Because of the improvement of machine-tool and tool performances in micro cutting field, the interest on these processes is increasing. Therefore, researchers involved in micro manufacturing processes focused their attention on these types of processes with the aim of improving the knowledge on the phenomena occurring during micro cutting operations. The objective of this work is to develop a modelling procedure for forecasting cutting forces in micromilling considering the tool run-out and the cutting tool geometry. The designed modelling procedure combines information coming from a force model, an optimization strategy and some experimental tests. The implemented force model is based on specific cutting pressure and actual instantaneous chip section. The tool run-out and the cutting tool geometry were considered in the analytical model. The adopted optimization strategy was based on the Particles Swarm strategy due to its suitability in solving analytical non-linear models. The experimental tests consisted in realizing micro slots on a sample made of Ti6Al4V. The comparison between experimental and analytical data demonstrates the good ability of the proposed procedure in correctly defining the model parameters.

SWARM Optimization of Force Model Parameters in Micromilling

Attanasio, A.;Ceretti, E.;Giardini, C.
2017-01-01

Abstract

Because of the improvement of machine-tool and tool performances in micro cutting field, the interest on these processes is increasing. Therefore, researchers involved in micro manufacturing processes focused their attention on these types of processes with the aim of improving the knowledge on the phenomena occurring during micro cutting operations. The objective of this work is to develop a modelling procedure for forecasting cutting forces in micromilling considering the tool run-out and the cutting tool geometry. The designed modelling procedure combines information coming from a force model, an optimization strategy and some experimental tests. The implemented force model is based on specific cutting pressure and actual instantaneous chip section. The tool run-out and the cutting tool geometry were considered in the analytical model. The adopted optimization strategy was based on the Particles Swarm strategy due to its suitability in solving analytical non-linear models. The experimental tests consisted in realizing micro slots on a sample made of Ti6Al4V. The comparison between experimental and analytical data demonstrates the good ability of the proposed procedure in correctly defining the model parameters.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/498438
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