Radial-mode abrasive waterjet turning of short carbon–fiber-reinforced plastics

An experimental study is carried out for single-pass radial-mode abrasive waterjet (AWJ) turning of a short carbon–fiber-reinforced polyetheretherketone (PEEK) specimen to understand the machining process and the effects of major process variables (feed speed, water pressure, abrasive mass flow rate, nozzle tilt angle, and rotational surface speed) on the major machining performance measures, that is, the depth of cut, material removal rate (MRR) and surface roughness. It is found that high water pressure, normal nozzle impact angle and high rotational speed with suitably selected feed speed and abrasive flow rate may be selected to achieve a high MRR without significantly compromising the surface roughness. Mathematical models for the three cutting performance measures are then developed for use in process control.     

Modelling and analysis of hybrid electrochemical turning-magnetic abrasive finishing of 6061 Al/Al2O3 composite

This paper integrates the electrochemical turning (ECT) process and magnetic abrasive finishing (MAF) to produce a combined process that improves the material removal rate (MRR) and reduces surface roughness (SR). The present study emphasizes the features of the development of comprehensive mathematical models based on response surface methodology (RSM) for correlating the interactive and higher-order influences of major machining parameters, i.e. magnetic flux density, applied voltage, tool feed rate and workpiece rotational speed on MRR and SR of 6061 Al/Al₂O₃ (10% wt) composite. The paper also highlights the various test results that also confirm the validity and correctness of the established mathematical models for in-depth analysis of the effects of hybrid ECT- MAF process parameters on metal removal rate and surface roughness. Further, optimal combination of these parameters has been evaluated and it can be used in order to maximize MRR and minimize SR. The results demonstrate that assisting ECT with MAF leads to an increase machining efficiency and resultant surface quality significantly, as compared to that achieved with the traditional ECT of some 147.6% and 33%, respectively.     

基于响应曲面法的YG8硬质合金刀片化学机械抛光工艺参数优化

为了快速确定YG8前刀面抛光的最佳工艺参数,提高加工效率和精度,利用响应曲面法对YG8硬质合金刀片抛光工艺进行优化试验研究。通过单因素试验确定抛光转速、抛光压力、磨粒粒径和磨粒浓度的水平,并对4个工艺参数进行中心复合设计试验。建立了材料去除率RMR和表面粗糙度Ra的预测模型,基于响应曲面法优化工艺参数获得最佳工艺参数为抛光转速65.5 r/min、抛光压力156.7 kPa、磨粒粒径1.1 μm、磨粒浓度14%,此时得到了最小表面粗糙度预测值Ra=0.019 μm,材料去除率RMR=56.6 nm/min。试验结果表明,基于响应曲面法的材料去除率与表面粗糙度预测模型准确有效。     

Fabrication of stepped hole on zirconia bioceramics by ultrasonic machining

Zirconia (ZrO₂) is a highly biocompatible ceramic material providing fracture strength properties that allow application as dental implants in biomedical engineering. In this present research, experimental analysis has been made for generating stepped hole on zirconia bioceramics with desired quality using ultrasonic machining (USM) process. Four independent controllable input process parameters are abrasive grain diameter, power rating, concentration of abrasive slurry, and tool feed rate. Material removal rate (MRR), overcut of larger diameter (OLD) hole, and overcut of smaller diameter (OSD) hole of stepped hole are considered as the responses. Response surface methodology (RSM) is used for modeling the performance of USM process. Multiobjective optimization has been performed to maximize the MRR and minimize the OLD hole and OSD hole of stepped holes. All the responses are improved at the optimal parametric condition and verified by confirmation test. The present research opens up the application feasibility of USM process for stepped hole generation on bioceramics and its utilization in biomedical field.     

Vibration emission as a potential source of information for abrasive waterjet quality process control

The paper deals with basic research of vibration generated at abrasive waterjet cutting of materials and their analysis of frequency spectrum in the plane cut. As an experimental material, stainless steel AISI 309 has been used. Experimentally controlled factor involved in the experiment was abrasive mass flow rate with values m _a ?=?250 and 400 g min^?1 at a constant traverse speed v?=?100 mm min^?1. The vibrations were recorded during experimental cutting by sensors PCB IMI type 607A11 placed on experimental material along the cut at a distance of 50 mm from the cutting plane. Data collection was carried by NI PXI measurement system and frequency analyzer Microlog GX-S. Signal was evaluated by virtual instrument created in the object-programming environment LabView 8.5. Various sizes of amplitudes were observed depending on the distance of abrasive waterjet cutting process from the beginning of the cut. Two peaks of frequency bands have been also found: the first between 500 and 600 Hz and the other at approximately 12.5 kHz. Using this method is possible to ensure the determination of technology efficiency of the material removal process.     

