Finite element simulation of semi-finishing turning of Electron Beam Melted Ti6Al4V under dry and cryogenic cooling

open6noIn the last few years, important step forwards have been made on Finite Element Simulation of machining operations. Wrought Ti6Al4V alloy has been deeply investigated both numerically and experimentally due to its wide application in the industry. Recently, Additive Manufacturing technologies as the Electron Beam Melting and the Direct Melting Laser Sintering are more and more employed in the production of biomedical and aeronautical components made of Ti6Al4V alloy. Fine acicular microstructures are generated by the application of additive manufacturing technologies, affecting the mechanical properties and the machinability. By the consequence, this peculiarity has to be considered in modelling the material behaviour. In this work, a numerical analysis of cylindrical external turning on Electron Beam Melted (EBM) Ti6Al4V alloy is presented. A Johnson-Cook constitutive equation was implemented as a flow stress model and adapted with respect to the wrought Ti6Al4V alloy. The model was calibrated and validated through the cutting forces and temperatures measurements acquired under dry and cryogenic lubricating conditions.openBordin, A; Imbrogno, S.; Rotella, G.; Bruschi, S.; Ghiotti, A.; Umbrello, D.Bordin, Alberto; Imbrogno, S.; Rotella, G.; Bruschi, Stefania; Ghiotti, Andrea; Umbrello, D

Modelling of material cutting with a material microstructure-level (MML) model

In this research work a material microstructure-level cutting model (MML cutting model) is presented. The crystal plasticity theory is adopted for modeling the cutting of the titanium alloy Ti–6Al–4V in orthogonal case. In this model, the grains of the studied material are explicitly presented, and their orientation angles and slip system strength anisotropy are considered as the main source of the microstructure heterogeneity in the cutting material. To obtain the material degradation process, the continuum self-consistent intragranular damage model and discrete cohesive zone inter-granular damage model, were developed, wherein the zero thickness cohesive element is implemented to simulate the bond between grain interfaces. This model was validated by a comparison with compression tests from literature. Results demonstrate the possibility to capture the influence of the microstructure on the material removal in terms of chip formation. Particularly, it is demonstrated that the grain orientation angle plays an important role for the chip segmentation and its periodicity during the cutting process

Drilling Process in γ-TiAl Intermetallic Alloys

Gamma titanium aluminides (gamma-TiAl) present an excellent behavior under high temperature conditions, being a feasible alternative to nickel-based superalloy components in the aeroengine sector. However, considered as a difficult to cut material, process cutting parameters require special study to guarantee component quality. In this work, a developed drilling mechanistic model is a useful tool in order to predict drilling force (Fz) and torque (Tc) for optimal drilling conditions. The model is a helping tool to select operational parameters for the material to cut by providing the programmer predicted drilling forces (Fz) and torque (Tc) values. This will allow the avoidance of operational parameters that will cause excessively high force and torque values that could damage quality. The model is validated for three types of Gamma-TiAl alloys. Integral hard metal end-drilling tools and different cutting parameters (feeds and cutting speeds) are tested for three different sized holes for each alloy.RTC-2014-1861-4, INNPACTO DESAFIO II. Spanish Governmen

Precision hard turning of ti6al4v using polycrystalline diamond inserts: Surface quality, cutting temperature and productivity in conventional and high-speed machining

This article presents the results of an experimental investigation into the machinability of Ti6Al4V alloy during hard turning, including both conventional and high-speed machining, using polycrystalline diamond (PCD) inserts. A central composite design of experiment procedure was followed to examine the efects of variable process parameters; feed rate, cutting speed and depth of cut (each at five levels) and their interaction efects on surface roughness and cutting temperature as process responses. The results revealed that cutting temperature increased with increasing cutting speed and decreasing feed rate in both conventional and high-speed machining. It was found that high speed machining showed an average increase in cutting temperature of 65% compared with conventional machining. Nevertheless, high speed machining showed better performance in terms of lower surface roughness despite using higher feed rates compared to conventional machining. High-speed machining of Ti6Al4V showed an improvement in surface roughness of 11% compared with conventional machining, with a 207% increase in metal removal rate (MRR) which offered the opportunity to increase productivity. Finally, an inverse relationship was verified between generated cutting temperature and surface roughness. This was attributed mainly to the high cutting temperature generated, softening, and decreasing strength of the material in the vicinity of the cutting zone which in turn enabled smoother machining and reduced surface roughness

DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al4V)

