Evaluation of performance of nanofluid using multiwalled carbon nanotubes for machining of Ti–6AL–4V

Machining of titanium alloys generate very high temperature in the cutting zone. This results in rapid tool wear and poor surface properties. Therefore, improvement in cutting performance in machining of titanium alloys is very much dependent on effectiveness of the cooling strategies applied. In the present work, performance of nanofluid using multiwalled carbon nanotubes (MWCNTs) dispersed in distilled water and sodium dodecyl sulfate (SDS) as surfactant is evaluated for turning operation on Ti–6Al–4V workpieces. Turning operations were carried out under three different conditions – dry, with conventional cutting fluid and with nanofluid. Nanofluid application was limited to 1 L/h and it was applied at the tool tip through gravity feed. Various machining responses like cutting force, surface finish and tool wear were analyzed while turning at optimum cutting parameters as 150 m/min, 0.1 mm/rev and 1 mm depth of cut. Later on, machining performance of nanofluid is confirmed at low cutting speed of 90 m/min. Nanofluid outperformed conventional cutting fluid with 34% reduction in tool wear, average 28% drop in cutting forces and 7% decrease in surface roughness at cutting speed of 150 m/min.     

Parameter optimization and mechanism of laser–arc hybrid welding of dissimilar Al alloy and stainless steel

Laser–cold metal transfer arc hybrid welding of 6061 Al alloy and AISI304 stainless steel (304SS) was carried out. Bead morphologies and intermetallic compound (IMC) layer characterizations of the joints were studied in detail. The optimal parameter range for accepted bead appearances (OPRBA) without surface and interface defects was obtained, and the growth mechanism of the IMC layer was summarized. The results showed that the nonuniformity in the thickness and shape along the fusion zone/304SS interface from the top surface to the bottom increases with increasing heat input and is more sensitive to laser power because the interface temperature is dominated by a high-temperature laser keyhole throughout the molten pool. As the welding parameters are within the OPRBA and the heat input is within the range of 80–110 J/mm, the joints are stronger than 130 MPa and the corresponding IMC layer thickness is at the range of 3–6.5 μm. The kinetic analysis showed that a controlling interface temperature no more than 1,120 °C may limit the growth of the IMC layer.     

Multiple quality optimization in laser cutting of difficult-to-laser-cut material using grey–fuzzy methodology

This paper investigates the laser cutting performance of 1 mm Duralumin sheet with the aim to improve quality of cut by simultaneously optimising multiple performances such as cut edge surface roughness, kerf taper and kerf width. The experimental data obtained by Taguchi methodology-based L₂₇ orthogonal array experimentation have been used in the hybrid approach optimization of grey relational analysis and fuzzy logic theory. The predicted optimum results have been verified by conducting confirmation experiments. The verification results show an overall improvement of 19 % in multiple quality characteristics. The effects of significant factors on quality characteristics have also been discussed.     

Experimental investigation and optimization of EDM process parameters for machining of aluminum boron carbide (Al–B4C) composite

This study investigates the effect of electric discharge machining (EDM) process parameters [current, pulse-on time (T_on), pulse-off time (T_off) and electrode material] on material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) during machining of aluminum boron carbide (Al–B₄C) composite. This article also summarizes a brief literature review related to aluminum metal matrix composites (Al-MMCs) based on different process and response parameters, work and tool material along with their sizes, dielectric fluid and different optimization techniques used. The MMC used in the present work is stir casted using 5% (wt) B₄C particles of 50 micron size in Al 6061 metal matrix. Taguchi technique is used for the design of experiments (L₉-orthogonal array), while the experimental results are analyzed using analysis of variance (ANOVA). Response table for average value of MRR, EWR and SR shows that current is the most significant factor for MRR and SR, while electrode material is most important for EWR. ANOVA also confirms similar results. It is also observed that the optimum level of process parameters for maximum MRR is A₃B₁C₃D₃, for minimum EWR is A₁B₂C₃D₁, and for SR is A₁B₃C₃D₃.     

Machine–part cell formation using a hybrid particle swarm optimization

Cell formation (CF) is a key step in group technology (GT). This combinatorial optimization problem is NP-complete. So, meta-heuristic algorithms have been extensively adopted to efficiently solve the CF problem. Particle swarm optimization (PSO) is a modern evolutionary computation technique based on a population mechanism. Since Kennedy and Eberhart invented the PSO, the challenge has been to employ the algorithm to different problem areas other than those that the inventors originally focused on. This paper investigates the first applications of this emerging novel optimization algorithm into the CF problem, and a newly developed PSO-based optimization algorithm for it is elaborated. Forming manufacturing cells lead to process each part family within a machine group with reduction intracellular travel of parts and setup time. A maximum number of machines in a cell and the maximum number of cells are imposed. Some published results in various problem sizes have been used as benchmarks to assess the proposed algorithm. Overall, the advantages of the proposed PSO are that it is rapidly converging towards an optimum, there are fewer parameters to adjust, it is simple to compute, it is easy to implement, it is free from the complex computation, and it is very efficient to use in CF with a wide variety of machine/part matrices.     