Machinability investigation in hard turning of AISI D3 cold work steel with ceramic tool using response surface methodology

The hard turning process has been attracting interest in different industrial sectors for finishing operations of hard materials. In this paper, the effects of cutting speed, feed rate, and depth of cut on surface roughness, cutting force, specific cutting force, and power in the hard turning were experimentally investigated. An experimental investigation was carried out using ceramic cutting tools, composed approximately with (70 %) of Al₂O₃ and (30 %) of TiC, in surface finish operations on cold work tool steel AISI D3 heat-treated to a hardness of 60 HRC. Based on 3³ full factorial designs, a total of 27 tests were carried out. The range of each parameter is set at three different levels, namely, low, medium, and high. Analysis of variance is used to check the validity of the model. Experimental observations show that higher cutting forces are required for machining harder work material. This cutting force gets affected mostly by feed rate followed by depth of cut. Feed rate is the most influencing factor on surface roughness. Feed rate followed by depth of cut become the most influencing factors on power; especially in case of harder workpiece. Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach. It was found that, the use of lower depth of cut value, higher cutting speed, and by limiting the feed rate to 0.12 and 0.13 mm/rev, while hard turning of AISI D3 hardened steel, respectively, ensures minimum cutting forces and better surface roughness. Higher values of depth of cut are necessary to minimize the specific cutting force.     

Experimental investigation on the electrochemical machining of 00Cr12Ni9Mo4Cu2 material and multi-objective parameters optimization

Special stainless steel 00Cr12Ni9Mo4Cu2 has multiple composition and inhomogeneous tissues; short circuiting will frequently occur when using conventional electrolyte processing. This article analyzes the reason why the process of machining is difficult from the material composition and structure. We used the NaNO₃ and NaClO₃ electrolyte composite to select the appropriate concentration, and then by using the orthogonal experiment and gray relational analysis method, we discussed how the voltage, feed speed, and electrolyte pressure solved the problem of the material removal rate (MRR), surface roughness (SR), and side gap. Under optimal conditions of 20 V, an electrolyte composite concentration of 178 g/l NaNO₃ and 41 g/l NaClO₃, a feed rate of 0.7 mm/min, and an electrolyte pressure of 0.8 MPa, a material removal rate of 100.8 mm3/min, a surface roughness of Ra 0.8 μm, and a side gap of 0.16 mm were produced. Given the same voltage, with an increasing cathode feed rate, the MRR was shown to increase while the surface roughness value and the side gap decreased. Under the same cathode feed rate, the MRR decreases, while the side gap and the surface roughness increase as the electrochemical machining application voltage increases. This study proves that using a certain concentration of electrolyte composite is a simple, low-cost, and feasible approach in improving efficiency and quality.     

On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations

This research work concerns the elaboration of a surface roughness model in the case of hard turning by exploiting the response surface methodology (RSM). The main input parameters of this model are the cutting parameters such as cutting speed, feed rate, depth of cut and tool vibration in radial and in main cutting force directions. The machined material tested is the 42CrMo4 hardened steel by Al₂O₃/TiC mixed ceramic cutting tool under different conditions. The model is able to predict surface roughness of Ra and Rt using an experimental data when machining steels. The combined effects of cutting parameters and tool vibration on surface roughness were investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of cutting parameters and tool vibration with respect to announced objectives which are the prediction of surface roughness. The adequacy of the model was verified when plotting the residuals values. The results indicate that the feed rate is the dominant factor affecting the surface roughness, whereas vibrations on both pre-cited directions have a low effect on it. Moreover, a good agreement was observed between the predicted and the experimental surface roughness. Optimal cutting condition and tool vibrations leading to the minimum surface roughness were highlighted.     

