Internship - R&D Engineer - Root Causes Of Turn-Ups During Hot Rolling Voreppe Fr 38341 H/F Constellium

C-TEC RECRUTE

INTERNSHIP - R&D ENGINEER F/H/X

Constellium is a global leader designing and manufacturing innovative and high value-added aluminum products and solutions for a broad range of applications dedicated primarily to aerospace, automotive and packaging markets. Constellium Technology Center (C-TEC) based in Grenoble (Voreppe - 38) is Constellium' s European research center with 246 employees and 20 nationalities.

PROJECT TITLE : «Investigation of the root causes of turn-ups during hot rolling : link with process parameters and corrections by the use of Artificial Intelligence»

Background

C-TEC aims at developing world-class prototyping capability for automotive sheet, aerospace plate and packaging products. Hot and cold rolling are the main transformation steps to prototype and produce aluminum strips. During the rolling process on reversing mills, the shape of the slab evolves in the thickness and in the length of the original ingot, it becomes thinner and longer, but other phenomena may occur. In particular, the deformation of the mill induces a non-homogeneous thickness deformation along the width (called profile') and sometimes, as the slab is not clamped at its extremities, an out-of-plane displacement of the slab (called turn-up') may occur.
These two phenomena are quite well understood from thermo-mechanical aspects; however, the quantification of the process parameters impact requires to go deeper in the understanding.
Profile and turn-up will be studied by means of physical theory, lab experiments, production data analysis, simulation data analysis, regression from statistics or artificial intelligence (AI).

Main Objectives
Describe the link between the process parameters and Profile + Turn-up and set up a correction strategy, in real-time or from pass to pass, based on AI.

- to quantify the correlation between process parameters and output parameters (profile & turn-up),

- to set up models (statistical model or AI model) to describe both profile and turn-up,

- design, implement and test correction strategies to reach the desired profile and to eliminate the turn-ups occurrence.

The resulting correction methods are expected to be shared over the plants of Constellium.

Key Highlights

- Constellium C-TEC has proven expertise in prototyping, modelling and digital techniques.

- Exposure to a large field of competencies (experiments, modelling, computing, AI techniques).

- Close collaboration with several groups within the R&D center and with Constellium plants.

Profile:

Education level : students engaged in their final year of Master's or Material / Mechanical Engineer's degree

Competencies & technical & soft skills requirement :

- Background in material science or a closely related discipline,

- Interested in research activities, including numerical data processing and numerical modelling,

- Solid basic knowledge in statistics and AI techniques,

- Solid basic knowledge in programming languages like Python or comparable,

- Good communication and team-work skills.