SMART FACTORY TEST CAMPAIGN AUTOMATION USING AI

Background

Translating high-level operational needs into executable diagnostic scenarios is often a manual, time-consuming, and error-prone process. It relies heavily on expert knowledge to identify the appropriate sequence of elementary diagnostic requests and interpret the expected results. Artificial Intelligence, domain-specific knowledge bases, and rule-based reasoning systems provide an opportunity to automate this process.

An intelligent diagnostic engine could understand operator intent through a user-friendly interface and automatically generate structured diagnostic test campaigns. The solution would improve the productivity of manufacturing, validation, and investigation teams while reducing the expertise required to create and execute complex diagnostic workflows. It would also promote standardization, repeatability, and scalability across different vehicle programs.

Objective

Design and develop, in Rust, an intelligent interpreter capable of transforming operator needs into structured diagnostic test campaigns executable by an embedded vehicle diagnostic platform. The solution will combine:

• A domain knowledge base
• A configurable rule engine
• Artificial Intelligence techniques to understand operator intent and translate it into sequences of elementary diagnostic requests
• An intuitive Human-Machine Interface (HMI)

The final goal is to enable non-expert users to create advanced diagnostic campaigns from natural-language or semi-structured requests, simplifying diagnostic operations while increasing efficiency, consistency, and accessibility.

Scope of work

• Diagnostic Interpretation Engine Development
• Intelligent Human-Machine Interface with AI-Based Recommendations
• Validation and Demonstration

Required skills

• Strong software development skills, particularly Python and Rust/C++
• Data processing and analysis
• Basic knowledge of AI and Machine Learning
• Knowledge of embedded systems, automotive diagnostics, and vehicle communication protocols is a plus
• Autonomy, technical curiosity, and strong analytical skills

Offer details

• Reference: 27-19
• 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.