drjobs Stage M2 - Validation de lappariement 3D de pices hors tolrances HF

Stage M2 - Validation de lappariement 3D de pices hors tolrances HF

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Monthly Salary drjobs

Not Disclosed

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Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Intgrer LINEACT au sein de CESI pour un stage de recherche serait une formidable opportunit de contribuer des projets innovants tout en approfondissant mes comptences dans un environnement la pointe de la transformation numrique et de lindustrie 4.0.


Abstract


This internship focuses on advancing the integration of AI into production lines by leveraging profilometerdata to optimize waste reduction and enhance precision.

This M2 internship aims to develop the step 4 of the project whose goal is to integrate Artificial Intelligence (AI) into the production line to reduce waste using the profilometers data.

The tasks assigned to the intern are as follows:

Clean the point cloud to only extract the front part and determine if the point cloud is incomplete

Match the CAD of the front part with its cloud point acquired by the laser profilometer.

Determine the key area used to match the back and front part of the product.

Creation of CAD back cover with defaults (out of tolerance dimensions)

Match the CAD of the back part with the cloud point of the front part acquired by the laser profilometer.



Rsum


Ce stage vise faire progresser lintgration de lIAdans les lignes de production en exploitant les donnes des profilomtrespour optimiser la rduction des dchets et amliorer la prcision.

Tolrance correspondance 3D CAO Lean Management Intelligence Artificielle

Ce stage de M2 vise dvelopper ltape 4 du projet dont lobjectif est dintgrer lIntelligence Artificielle (IA) dans la ligne de production pour rduire les dchets en utilisant les donnes des profilomtres.

Les tches assignes au stagiaire sont les suivantes :

Nettoyer le nuage de points pour nextraire que la partie avant et dterminer si le nuage de points est incomplet

Faire correspondre la CAO de la partie avant avec son nuage de points acquis par le profilomtre laser.

Dterminer la zone cl utilise pour faire correspondre la partie arrire et la partie avant du produit.

Cration dune couverture arrire CAO avec des valeurs par dfaut (dimensions hors tolrance)

Faire correspondre la CAO de la partie arrire avec le point de nuage de la partie avant acquis par le profilomtre laser.



Research Work

Scientific context


This initiative is part of the collaboration between Cetim and CESI within the framework of the Industry of the Future. It focuses on implementing an online control demonstrator system integrated into an existing manufacturing chain on the CESI Industry of the Future platform at the Rouen campus

Industry 4.0 (or the Industry of the Future) can be seen as the convergence point between traditional operational and information technologies (ERP MES etc. and datadriven disciplines such as Machine Learning (ML) Big Data Analytics IoT and Cloud Computing.



Subject


The use of these new technologies reduces the costs associated with collecting and managing industrial data while enabling new applications for these data in production and maintenance. For example the various sensors embedded in production equipment must communicate and transmit their data using standard IoT protocols. This ensures better interoperability between the underlying components of the system.

To enhance the production tool additional instrumentation will provide new control capabilities. These instruments must be integrated into the machines MES and capable of disseminating information to other systems.


Prior works in the laboratory


This work follows on from a collaboration between CETIM and CESI which enabled a Profilometer to be installed on a production line. All the documents produced within this framework will be used as a basis for the work.


Context

Lab presentation


CESI LINEACT (UR 7527 Laboratory for Digital Innovation for Businesses and Learning to Support the Competitiveness of Territories anticipates and accompanies the technological mutations of sectors and services related to industry and construction. The historical proximity of CESI with companies is a determining element for our research activities. It has led us to focus our efforts on applied research close to companies and in partnership with them. A humancentered approach coupled with the use of technologies as well as territorial networking and links with training have enabled the construction of crosscutting research; it puts humans their needs and their uses at the center of its issues and addresses the technological angle through these contributions.

Its research is organized according to two interdisciplinary scientific teams and several application areas.

Team 1 Learning and Innovating mainly concerns Cognitive Sciences Social Sciences and Management Sciences Training Techniques and those of Innovation. The main scientific objectives are the understanding of the effects of the environment and more particularly of situations instrumented by technical objects (platforms prototyping workshops immersive systems... on learning creativity and innovation processes.

Team 2 Engineering and Digital Tools mainly concerns Digital Sciences and Engineering. The main scientific objectives focus on modeling simulation optimization and data analysis of cyber physical systems. Research work also focuses on decision support tools and on the study of humansystem interactions in particular through digital twins coupled with virtual or augmented environments.

These two teams develop and cross their research in application areas such as

Industry 5.0

Construction 4.0 and Sustainable City

Digital Services.

Areas supported by research platforms mainly that in Rouen dedicated to Factory 5.0 and those in Nanterre dedicated to Factory 5.0 and Construction 4.0.


Presentation of CETIM

CETIM group


Since 1965 the development of Cetim has led to the creation of an international engineering group that supports your innovation and competitiveness challenges offering the best in mechanical engineering technology expertise. It also aims to lead our clients into the industry of the future in France and worldwide.

Thanks to the expertise of our 1000 experts engineers and technicians serving 4000 clients around the world we achieve a turnover of 150 million. 50 of services are performed in the sectors of aeronautics automotive energy and oil & gas www.cetimengineering.





Skills


Scientific and technical skills:

  • Artificial Intelligence
  • Python & C C# (optional)
  • PyTORCH
  • Tensorflow
  • LINUX (WSL2
  • WINDOWS


Interpersonal Skills :

  • Autonomy initiative curiosity
  • Teamwork ability and good interpersonal skills
  • Rigorousness


Comptences


Comptences scientifiques et techniques :

  • Intelligence Artificielle
  • Python & C C# (optional)
  • PyTORCH
  • Tensorflow
  • LINUX (WSL2
  • WINDOWS


Comptences relationnelles :

  • Autonomie initiative curiosit
  • Capacit travailler en quipe et bonnes aptitudes relationnelles
  • Rigueur


Gratification 15 du plafond horaire de la Scurit Sociale

Date de dbut : Fvrier 2025



#CESILINEACT






Employment Type

Full-Time

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