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1 MAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l-Aérien 2 ICA - Institut Clément Ader 3 IMT - Institut de Mathématiques de Toulouse UMR5219

Abstract : Plunge milling is a recent and efficient production mean for machining deep workpieces, notably in aeronautics. This paper focuses on the minimization of the machining time by optimizing the values of the cutting parameters. Currently, neither Computer-Aided Manufacturing CAM software nor standard approaches take into account the tool path geometry and the control laws driving the tool displacements to propose optimal cutting parameter values, despite their significant impact. This paper contributes to plunge milling optimization through a Mixed-Integer NonLinear Programming MINLP approach, which enables us to determine optimal cutting parameter values that evolve along the tool path. It involves both continuous cutting speed, feed per tooth and, in contrast with standard approaches, integer number of plunges optimization variables, as well as nonlinear constraints. These constraints are related to the Computer Numerical Control CNC machine tool and to the cutting tool, taking into account the control laws. Computational results, validated on CNC machines and on representative test cases of engine housing, show that our methodology outperforms standard industrial engineering know-how approaches by up to 55% in terms of machining time.

Keywords : Plunge milling Mixed-Integer NonLinear Programming Machining time optimization Optimized cutting parameters





Autor: Sonia Cafieri - Frederic Monies - Marcel Mongeau - Christian Bes -

Fuente: https://hal.archives-ouvertes.fr/



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