Strength modeling and optimizing ultrasonic welded parts of ABS-PMMA using artificial intelligence methods

This study analyzes variations in metal removal rate (MRR) and quality performance of roughness average (R _a) and corner deviation (CD) depending on parameters of wire electrical discharge machining (WEDM) process in relation to the cutting of pure tungsten profiles. A hybrid method including response surface methodology (RSM) and back-propagation neural network (BPNN) integrated simulated annealing algorithm (SAA) were proposed to determine an optimal parameter setting. The results of 18 experimental runs via a Taguchi orthogonal table were utilized to train the BPNN to predict the MRR, R _a, and CD properties. Simultaneously, RSM and SAA approaches were individually applied to search for an optimal setting. In addition, analysis of variance was implemented to identify significant factors for the processing parameters. Furthermore, the field-emission scanning electron microscope images show that a lot of built-edge layers were presented on the finishing surface after the WEDM process. Finally, the optimized result of BPNN with integrated SAA was compared with that obtained by an RSM approach. Comparisons of the results of the algorithms and confirmation experiments show that both RSM and BPNN/SAA methods are effective tools for the optimization of parameters in WEDM process.     

Multiple-response optimization for micro-endmilling process using response surface methodology

In the present trend, new fabrication methods for producing miniaturized components are gaining popularity due to the recent advancements in micro-electro mechanical systems. Micro-machining differs from the traditional machining with the small size tool, resolution of x?Cy and z stages. This paper focuses RSM for the multiple response optimization in micro-endmilling operation to achieve maximum metal removal rate (MRR) and minimum surface roughness. In this work, second-order quadratic models were developed for MRR and surface roughness, considering the spindle speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models were used for multiple-response optimization by desirability function approach to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in good agreement with the predicted values.     

Comparative assessment of wiper and conventional ceramic tools on surface roughness in hard turning AISI 4140 steel

This study considers the comparison between the surface roughness criteria (Ra, Rz and Rt) of the wiper inserts with conventional inserts during hard turning of AISI 4140 hardened steel (60 HRC).The planning of experiments was based on Taguchi’s L₂₇ orthogonal array. The response surface methodology (RSM) and analysis of variance (ANOVA) were used to check the validity of quadratic regression model and to determine the significant parameter affecting the surface roughness. The statistical analysis reveals that the feed rate and depth of cut have significant effects in reducing the surface roughness. The optimum machining conditions to produce the best possible surface roughness in the range of this experiment under these experimental conditions searched using desirability function approach for multiple response factors optimization. The results indicate that the surface quality obtained with the wiper ceramic insert significantly improved when compared with conventional ceramic insert is 2.5. Roughness measurements reveal a dependence on CC6050WH tool wear. However, although the wear rises up to the allowable flank wear of value 0.3 mm, roughness Ra did not exceeded 0.9 μm.     

Using the acoustic sound pressure level for quality prediction of surfaces created by abrasive waterjet

The paper deals with an innovative way of cutting materials by abrasive waterjet with a view to increase its quality. In the research work, we were concerned with the search for a relationship between surface roughness and noise in the abrasive waterjet cutting process. Innovation lies in the use of negative characteristic of the technology—noise, which is a carrier of information about the quality of cutting process. In this way, the noise can be positively used in the on-line control of the technological process. The final result is a project for control of the process of abrasive waterjet cutting of materials by means of feedback according to the on-line measurement of acoustic pressure level L _aeq (dB). Instantaneous information about the state of cut according to the instantaneous value of L _aeq amplitude allows the automatic regulation of traverse speed of cutting head v _p (mm.min^?1), which is, together with the pressure p (MPa), one of the most important technological factors of control of production technology from the point of view of economic indicators and qualitative indicators of a semiproduct. The proposed model has been experimentally verified and was simulated in Matlab.     

