Helmi Attia

NUMERICAL AND EXPERIMENTAL INVESTIGATION OF LASER-ASSISTED MACHINING OF INCONEL 718

A numerical investigation of laser-assisted machining for Inconel 718 is presented. This study is based on a three-dimensional finite element model, which takes into account a new constitutive law of Inconel 718 as well as friction and heat transfer models at the tool-chip interface that are developed at the Aerospace Manufacturing Technology Centre (AMTC), of the National Research Council of Canada (NRC), Canada. The material flow stress is described as a function of the strain, the strain rate, and the temperature. The friction model accounts for the sticking and the sliding regions observed experimentally. The formulation of the heat transfer model is based on combining contact mechanics analysis with the solution of the thermal contact problem. The laser beam is modeled as a moving heat source, which is experimentally calibrated. To validate the three-dimensional finite element model, laser-assisted machining experiments were designed and carried out under different cutting conditions. The predicted cutting force and chip thickness are compared with the experimental results. The temperature, stress, strain, and strain rate fields in the primary deformation zone are investigated in order to reveal the plastic deformation process under laser-assisted machining operations.

CURRENT STATUS AND FUTURE DIRECTION IN THE NUMERICAL MODELING AND SIMULATION OF MACHINING PROCESSES: A CRITICAL LITERATURE REVIEW

This paper presents a literature review on modeling and simulation of the metal cutting process, with special consideration to difficult-to-cut materials. The critical issues in the modeling of the cutting process are presented and investigated, which include the identification and formulation of the material constitutive equation, as well as the models that describe the tribological and thermal interactions at the tool-chip interface. The available approaches for generating constitutive data are critically examined, and their advantages, capabilities and limitations are discussed. The formulation of the constitutive equation significantly affects the accuracy of the finite element (FE) simulation. The evaluation criteria proposed recently by the authors to assess the goodness of different constitutive relationships for the machining process are presented. It is shown that more accurate simulation can be obtained when using a pressure-dependent friction model, compared to that with uniform coefficients. Similar conclusion can be drawn in relation to expressing the thermal contact resistance (or conductance) as position dependent, being directly correlated to the local contact pressure at the interface. In addition, the current applications and future directions of the finite element modeling (FEM) of the metal cutting process are summarized.

Integrated Process of Laser-Assisted Machining and Laser Surface Heat Treatment

A process is proposed for integrating the laser-assisted machining (LAM) and laser surface heat treatment (LSHT) in a single operation. Experimental and numerical investigations were carried out. LSHT tests were performed to investigate the effect of the process parameters on the microstructure evolution and hardenability. A methodology and an empirical model for prediction of hardened depth were proposed. A two-dimensional finite element (2D-FE) model was developed to predict the phase transformation during the LAM and LSHT processes. The optimization of the LAM process was also investigated using the developed finite element model.

THERMAL CONSIDERATION OF THE DESIGN OF MULTILAYER COATED TOOLS FOR HIGH SPEED MACHINING

Quantitative assessment of the thermal role of multi-layer coating in cutting tools was approached through the analysis of mechanical contact problem at the tool–chip interface and the constriction resistance phenomenon. The micro-contact configuration on the surface asperity level (size and density of contact points, and surface approach) and the macro-contact configuration (contact pressure distribution and the size of the adhesion and sliding zones) were defined. The effect of multi-layer coating on stiffness of the contact interface was experimentally investigated and used to estimate effective flow stress of contacting solids. Thermal constriction model, based on the concept of heat flow channel, was developed. Using FE simulation, the correlation between the contact pressure and the thermal contact resistance of uncoated and multi-layer coated tools were established and validated. The thermal interaction and heat redistribution in the workpiece–chip-tool system was then examined for multi-layer coated tools in conventional and high speed machining. Analysis of the results showed that the tool coating causes the reduction of the heat flowing into the tool and the reduction of the maximum temperature rise. The thermal constriction model developed in this work provides a methodology for the design of coated tools based on thermal considerations.Copyright

