About Abdoulaye Affadine
- Industrial data reliability and structuring (SQL, Python)
- Predictive modeling & machine learning
- Process monitoring (welding, composite infusion, marine engines)
- Corrosion analysis and equipment aging
- Anomaly detection & performance optimization
- Creation of business indicators/KPIs & dashboards (Power BI, Grafana)
- Nuclear: modeling corrosion degradation, production data analysis
- Maritime: monitoring main & auxiliary engines, energy optimization
- Aeronautics: critical parts quality control, multi-material drilling, MRO
- Composites: real-time monitoring of resin front and process improvement
French
Native or bilingual
Arabic
Native or bilingual
English
Fluent
Spanish
Basic
Experience
- PREDICT-SNEF (IQANTO),Data Scientist|Data AnalystApril 2023 - Today (3 years and 2 months)Toulon, FranceAnalysis of corrosion phenomena in the nuclear sector: collection and validation of production data, development of a methodological modeling framework to estimate equipment degradation and anticipate aging.Maritime transport: monitoring critical equipment (main and auxiliary engines) of the container ships Palais with the objectives of system reliability, energy consumption optimization, and contribution to decarbonization efforts.Aeronautics: development of quality control tools for identifying defects on critical parts and creating robust quality indicators.Naval & Defense: implementation of a real-time monitoring solution for the infusion process of carbon fiber composite parts (resin front monitoring, instrumentation, process analysis, detection of process anomalies, and improvement of manufacturing quality).Supervision: overseeing an apprentice and an intern with a role of technical and methodological mentoring.
- Ecole Nationale superieure des arts et metiersResearch Work | PhD ThesisAVIATION AND AEROSPACENovember 2019 - November 2022 (3 years)Bordeaux, FranceApplied research on the assembly of multi-material aeronautical structures (stacked aluminum alloys, titanium, and carbon fiber composites): study of multi-material drilling issues related to differences in thermomechanical properties and their impact on machining quality and tool life.Development of an auto-adaptive drilling tool: design of intelligent system modules capable of adjusting cutting conditions (spindle speed, feed rate) in real-time based on the material being drilled.Process reliability & monitoring: implementation of an approach for monitoring cutting tool wear and detecting anomalies (tool breakage, chip jamming, lubrication defects).Data & AI: exploration and structuring of drilling data, construction of industrial databases, time and frequency analysis of signals, implementation of machine learning models for automatic detection of materials and wear states.R&D & innovation: proposal of an innovative adaptive machining concept to reduce tool costs and improve the quality of multi-material assemblies.
- Safran Aéro CompositeInternship: Composite Materials and Manufacturing Processes EngineerAVIATION AND AEROSPACEApril 2019 - October 2019 (6 months)Itteville, FranceExperimental analysis of the RTM process applied to textile reinforcements: study of permeability, monitoring of impregnation, and analysis of resin flow phenomena, curing under pressure in the mold.Identification of material laws: rheo-cinematic characterization of aeronautical resins from laboratory tests (viscosity, polymerization kinetics).Analysis and exploitation of permeability tests on different textile reinforcements.Numerical simulations of laboratory tests for validation of material laws.Calculations and simulations at the part level, with verification of simulation / industrial test correlation.Methodological development: improvement of the existing workflow to integrate the influence of pressure in the process and ensure the reliability of part-level simulation.R&D contribution to a strategic Safran project on the manufacturing of high-performance composite engine blades.
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