Phenomenological modelling of micro-cutting based on experimental results - Université de Lorraine Accéder directement au contenu
Article Dans Une Revue International Journal of Advanced Manufacturing Technology Année : 2017

Phenomenological modelling of micro-cutting based on experimental results

Résumé

In micro-milling, cutting forces are driven by many parameters, including feed per tooth, depth of cut, rake angle and machined material. Because of size effects, issues inherent in the micro-milling process, such as chatter, edge radius or tool deflection, influence the cutting forces making it difficult to understand the process. To overcome this problem, the best solution is to performexperiments independently on each parameter. With orthogonal and oblique micro-cutting experiments, chip formation is investigated with fewer parameters. This study aimed to model micro-cutting using the results obtained from orthogonal and oblique micro-cutting experiments, based on tube turning ignoring dynamic considerations. It was experimentally observed that a jump in cutting forces occurs when the uncut chip thickness decreases, described as a transient regime between ploughing and shearing dominant regimes. The ploughing regime for low uncut chip thicknesses is characterised by a normal force greater than the cutting force. At higher uncut chip thicknesses, the cutting force is dominant. A phenomenological model was developed to take into account the divergence in cutting forces at low uncut chip thicknesses. The model was divided into two terms that model, respectively, ploughing and shearing regimes with a continuous transient regime. The model reproduced the behaviour quite well and could be enriched with more parameters.
Fichier non déposé

Dates et versions

hal-02131330 , version 1 (16-05-2019)

Identifiants

Citer

Romain Piquard, Sébastien Thibaud, Alain Acunto, Michael Fontaine, Daniel Dudzinski. Phenomenological modelling of micro-cutting based on experimental results. International Journal of Advanced Manufacturing Technology, 2017, 88 (9), pp.3429-3436. ⟨10.1007/s00170-016-9047-9⟩. ⟨hal-02131330⟩
104 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More