Optimization of the chemical mechanical polishing process for optical silicon substrates

Chemical mechanical polishing (CMP) experiments are performed to study the effects of four key process factors on the flatness and surface finish of the polished optical silicon substrates and on the material removal rate (MRR). The experimental results and analyses reveal that the pad rotational speed and polish pressure have significant effects on the MRR, the interaction of the polish head rotational speed and slurry supply velocity and the interaction of the polish pressure and polish head rotational speed have significant effects on the flatness, and the pad rotational speed has a significant effect on the surface roughness R _t of the optical silicon substrates polished. The optimal combination of the four factors investigated is a polish pressure of 9,800 Pa, a pad rotational speed of 20 rpm, a polish head rotational speed of 20 rpm, and a slurry supply velocity of 100 ml/min. A confirmation CMP experiment has been carried out using the optimal process parameter setting obtained from the design of experiments analyses. The goal to attain optical silicon substrates with nanometric surface roughness and micrometric flatness by an optimized CMP process with a high MRR simultaneously so as to reduce the polishing time to only 15 min from over 8 h has been achieved.     

Effect of the process parameters on the three-dimensional shape of molten pool during full-penetration laser welding process

Slow tool servo (STS) turning is superior in machining precision and in complicated surface. However, STS turning is a complex process in which many variables can affect the desired results. This paper focuses on surface roughness prediction in lenses STS turning. An exponential model, based on the five main cutting parameters including tool nose radius, feed rate, depth of cut, C-axis speed, and discretization angle, for surface roughness prediction of lenses is developed by means of orthogonal experiment regression analysis. Meanwhile, a prediction model of surface roughness based on least squares support vector machines (LS-SVM) with radial basis function is constructed. Orthogonal experiment swatches are studied, and chaotic particle swarm optimization and leave-one-out cross-validation are applied to determine the model parameters. The comparison of LS-SVM model and exponential model is also carried out. Predictive LS-SVM model is found to be capable of better predictions for surface roughness and has absolute fraction of variance R² of 0.99887, the mean absolute percent error e_M of 8.96 %, and the root mean square error e_R of 10.68 %. The experimental results and prediction of LS-SVM model show that effects of tool nose radius and feed rate are more significant than that of depth of cut on surface roughness of lenses turning.     

A dual response surface-desirability approach to process modeling and optimization of Al2O3 powder-mixed electrical discharge machining (PMEDM) parameters

This paper presents an effort to model and optimize the process parameters involved in powder-mixed electrical discharge machining (PMEDM). Aluminum oxide (Al₂O₃) fine abrasive powders with particle concentration and size of 2.5–2.8 g/L and 45–50 μm, respectively, were added into the kerosene dielectric liquid of a die-sinking electrical discharge machine. The experiments were carried out in planing mode on a specially designed experimental set up developed in laboratory. The CK45 heat-treated die steel and commercial copper was used as work piece and tool electrode materials, respectively. Response surface methodology, employing a face-centered central composite design scheme, has been used to plan and analyze the experiments. Based on the preliminary and screening tests as well as the working characteristics of selected EDM machine, discharge current (I), pulse-on time (T _on), and source voltage (V) were designated as the independent input variables to assess the process performance in terms of material removal rate (MRR) and surface roughness (Ra). Suitable mathematical models for the response outputs were obtained using the analysis of variance technique, in which significant terms (main effects, two factor interactions, and pure quadratic terms) were chosen according to their p values less than 0.05 (95 % of confidence interval). Having established the suitable regression equations, a search optimization procedure, based on the use of desirability functions, optimizes the process performance in each machining regime of finishing (Ra?≤?3 μm), semifinishing (3 μm?≤?Ra?≤?4.5 μm), and roughing (Ra?≥?4.5 μm). The results are sets of optimum points which make the MRR as high as possible and keep the Ra and all machining parameters in their specified ranges simultaneously. Finally, the modeling and obtained optimization results were also discussed and verified experimentally. It was shown that the error between experimental and anticipated values at the optimal combination settings of input variables are all less than 11 %, confirming the feasibility and effectiveness of the adopted approach.     

Internal finishing process for alumina ceramic components by a magnetic field assisted finishing process

This study presents the application of a new technique, magnetic field assisted finishing, for finishing of the inner surfaces of alumina ceramic components. The experiments performed on alumina ceramic tubes examine the effects of volume of lubricant, ferrous particle size, and abrasive grain size on the finishing characteristics. The finished surface is highly dependent on the volume of lubricant, which affects the abrasive contact against the surface; on the ferrous particle size, which changes the finishing force acting on the abrasive; and on the abrasive grain size, which controls the depth of cut. By altering these conditions, this process achieves surface finishes as fine as 0.02 μm in surface roughness (R_a) and imparts minimal additional residual stress to the surface. This study also reveals the mechanism to smooth the inner surface of alumina ceramic tube and to improve the form accuracy, i.e. the roundness of inside the alumina ceramic tube.     