Temperature and surface roughness are important factors, which determine the degree of machinability and the performance of both the cutting tool and the work piece material. In this study, numerical models obtained from the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques were used for predicting the magnitude of the temperature and surface roughness during the machining operation of titanium alloy (Ti6Al4V). The design of the numerical experiment was carried out using the Response Surface Methodology (RSM) for the combination of the process parameters while the Artificial Neural Network (ANN) with 3 input layers, 10 sigmoid hidden neurons and 3 linear output neurons were employed for the prediction of the values of temperature. The ANN was iteratively trained using the Levenberg-Marquardt backpropagation algorithm. The physical experiments were carried out using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine with a maximum spindle speed of 18 000 rpm. A carbide-cutting insert (RCKT1204MO-PM S40T) was used for the machining operation. A professional infrared video thermometer with an LCD display and camera function (MT 696) with infrared temperature range of −50−1000 °C, was employed for the temperature measurement while the surface roughness of the work pieces were measured using the Mitutoyo SJ – 201, surface roughness machine. The results obtained indicate that there is high degree of agreement between the values of temperature and surface roughness measured from the physical experiments and the predicted values obtained using the ANN and RSM. This signifies that the developed RSM and ANN models are highly suitable for predictive purposes. This work can find application in the production and manufacturing industries especially for the control, optimization and process monitoring of process parameters

A numerical analysis of machining induced residual stresses of Grade 5 Titanium Alloy

In general most manufacturing techniques alter the surface integrity of the final component. Surface integrity refers to the surface properties and their influence on the functional performance of manufactured components1. Machining induced residual stress is a surface integrity descriptor that may have a significant influence on the mechanical behavior of metallic parts subjected to dynamic loads2. Most manufacturing processes introduce some form of residual stress to the material. Cutting or more specifically machining involves large plastic deformation and elevated temperatures that may induce significant residual stresses in the surface and near surface region. When turning steel these stresses are largely tensile in nature and extend to a depth of approximately 200 μm1

Effect of constitutive modeling during finite element analysis of machining-induced residual stresses in Ti6Al4V

Residual stress is an important surface integrity descriptor that may have a marked effect on the functional performance of machined alloy parts. This paper describes a finite element evaluation of the effect of different constitutive models on machining induced residual stresses for Ti6Al4V titanium alloy. A two dimensional orthogonal turning process is modelled and the results compared to experimental data. Residual stress is evaluated with respect to different elastic-viscoplastic constitutive models at certain cutting speeds and feeds. The general-purpose finite element code MSC Marc@ was used with comparisons with experimental data made relative to residual stress, cutting force and temperature. The magnitude and extent (depth) of the residual stress field is evaluated with regards to the different material models and compared with experimental data

Reduction of the mesh size influence on the results of a lagrangian finite element machining mode

Mesh dependence of the results of a finite element model are well known in many fields such as in structural design. This problem is however not much addressed in the literature for machining modelling although it is crucial for the quality of the results and the predictive aspect of the model. In this work, an orthogonal cutting model of the titanium alloy Ti6Al4V is exploited. The model formulation is Lagrangian and a damage criterion with eroding elements is used. A strong sensitivity of the results to the size of the elements is observed and the results do not converge when the size of the mesh decreases. To address this issue, a non-local damage criterion that reduces the mesh dependence of the results is introduced. The results show a strong decrease of their dependence to the size of the mesh. The recommendation is to use elements length that is not too far from the size of the grains of the material to avoid a dramatic increase of the computing time for very small elements and the absence of converged results for too large elements

The impact of process variables and wear characteristics on the cutting tool performance using Finite Element Analysis

The frequent failure of cutting tool in the cutting process may cause a huge loss of money and time especially for hard to machine materials such as titanium alloys. Thus this study is mainly focused on the impact of wear characteristics and process variables on the cutting tool which is ignored by most of researchers. A thermo-mechanical finite element model of orthogonal metal cutting with segment chip formation is presented. This model can be used to predict the process performance in the form of cutting force, temperature distribution and stress distribution as a function of process parameters. Ls-dyna is adopted as the finite element package due to its ability in solving dynamic problems. Ti-6Al-4V is the workpiece material due to its excellent physical property and very hard to machine. This thesis uses the Johnson-Cook constitutive model to represent the flow stress of workpiece material and the Johnson-Cook damage model to simulate the failure of the workpiece elements. The impacts of process variables and tool wear are investigated through changing the value of the variables and tool geometry. It is found that flank wear length has a linear relationship with the cutting force which is useful for predicting the cutting tool performance. Increasing the crater wear will in some degree diminishes the cutting force and temperature. A chip breakage will also happen in some cases of crater wear. Through these findings, the relationship between flank wear and cutting power is established which can be used as the guidance in the workshop for changing the tools. The distribution of temperature and stress on the cutting tool in different cutting conditions can be adopted to predict the most possible position forming cutting tool wear

Machining Simulation of Ti6Al4V under Dry and Cryogenic Conditions

Abstract Nowadays, numerical modeling is becoming a valuable and powerful tool for designing and optimizing the production process, as well as improving the machined components quality. Particularly, the Finite Element Method permits to increase the knowledge on the machinability of difficult-to-cut metals, such as the titanium alloys. The aim of this work is to develop a 3D FE model as a tool for predicting cutting forces, temperature, and machining-induced microstructural alterations during semi-finishing turning Ti6Al4 V under dry and cryogenic conditions. The numerical model is experimentally calibrated and validated