Application of response surface method on machining of Al–SiC nano-composites

The newly fabricated metal matrix nano-composite (MMNC) of Al 7075 reinforced with 1.5 wt% SiC nano-particles was prepared by a novel ultrasonic cavitation method. The high resolution scanning electron micrograph (SEM) and field emission scanning electron micrograph (FESEM) shows uniform distribution and good dispersion of the SiC nanoparticles within the aluminum metal matrix. Electrical discharge machining (EDM) was employed to machine MMNC with copper electrode by adopting face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions. Further a mathematical model has been formulated in order to estimate the machining characteristics. It has been observed that pulse current was found to be the most important factor affecting all the three output parameters such as material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR). The optimum parameter of combination setting has been identified for the MMNC are voltage 50.00 V, pulse current 8.00 A, Pulse on time 8.00 μs and pulse off time 9.00 μs. Finally the parameters were optimized for maximizing MRR, minimizing EWR and SR using desirability function approach.     

A study on micro machining of e-glass–fibre–epoxy composite by ECSM process

The paper presents the result of an experimental investigation on the micro machining of electrically non-conductive e-glass–fibre–epoxy composite during electrochemical spark machining using specially designed square cross section with centrally micro hole brass tool and different diameter round-shaped micro tools made of IS-3748 steel. A micro electrochemical spark machining (ECSM) setup has been designed, fabricated and used for conducting the experiments. According to the Taguchi method-based design, the specific numbers of experiments have been carried out to investigate the influence of the fabricated ECSM parameters on the material removal rate and overcut on generated hole radius. Test results show that the material removal rate is maximum when machining was performed at higher setting value of D.C. supply voltage (e.g. 70?V), moderate setting value of electrolytic concentration (e.g. 80?g/l) and 180-mm gap between electrodes. Taking significant machining parameters into consideration and using multiple linear regression, mathematical modes for material removal rate and overcut on hole radius are established to investigate the influence of cutting parameters during micro-ECSM. The influence of machining parameters on machined hole and special shape contour quality are also analysed through different scanning electron micrographs. Confirmation test results established the fact that the developed mathematical models are appropriate for effectively representing the machining performance criteria.     

Parameter estimation of lithium-ion batteries and noise reduction using an H∞ filter

Lithium-ion batteries are widely used in conventional hybrid vehicles and in some electrical devices. A lumped parameter model of lithium-ion battery is constructed and system parameters are identified by using the autoregressive moving average (ARMA) and a genetic algorithm (GA). The precise information of state-of-charge (SOC) and terminal voltage are required to prolong the battery life and to increase the battery performance, reliability, and economics. By assuming a priori knowledge of the process and measurement noise covariance values, Kalman filter or extended Kalman filter has been used to estimate the SOC and terminal voltage. However, the main drawbacks of the Kalman filter is to use correct a priori covariance values, otherwise, the estimation errors can be lager or even divergent. These estimation errors can be relaxed by using the H_∞ filter, which does not make any assumptions about the noise, and it minimizes the worst case estimation error. In this paper, H_∞ filter is used to estimate the SOC and terminal voltage. The H_∞ filter can reduce SOC estimation error, making it more reliable than using a priori process and measurement noise covariance values.     

Determining the energy distribution during electric discharge machining of Ti–6Al–4V

The titanium (Ti) alloys are the notoriously “difficult-to-machine” aerospace materials. Compared with the traditional mechanical cutting methods which are costly because of high tooling costs, electrodischarge machining (EDM) is an effective machining method for the Ti alloys. The energy distribution during the EDM process of Ti alloys was rarely reported, though it is a very important factor that can affect the machining performance. In this work, the energy distribution during EDM of Ti–6Al–4V has been investigated by a novel method, at different EDM parameters including interelectrode distance, pulse duration, polarity, and electrode shape. The results of this work show that energy distribution characteristics are greatly affected by the power density applied on the electrodes and more energy is distributed into the anode than into the cathode, which are in good concurrence with the results obtained by other authors. The results of this work will be helpful for further improving the technological performance of this process.     

Numerical simulation of the system “fixture–workpiece” for lever machining

In this article, the new configuration of fixture was proposed for ensuring the sufficient tool accessibility, which allows carrying out multiaxis machining of levers in one setup. The research based on numerical simulation was confirmed that the proposed fixture corresponds to all the accuracy parameters. Workpieces from steel, cast iron and aluminium alloy were investigated within the simulation. The values of displacements and stresses occurring during machining are less for proposed fixture in comparison with the existing fixtures that was confirmed by the deflected mode analysis. The modal analysis proved that the proposed fixture has much higher value of eigenfrequency than the other fixtures. To optimize the machining, the dependences for displacements and stresses on the cutting depth were determined. Oscillations of the system “fixture–workpiece” during machining were investigated for various manufacturing steps of levers machining of the fixtures from different fixture systems. The results of harmonic analysis showed that the dynamic stiffness of the proposed fixture was higher than that for the dedicated and modular fixtures. The oscillation amplitudes in the places of machined surfaces in the proposed fixture do not exceed the tolerance requirements for lever manufacturing.     

Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT–SVD

This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques.     

Combined rough and finish machining of Ti–6Al–4V alloy by electrochemical mill-grinding

Abstract

This study proposes a combined method for the electrochemical mill-grinding of Ti–6Al–4V alloy to achieve a high material removal rate, high machining accuracy and good surface quality based on rough and finish machining. In the rough machining stage, a maximum feed rate of 2.7?mm min^?1 and a material removal rate of 248.3?mm³ min^?1 were achieved experimentally at a 10?mm cut depth using an abrasive tool with five rows of tool-sidewall outlet holes. In the finish machining stage, there were almost no overcuts or stray corrosions produced. The sidewall surface roughness and sidewall flatness were Ra = 1.06 and 76.8?μm after the finishing stage, which represent a 68% and 79.2% improvement compared with the rough machining stage, respectively. Finally, we fabricated a 1-mm-thick thin-walled structure using the combined machining operations, in which approximately 96% of the total material removal volume was performed at the rough machining stage.     

Optimizing the geometric parameters of chamfered edge for rough machining Fe–Cr–Ni stainless steel

Geometry of cutting edge has great influence on performance and reliability of modern precision cutting tools. In this study, two-dimensional finite element model of orthogonal cutting of Fe–Cr–Ni stainless steel has been built to optimize the geometric parameters of chamfered edge. A method to measure the chip curl radius has been proposed. The effect of cutting edge geometric parameters on tool stress and chip curl radius has been analyzed. Then, the chamfered edge parameters have been optimized based on numerical simulation results. It finds that, keeping the equal material removal rate, the optimal geometric parameters of chamfered edge for rough machining Fe–Cr–Ni stainless steel are that the rake angle is from 16° to 17°, and the chamfer length is from 60 to 70 μm. Small (large) rake angle combined with small (large) chamfer length is more reasonable to reduce the tool stress. When the length of land is approximately equal to undeformed chip thickness and the rake angle is larger than 15°, the chip curl radius is minimal. The groove type with large radio of width to depth should be used in the chip breaking based on the optimization results.     

Mapping of mechanical properties of WC–Co using nanoindentation

High-resolution measurements of mechanical properties are of immense importance in metallurgy. Measuring the intrinsic properties of each phase separately in multiphase materials gives information that is valuable for the development of new materials and for modelling. In this work, nanoindentation has been used to reveal mechanical properties of different phases in WC–Co with very high resolution. The resolution limits of the equipment and this material as well as various techniques to accomplish the measurements were evaluated. By making indents only 0.1 μm apart and using very low loads (1 mN) it was possible to distinguish between the two different phases, WC and Co. Maps created from the measured properties, hardness and Young’s modulus, were in excellent agreement with SEM images of the same area. Furthermore, it was also possible to detect an increased hardness of the Co binder phase by a factor of four as compared to the bulk hardness of Co. This work verifies experimentally what several authors have proposed earlier based on modelling. This revised version was published online in August 2006 with corrections to the Cover Date.     

Prediction of friction and heat flow in machining incorporating thermophysical properties of the coating–chip interface

This paper deals with an experimental and analytical investigation into the thermodynamically activated effects influencing the behaviour of the multi-layered coated tool rake face during orthogonal cutting of ferromagnetic and paramagnetic steels. Temperature measurements on the tool rake face using a thermocouple-based technique and identification of the contact zone by means of computer image processing were carried out. New methodology for assessing friction and the amount of thermal energy generated when machining with a coated tool insert with natural and restricted contact coupled with a metallic chip, using thermophysical properties of the sliding materials is developed in this study. The dependence of the material properties on the contact temperature makes the predictive models more realistic. It was proven, based on the heat flux analysis, that the use of advanced coatings with an intermediate Al₂O₃ layer could substantially improve the heat flow into the chip at distinctly lower temperatures than other commercially available coatings. The data obtained can be used for the optimisation of tool selection with respect to friction and heat transfer and for maintaining the recommended contact temperature.     

Optimization of the EDM parameters on machining Ti–6Al–4V with multiple quality characteristics

In this paper, parameter optimization of the electrical discharge machining process to Ti–6Al–4V alloy considering multiple performance characteristics using the Taguchi method and grey relational analysis is reported. Performance characteristics including the electrode wear ratio, material removal rate and surface roughness are chosen to evaluate the machining effects. The process parameters selected in this study are discharge current, open voltage, pulse duration and duty factor. Experiments based on the appropriate orthogonal array are conducted first. The normalised experimental results of the performance characteristics are then introduced to calculate the coefficient and grades according to grey relational analysis. The optimised process parameters simultaneously leading to a lower electrode wear ratio, higher material removal rate and better surface roughness are then verified through a confirmation experiment. The validation experiments show an improved electrode wear ratio of 15%, material removal rate of 12% and surface roughness of 19% when the Taguchi method and grey relational analysis are used.