CE10 - Usine du futur : Homme, organisation, technologies

Smart machining for controlling part deflection – IMaDe

Submission summary

This project focuses on large aluminum part machining for nuclear and aerospace sectors. To meet the functional requirements, the raw parts are produced with processes which generate residual stress. The reorganization of these stresses after a removal of material induces a deformation of the part during the machining and after unclamping. This results in a non-control of the geometric quality (several millimeters) of the machined parts and the setting of recoveries additional operations.
In this project, we are interested in controlling the parts deformation during machining from an in-situ measurement of the part behavior and defining an intelligent adaptation of the clamping and the positioning of the part. This project contributes to the implementation of so-called intelligent machining adapted to the behavior of the part during machining and after unclamping.
To achieve this goal, we want to conduct research activities around two major scientific obstacles:
• The development of a quantitative imaging measurement method adapted to the machining of large parts by coupling stereo-correlation and image projection:
In this project, we want to carry out research activities to introduce a new full-field measurement method consistent with the machine tool environment and deformation kinematics. To implement this new method, formulated on a CIN approach, we will couple it with a method of projecting an image using a projector on the part surfaces. This strategy allows us to work on parts with high material removal rate. An activity of this project will focus on the choice of the projected pattern which will allow us to estimate directly by CIN the deformation of the part and displacements in the order of 0.02 mm in the machine reference frame.
The challenge then is to determine an absolute displacement of the general part shape with regard to the machining reference system and the positions of the functional surfaces in the part reference frame.
• Reduction of the dimensional defects generated by the rebalancing of the residual stresses by means of an intelligent machining clamping system:
A literature review has shown that the balancing of the machined part in the raw part, the number and the positions of the clamping system and the isostatic points of support, the values of the clamping forces as well as the machining strategy have a very significant influence on the deformation and of dimensional and geometric defects of the machined piece. Thus, we want to implement an approach consisting in acting in real time on the clamping system to constrain or deform the workpiece during machining. For this, the clamping and positioning system must be able to modify, depending on the measured quantities (clamping force, cutting forces, thickness measurement) and a pre-established strategy, the forces applied to the part and the position of its support points.
The coupling of the measured forces with a measurement of the deformation of the part and a meta-model realized within the framework of this project must make it possible to estimate in real time the final deformation of the part after unclamping. The final goal is to evolve this intelligent machining clamping system.
Even if these two scientific obstacles relate to different aspects, they are, in fact, intimately linked. The method of measuring kinematic fields and the measured stresses with the clamping system must make it possible to readjust and enrich a meta-model in order to predict the final deformation of the machined part and to change the clamping and positioning of the part.
This work will define an instrumentation and a strategy to control the quality of machined parts with residual stresses.

Project coordinator


The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.



Help of the ANR 573,950 euros
Beginning and duration of the scientific project: September 2019 - 48 Months

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