Data Quality Assessment for Industrial Data

Modèle de maintenance prédictive basé sur un Random Forest optimisé pour détecter les pannes industrielles (AI4I 2020)

Code and processed data accompanying the MSc thesis Integrating Dynamical Systems and Machine Learning for Modeling and Predicting Decay Across Wood Treatments, conducted at DTU in collaboration with the Danish Technological Institute.

Simulation, stockage et visualisation de mesures industrielles en Python/MySQL

Industrial stability and risk analytics framework for solar ingot puller operations using engineered variability, control deviation (SP–PV gaps), drift features, and interpretable regression modeling.

Predictive maintenance analysis of Scania vehicle components using feature engineering, PCA, and association-rule mining.