Laser Assisted Finish Turning of Inconel 718: Process Optimization

Generally, superalloys have superior strength and toughness compared to conventional engineering material. However, while applications for such materials are growing, the improvement of their machinability has not been improved in parallel. Of particular interest to the aerospace industry, are nickel-based superalloys. Inconel 718, which is one type of nickel-based superalloy, is considered difficult-to-machine at room temperature due to the fact that it retains much of its strength at high temperatures. Conventional machining methods applied to these materials results in excessive tool wear and poor surface finish. One approach, which is becoming increasingly popular with difficult-to-machine materials, is laser assisted machining (LAM). This study assesses the effect of LAM on the machinability of Inconel 718 using a triple-layer coated carbide tool in terms of cutting forces, tool wear and surface finish. A focused Nd:YAG laser beam was used as a localized heat source to thermally soften the workpiece prior to material removal. Finishing operations were assumed throughout the experiments. Cutting tests were performed over a wide range of cutting speeds (ranging from 100 to 500 m/min) and feeds (ranging from 0.125 to 0.500 mm/rev) to determine the optimum cutting speed and feed for each tool material. Results showed a significant drop in all three components of cutting force when thermal softening caused by the laser power was in effect. A two to three fold improvement was observed in terms of surface finish and tool wear under LAM conditions when compared to conventional machining.Copyright

Optimization of Cutting Conditions in Vibration Assisted Drilling of Composites via a Multi-Objective EGO Implementation

A recent and promising technique to overcome the challenges of conventional drilling is vibration-assisted drilling (VAD) whereby a controlled harmonic motion is superimposed over the principal drilling feed motion in order to create an intermittent cutting state. Two additional variables other than the feed and the speed are introduced, namely the frequency and the amplitude of the imposed vibrations. Optimum selection of cutting conditions in VAD operations of composite materials is a challenging task due to several reasons; such as the increase in the number of controllable variables, the need for costly experimentation, and the limitation on the number of experiments that can be performed before tool degradation becomes an issue in the reliability of measurements. Additionally, there are often several objectives to consider, some of which may be conflicting, while others may be somewhat correlated. Pareto-optimality analysis is needed for conflicting objectives; however the existence of several objectives (high-dimension Pareto space) makes the generation and interpretation of Pareto solutions difficult. An attractive approach to the optimization task is thus to employ Kriging meta-models in a multi-objective efficient global optimization (m-EGO) framework for incremental experimentation of optimal setting of the cutting parameters. Additional challenge posed by constraints on machine capabilities is accounted for through domain transformation of the design variables prior to the construction of the Kriging models. Study results using a baseline exhaustive experimental data shows opportunity for employing m-EGO for the generation of well distributed Pareto-frontiers with fewer experiments.Copyright

Multi-Objective Selection of Cutting Conditions in Advanced Machining Processes via an Efficient Global Optimization Approach

Optimum selection of cutting conditions in high-speed and ultra-precision machining processes often poses a challenging task due to several reasons; such as the need for costly experimental setup and the limitation on the number of experiments that can be performed before tool degradation starts becoming a source of noise in the readings. Moreover, oftentimes there are several objectives to consider, some of which may be conflicting, while others may be somewhat correlated. Pareto-optimality analysis is needed for conflicting objectives; however the existence of several objectives (high-dimension Pareto space) makes the generation and interpretation of Pareto solutions difficult. The approach adopted in this paper is a modified multi-objective efficient global optimization (m-EGO). In m-EGO, sample data points from experiments are used to construct Kriging meta-models, which act as predictors for the performance objectives. Evolutionary multi-objective optimization is then conducted to spread a population of new candidate experiments towards the zones of search space that are predicted by the Kriging models to have favorable performance, as well as zones that are under-explored. New experiments are then used to update the Kriging models, and the process is repeated until termination criteria are met. Handling a large number of objectives is improved via a special selection operator based on principle component analysis (PCA) within the evolutionary optimization. PCA is used to automatically detect correlations among objectives and perform the selection within a reduced space in order to achieve a better distribution of experimental sample points on the Pareto frontier. Case studies show favorable results in ultra-precision diamond turning of Aluminum alloy as well as high-speed drilling of woven composites.Copyright