Experimental modeling and multi-objective optimization of traveling wire electrochemical spark machining (TW-ECSM) process

The present paper attempts to focus an application of a hybrid methodology comprising of Taguchi methodology (TM) coupled with response surface methodology (RSM) for modeling and TM coupled with weighted principal component (WPC) methodology for multiobjective optimization of a self developed traveling wire electro-chemical spark machining (TW-ECSM) process. First optimum level of input parameters is found using TM which is used as the central values in RSM to develop the second-order response model. For multiobjective optimization two quality characteristics surface roughness (R_a) and material removal rate (MRR), which are of opposite nature (R_a is the lower-the-better type, while MRR is the higher-the-better type), have been selected. The WPC is employed for the calculation of weight corresponding to each quality characteristic. The results indicate that the hybrid approaches applied for modeling and optimization of the TW-ECSM process are reasonable.     

Effects of process parameters on surface roughness in abrasive waterjet cutting of aluminium

Abrasive waterjet cutting is a novel machining process capable of processing wide range of hard-to-cut materials. Surface roughness of machined parts is one of the major machining characteristics that play an important role in determining the quality of engineering components. This paper shows the influence of process parameters on surface roughness (R_a) which is an important cutting performance measure in abrasive waterjet cutting of aluminium. Taguchi’s design of experiments was carried out in order to collect surface roughness values. Experiments were conducted in varying water pressure, nozzle traverse speed, abrasive mass flow rate and standoff distance for cutting aluminium using abrasive waterjet cutting process. The effects of these parameters on surface roughness have been studied based on the experimental results.     

Soft computing models based prediction of cutting speed and surface roughness in wire electro-discharge machining of tungsten carbide cobalt composite

This paper reports on an experimental investigation of small deep hole drilling of Inconel 718 using the EDM process. The parameters such as peak current, pulse on-time, duty factor and electrode speed were chosen to study the machining characteristics. An electrolytic copper tube of 3 mm diameter was selected as a tool electrode. The experiments were planned using central composite design (CCD) procedure. The output responses measured were material removal rate (MRR) and depth averaged surface roughness (DASR). Mathematical models were derived for the above responses using response surface methodology (RSM). The results revealed that MRR is more influenced by peak current, duty factor and electrode rotation, whereas DASR is strongly influenced by peak current and pulse on-time. Finally, the parameters were optimized for maximum MRR with the desired surface roughness value using desirability function approach.     

An experimental investigation on machining parameters of AISI D2 steel using WEDM

The performance of the wire electrodischarge machining (WEDM) machining process largely depends upon the selection of the appropriate machining variables. Optimization is one of the techniques used in manufacturing sectors to arrive for the best manufacturing conditions, which are essential for industries toward manufacturing of quality products at lowest cost. As there are many process variables involved in the WEDM machining process, it is difficult to choose a proper combination of these process variables in order to maximize material removal rate and to minimize tool wear and surface roughness. The objective of the this work is to investigate the effects of process variables like pulse on time, pulse off time, peak current, servo voltage, and wire feed on material removal rate (MRR), surface roughness (SR), gap voltage, gap current, and cutting rate in the WEDM machining process. The experiment has been done using Taguchi’s orthogonal array L27 (3⁵). Each experiment was conducted under different conditions of input parameters and statistically evaluated the experimental data by analysis of variance (ANOVA) using MINITAB and Design Expert tools. The present work also aims to develop mathematical models for correlating the inter-relationships of various WEDM machining parameters and performance parameters of machining on AISI D2 steel material using response surface methodology (RSM).The significant machining parameters and the optimal combination levels of machining parameters associated with performance parameters were also drawn. The observed optimal process parameter settings based on composite desirability (61.4 %) are pulse on time 112.66 μs, pulse off time 45 μs, spark gap voltage 46.95 V, wire feed 2 mm/min, peak current of 99.99 A for achieving maximum MRR, gap current, gap voltage, cutting rate, and minimum SR; finally, the results were experimentally verified.