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Benjamin LAMOUREUX

PARIS

En résumé

Mechatronics engineer by training, I progressively shifted the domain of data science through predictive maintenance. I like to see myself at the crossroads of predictive maintenance engineering and data science, my mission being to turn experts knowledge into an automated data processing solution. My professionnal objective is to flourish predictive maintenance and data science in the industry.

Mes compétences :
Simulink
AMESim
Machine Learning
Microsoft Office
Microsoft Project
MATLAB
Railway
Aerospace
Signal Processing
Windows Azure
Automation
Engineering
Big Data
HortonWorks
Statistical Modeling
Multivariate Statistics
Health Monitoring
Linux
SQL
Prognostics
Python
R
Predictive Maintenance
Sensitivity Analysis
Python Programming
shell scripting
Robotics
Microsoft SharePoint
Journals
Intellectual Property Law
Databases management
Data processing
Data preparation
D project management

Entreprises

  • ALSTOM Transport - Ingénieur maintenance prédictive / PHM

    2014 - maintenant R&D program for the development of data science technologies applied to predictive maintenance:
    1.Business and data understanding: capture both the end user need and the domain expert knowledge to understand the business value
    2.Data preparation: cleansing of the dataset, incorporation of external data, signal processing for raw time series
    3.Data engineering: participation in the IT architecture definition for Big Data, configuration of database servers, management of database structure and connectors to programming languages
    4.Data processing: programming in Matlab, R and Python: extraction of features from time series, multivariate statistical analysis, machine learning
    5.Pre-industrialization of the solution (demonstrator): deployment and automation of scripts execution on linux cloud environment
    6.R&D project management (including collaboration with several research labs)

  • Alstom - Data Scientist & Predictive Maintenance Eng.

    2014 - maintenant Involvement in a R&D program on predictive maintenance for rolling stock and signaling:
    * Business/data understanding: capture end user need and the expert knowledge ;
    * Data preparation: cleansing of the dataset, signal processing for raw time series ;
    * Data engineering: participation in the IT architecture definition for Big Data ;
    * Data processing: machine learning in Matlab, R and Python ;
    * Pre-industrialization: deployment and automation on linux cloud environment ;
    * R&D project management including collaboration with several research labs

  • Safran Snecma - Predictive Maintenance PhD Eng.

    2011 - 2014 Title : ``Development of an Integrated Approach for PHM - Prognostics and Health
    Management - : Application to a Turbofan Fuel System ''.
    * 2 publications in international journals with peer review process [1] [2] ;
    * 6 international conferences with peer review process [1] [2] [3] ;
    * 2 international patents [1] [2] ;
    * 60 hours of teaching in automation and signal processing

  • Snecma - Predictive Maintenance PhD Engineer

    Courcouronnes 2011 - 2014 PhD program (CIFRE) untitled:
    "Development of an Integrated Approach for PHM - Prognostics and Health Management - :
    Application to a Turbofan Fuel System"​

    The full manuscipt is available at: https://hal.inria.fr/hal-01102742/document

    - Terminological and architectural formalism for prognostics and health management of aerospace systems
    - Physics-based modeling (cosimulation Matlab/AMESim) to assess the performance of PHM systems during early design stages
    - Utilization of different sensitivity analysis techniques to simplify the model
    - Development of a combination of Kriging with support vector regression to provided a low runtime estimator of the model outputs

Formations

  • Ecole Nationale Supérieure Des Arts Et Métiers

    Paris 2011 - 2014 Thèse de doctorat délivrée par l’École Nationale Supérieure des Arts et Métiers

    Development of an Integrated Approach for PHM - Prognostics and Health Management - : Application to a Turbofan Fuel System
    Laboratoire : Procédés et ingénierie en mécanique et matériaux (PIMM - UMR 8006)
    Direction : Philippe Lorong, co-encadrée par Nazih Mechbal
    Soutenue le 30 juin 2014 devant Albert Benveniste (président), Christophe Bérenguer (rapporteur), Emanuele Borgonovo (rapporteur)

  • Arts Et Métiers Paristech (ENSAM)

    Paris 2010 - 2014 Doctor of Philosophy

    Specialty: automation and signal processing
    Title: "Development of an Integrated Approach for PHM - Prognostics and Health Management - : Application to a Turbofan Fuel System"​
    • 6 international conferences with peer review process
    • 2 publications in international journals with peer review process
    • 2 international patents

  • Arts Et Métiers ParisTech - École Nationale Supérieure D'Arts Et Métiers

    Paris 2010 - 2014 Doctor of Philosophy (PhD)

    60 hours of teaching in automation and signal processing
    Technical reference for the organization of robotics competition "RobAFIS 2012".

    • 6 international conferences with peer review process
    • 2 publications in international journals with peer review process
    • 2 international patents

  • Ecole Nationale Superieure D'Arts Et Métiers ENSAM

    Paris 2007 - 2010 Master of Engineering (M.Eng.)

  • Arts Et Métiers Paristech (ENSAM)

    Paris 2007 - 2010 Master's Degree

    Specialty: Advanced systems and robotics

  • Lycée Clemenceau

    Nantes 2004 - 2007

Réseau

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