Abstract
Machining of metals is an essential operation in the manufacturing industry. Chip formation in metal cutting is associated with large plastic strains, large deformations, high strain rates and high temperatures, mainly located in the primary and in the secondary shear zones. During the last decades, there has been significant progress in numerical methods and constitutive modeling for machining operations. In this work, the Particle Finite Element Method (PFEM) together with a dislocation density (DD) constitutive model are introduced to simulate the machining of Ti-6Al-4V. The work includes a study of two constitutive models for the titanium material, the physically based plasticity DD model and the phenomenology based Johnson–Cook model. Both constitutive models were implemented into an in-house PFEM software and setup to simulate deformation behaviour of titanium Ti6Al4V during an orthogonal cutting process. Validation show that numerical and experimental results are in agreement for different cutting speeds and feeds. The dislocation density model, although it needs more thorough calibration, shows an excellent match with the results. This paper shows that the combination of PFEM together with a dislocation density constitutive model is an excellent candidate for future numerical simulations of mechanical cutting.
Highlights
Metal machining is an important manufacturing technique in major mechanical industries like the automobile or aerospace
Results from Particle Finite Element Method (PFEM) simulations of orthogonal cutting using a dislocation based constitutive model and Johnson-Cook constitutive model were compared with experimental measurements of cutting and feed forces, see Tables 5–7
In this work we do not consider fracture or separation of material from the main domain. These phenomenon can readily be included within the PFEM modelling framework
Summary
Metal machining is an important manufacturing technique in major mechanical industries like the automobile or aerospace. Using this technology, the material is removed continuously from the work piece by a cutting tool, creating a new shape for the piece. New manufacturing techniques, such as additive manufacturing [1], have recently been developed for metal processing, machining is the most prevalent manufacturing operation in terms of volume and expenditure. It has been estimated that machining expenditure contributes to approximately 5% of the GDP in developed countries [2,3]. Via the improvement of the accuracy of the numerical simulations it will be the possibility to replace difficult, costly or even impossible experiments used for tool and process design. The modelling and simulation at the design stage can contribute to the shortening
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