• Analyze the available data and build a set of annotated cases.
• Compare a rules-based approach with AI models.
• Deliver an explainable prototype, an evaluation report, and technical documentation.

Required skills

• Python
• Data preparation
• Machine learning
• Basics in automotive diagnostics, DTCs, and embedded computers
• Experimental rigor, analytical skills, and ability to interact with business experts

Offer details

• Reference: 27-18
• Position: Engineer, 1 opening
• Duration: 6 months
• This is a Projet de Fin d'Études within Ampere Software Technology Tunisia. Candidates prepare a BAC+5 engineering degree specializing in computer science, embedded systems, electronics, or telecommunications. Integration is planned for February 2027.