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A new approach for machine-tool architecture selection at preliminary design stage

Authors :
Emmanuel Duc
Hélène Chanal
B. Chedli Bouzgarrou
Mohamed Lajili
DUGAT, Pascale
Institut Pascal (IP)
SIGMA Clermont (SIGMA Clermont)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)
Source :
JCM, JCM, 2018, CARTAGENA, Spain, Advances on Mechanics, Design Engineering and Manufacturing II ISBN: 9783030123451
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

Productivity and quality requirements in the aerospace industry involve optimized machine-tools in terms of stiffness, precision, kinematics and dynamics. Many researches aiming at evaluating and optimizing machine-tool performances in the preliminary design stage have been carried-out. This paper presents a new approach for selecting the best appropriate machine-tool architecture, for a given application, based on optimizing conceptual design models. In fact, considered machine-tool structures are modeled with simplified shape parts. The dimensions of these parts are defined as design variables. Afterward, a parametric design optimization is performed for each considered architecture, in order to minimize its total mass under the constraint of a minimal attempted stiffness all over the workspace. After that, several architectures can be compared and classified according to performance indices computed from the mechanical behavior of their corresponding optimized structures. This approach allows restricting the total number of structural arrangements to be detailed further and analyzed more accurately. The paper includes an illustration of the proposed approach through a comparative study between an open-loop and a closed-loop machine-tool architectures.

Details

Language :
English
ISBN :
978-3-030-12345-1
ISBNs :
9783030123451
Database :
OpenAIRE
Journal :
JCM, JCM, 2018, CARTAGENA, Spain, Advances on Mechanics, Design Engineering and Manufacturing II ISBN: 9783030123451
Accession number :
edsair.doi.dedup.....16fe65fe9c7dfdf3df88e1f356dc3614