Overview:

• Department: Engineering - Production - Maintenance. Profile: Industrial / Manufacturing / Data student with interest in AI and digitalization.
• Context: OEE (Overall Equipment Effectiveness) is currently monitored manually and updated retrospectively; the project aims to enable real-time visibility and proactive reaction to production deviations.

Objectives & Tasks:

• Develop a connected interface (e.g., Python + Power BI / IoT) to collect and display real-time OEE metrics.
• Integrate an AI model that anticipates OEE drops based on production trends and provide automatic alerts to supervisors via a dashboard.
• Implement real-time OEE monitoring and early detection of deviations before they impact production.

Required Skills & Technologies:

• Data acquisition & system integration experience to connect PLCs/IoT sensors or existing production data sources.
• Proficiency in Python and experience with Power BI for dashboarding; familiarity with basic AI/ML modeling for time-series or anomaly detection.

Expected Deliverables & Outcomes:

• A working connected interface and dashboard (Power BI or equivalent) showing live OEE metrics and historical trends.
• An AI/ML component that predicts imminent OEE drops and a notification/alert mechanism for supervisors.
• Documentation of integration steps, data flows, model performance, and user instructions for the dashboard.

Project Details & Logistics:

• Duration: 06 Months (listed) — 4-6 months expected for the internship.
• Number of interns: 01; focus on production impact reduction through digitalization.

Application:

• To apply, contact: G-TN-StagePFE@autoelectric.com
• Use the provided email address and reference this specific project in your application to ensure proper routing.