Characterisation and optimisation of minimum quantity lubrication in milling of Ti-6Al-4V alloy using phase Doppler anemometry (PDA)

The main objective of this work is to understand the effect of the MQL parameters; namely, oil flow rate, air flow rate and nozzle distance from the cutting zone, on the flow characteristics in order to optimise the cooling and lubrication capacities of the jet for machining applications. Flow visualisation experiments were performed for different air and oil flow rates and distances from the nozzle using phase Doppler anemometry (PDA). The visualisation results, such as, the droplet size and velocity vector were used to identify the optimum MQL conditions to achieve the desired flow characteristics for machining applications. It was found that a spray with high air flow rate and high oil flow rate would give an axial, symmetrical, coherent, and undisturbed spray, which is characterised by small droplet size and high velocity. This spray is optimum for machining due to its ability for better penetration and cooling effect in the cutting zone. Milling tests were performed on Ti-6Al-4V alloy to validate the effect of MQL parameters on the machining performance, in terms of cutting forces, surface roughness and tool temperature.

Optimization of the Cutting Conditions for High Speed Drilling of Woven Composites

The present work proposes a new algorithm for the optimization of cutting parameters in the high speed drilling of woven composites. The cutting parameters under consideration are the feed rate and the spindle speed. Three performance parameters are to be minimized. These are the exit delamination, the surface roughness and the thrust force. These performance parameters are observed experimentally. One of the challenges that face the experimental testing of these parameters is the high cost of the drilling tools and specimen materials. Therefore, the minimization of the number of experimental tests is a necessary requirement. The algorithm presented hybridizes Kriging as a meta-modeling technique with evolutionary multi-objective optimization to optimize the cutting parameters while intelligently selecting the new set of cutting parameters in each iteration. After starting with a factorial design of the search space, and after testing the performance criteria at these points, the algorithm fits a multi-dimensional surface using Kriging. This step is followed by an evolutionary search on the fitted model. The search spreads a population of search points in the direction of better performance criteria as well as in the direction of un-sampled space. The previous two steps are conducted iteratively for a pre-defined number of iterations. In the final iteration, the population of search points is clustered to yield a small number of new points at which the new experiments will be conducted. The whole process is iterated until the maximum number of allowable experiments is achieved. The algorithm is tested using an existing set of previously published experimental data that are dense enough to predict the actual response surface of the performance criteria. Results showed that the algorithm smartly moved into the direction of higher performance criteria with a low number of experimental trials.Copyright

An Integrated Approach for the Predictions of the Workpiece Vibrations During Machining of Aerospace Structure: Numerical and Experimental Validation

Accurate predictions of the workpiece vibrations during high speed machining of aerospace structural components is a critical issue since it affects the accuracy of the final part. For fixture design purposes, and for force predictions, the computational efficiency of the dynamic models predicting the workpiece vibrations is a crucial factor since it affects the cycle time for the design and optimization of the fixtures. Most of the available dynamic models are based on computationally prohibitive techniques, such as finite element analysis. In this work, an integrated approach, based on recently developed semi-analytical models, is presented for the analysis of the effect of the fixture layout on the dynamics of thin-walled structures while taking into account the continuous change of thickness of the workpiece, and the effect of rigid and deformable fixture supports. The developed approach is based on plate models with holonomic constraints and finite stiffness springs. This approach, together with all the developed models and formulations are validated numerically for different workpiece geometries and various types of loading. An experimental study has been performed to validate this approach through the machining of thin-walled components. It was found that this approach led to prediction errors within 10% and more than 20 times reduction in the computation time. The challenge of filtering the effect of the dynamics of the force measurement system from the measured signals was overcome by developing a new hybrid semi-analytical methodology for accurate measurement of the machining forces.Copyright