Jimmy Ndagijimana

Operations Intern – Logistics & Quality Assurance • Training in leading and developing operational teams, ensuring safety, quality, and environmental compliance. • Analyzing KPIs and leading process improvement projects to boost productivity, quality, and customer service. • Collaborating cross-functionally with departments and management to standardize shift procedures and drive Operational Excellence.

• Unterstützung in Produktion und Qualitätssicherung, inklusive Auswertungen, Analysen und Dokumentation (Plus Client.Net, Qlive, Excel). • Mitarbeit im End-of-Line-Bereich: Prüfabläufe, Nacharbeiten und Prozessneuanläufe. • Optimierung bestehender Prozesse und Unterstützung kleiner Projekte. • Erstellung von Entscheidungsgrundlagen, Schulungsunterlagen und Datentabellen zur Qualitätssicherung.

- In C# programmiert, um den Energieverbrauch mit dem Tinkerforge Energieüberwachungsgerät zu messen - Mit Hardwarekomponenten gearbeitet, um Echtzeitdaten zum Energieverbrauch zu sammeln

- Assisting with the installation of LiDAR equipment - Support in the area of office organisation - Supporting the experts and senior experts in their daily work - Assisting in the inspection of sites for wind energy projects

Betreuung von Studierenden mit Schwerpunkt auf Syntax, Datenstrukturen, objektorientierter Programmierung und algorithmischem Problemlösen.

Focus: industrial robotics, IIoT, data analytics, and digitalization engineering (AAS, MQTT, OPC UA). Hands-on work with robotic simulation (KUKA Sim Pro, ROS), real-time data acquisition/visualization (InfluxDB, Grafana), and data-driven analysis (KDD, Python).

Industrial AAS(Digital Twin), Industrial IoT, Data analysis, industrial robotics, Automation, innovation management, and more I4.0 related.

Final grade: 2.3 | Specialization: Wind Energy Bachelor thesis: “Blade design and aerodynamic performance analysis for small horizontal axis wind turbines” (International Small Wind Turbine Contest). • Performed BEM and aerodynamic analysis of wind turbine airfoils (lift/drag, Reynolds number effects, rotor efficiency) using MATLAB and Qlade. • Evaluated blade design parameters and estimated annual energy yield via Weibull wind speed modelling, delivering data-driven design recommendations.