An investigation on machinability of nodular cast iron by WEDM

In this study, the machinability of standard GGG40 nodular cast iron by WEDM using different parameters (machining voltage, current, wire speed, and pulse duration) was investigated. From the results, the increase in surface roughness and cutting rate clearly follows the trend indicated with increasing discharge energy as a result of an increase of current and pulse-on time, because the increased discharge energy will produce larger and deeper discharge craters. Three zones were identified in rough regimes of machining for all samples: decarburized layer, heat affected layer, and bulk metal. High machining efficiency can be obtained when the proper electrical parameters are selected, but whether high energy or the low energy is used, a coarse surface is always obtained. The variation of surface roughness and cutting rate with machining parameters is mathematically modeled by using the regression analysis method.     

不同冷却润滑条件下TB6钛合金高速切削表面完整性研究

通过TB6钛合金高速铣削试验,测量观察加工表面粗糙度、表面三维形貌和表层微观组织等表面完整性特征,利用极差法分析切削参数对表面粗糙度影响的显著性,探讨冷却润滑条件对加工表面形貌和表面变质层的影响。研究表明:工艺参数对表面粗糙度影响程度依次为径向切深、切削速度、进给量和轴向切深;相比低温冷风加,微油雾润滑加工时钛合金表面粗糙度低,且表面无明显晶粒变形,表明加工表面塑性变形是影响粗糙度的主要因素。     

Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm

Modeling and optimization of cutting parameters are one of the most important elements in machining processes. The present study focused on the influence machining parameters on the surface roughness obtained in drilling of AISI 1045. The matrices of test conditions consisted of cutting speed, feed rate, and cutting environment. A mathematical prediction model of the surface roughness was developed using response surface methodology (RSM). The effects of drilling parameters on the surface roughness were evaluated and optimum machining conditions for minimizing the surface roughness were determined using RSM and genetic algorithm. As a result, the predicted and measured values were quite close, which indicates that the developed model can be effectively used to predict the surface roughness. The given model could be utilized to select the level of drilling parameters. A noticeable saving in machining time and product cost can be obtained by using this model.     

Influence of discharge energy on machining characteristics in EDM

The machining characteristics of electrical discharge machining (EDM) directly depend on the discharge energy which is transformed into thermal energy in the discharge zone. The generated heat leads to high temperature, resulting in local melting and evaporation of workpiece material. However, the high temperature also impacts various physical and chemical properties of the tool and workpiece. This is why extensive knowledge of development and transformation of electrical energy into heat is of key importance in EDM. Based on the previous investigations, analytical dependence was established between the discharge energy parameters and the heat source characteristics in this paper. In addition, the thermal properties of the discharged energy were experimentally investigated and their influence on material removal rate, gap distance, surface roughness and recast layer was established. The experiments were conducted using copper electrode while varying discharge current and pulse duration. Analysis and experimental research conducted in this paper allow efficient selection of relevant parameters of discharge energy for the selection of most favorable EDM machining conditions.     

Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations

Optimization of cutting parameters is valuable in terms of providing high precision and efficient machining. Optimization of machining parameters for milling is an important step to minimize the machining time and cutting force, increase productivity and tool life and obtain better surface finish. In this work a mathematical model has been developed based on both the material behavior and the machine dynamics to determine cutting force for milling operations. The system used for optimization is based on powerful artificial intelligence called genetic algorithms (GA). The machining time is considered as the objective function and constraints are tool life, limits of feed rate, depth of cut, cutting speed, surface roughness, cutting force and amplitude of vibrations while maintaining a constant material removal rate. The result of the work shows how a complex optimization problem is handled by a genetic algorithm and converges very quickly. Experimental end milling tests have been performed on mild steel to measure surface roughness, cutting force using milling tool dynamometer and vibration using a FFT (fast Fourier transform) analyzer for the optimized cutting parameters in a Universal milling machine using an HSS cutter. From the estimated surface roughness value of 0.71 μm, the optimal cutting parameters that have given a maximum material removal rate of 6.0×10³ mm³/min with less amplitude of vibration at the work piece support 1.66 μm maximum displacement. The good agreement between the GA cutting forces and measured cutting forces clearly demonstrates the accuracy and effectiveness of the model presented and program developed. The obtained results indicate that the optimized parameters are capable of machining the work piece more efficiently with better surface finish.     

Influence of machining parameters on surface roughness in finish cut of WEDM

Surface roughness is significant to the finish cut of wire electrical discharge machining (WEDM). This paper describes the influence of the machining parameters (including pulse duration, discharge current, sustained pulse time, pulse interval time, polarity effect, material and dielectric) on surface roughness in the finish cut of WEDM. Experiments proved that the surface roughness can be improved by decreasing both pulse duration and discharge current. When the pulse energy per discharge is constant, short pulses and long pulses will result in the same surface roughness but dissimilar surface morphology and different material removal rates. The removal rate when a short pulse duration is used is much higher than when the pulse duration is long. Moreover, from the single discharge experiments, we found that a long pulse duration combined with a low peak value could not produce craters on the workpiece surface any more when the pulse energy was reduced to a certain value. However, the condition of short pulse duration with high peak value still could produce clear craters on the workpiece surface. This indicates that a short pulse duration combined with a high peak value can generate better surface roughness, which cannot be achieved with long pulses. In the study, it was also found that reversed polarity machining with the appropriate pulse energy can improve the machined surface roughness somewhat better compared with normal polarity in finish machining, but some copper from the wire electrode is accreted on the machined surface.     

Electrical discharge precision machining parameters optimization investigation on S-03 special stainless steel

S-03 is a novel special stainless steel, which is widely used in precision aerospace parts and electrical discharge machining technology has the merit of high-accuracy machining. This paper aims to combine gray relational analysis and orthogonal experimental to optimize electrical discharge high-accuracy machining parameters. The four process parameters of gap voltage, peak discharge current, pulse width, and pulse interval are required to optimize in the fewest experiment times. The material removal rate and surface roughness are the objective parameters. The experiment were carried out based on Taguchi L9 orthogonal array, then we carried out the gray relational analysis to optimize the multi-objective machining parameter, finally, we verified the results through a confirmation experiment. The sequence of machining parameters from primary to secondary are as follows: discharge current 7A, pulse interval 100 μs, pulse width 50 μs, and gap voltage 70 V. Using the above machining parameters, we can obtain good surface roughness Ra1.7 μm, and material removal rate 13.3 mm³/min. The machined work piece almost has no surface modification layer. The results show that combining orthogonal experiment and gray relational analysis can further optimize machining parameters, the material removal rate increased by 23.8 %, and the surface roughness almost has no change.     

An optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool for best surface finish

High-speed machining (HSM) has emerged as a key technology in rapid tooling and manufacturing applications. Compared with traditional machining, the cutting speed, feed rate has been great progress, and the cutting mechanism is not the same. HSM with coated carbide cutting tools used in high-speed, high temperature situations and cutting more efficient and provided a lower surface roughness. However, the demand for high quality focuses extensive attention to the analysis and prediction of surface roughness and cutting force as the level of surface roughness and the cutting force partially determine the quality of the cutting process. This paper presents an optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool to achieve minimum cutting forces and better surface roughness. Taguchi optimization method is the most effective method to optimize the machining parameters, in which a response variable can be identified. The standard orthogonal array of L₉ (3⁴) was employed in this research work and the results were analyzed for the optimization process using signal to noise (S/N) ratio response analysis and Pareto analysis of variance (ANOVA) to identify the most significant parameters affecting the cutting forces and surface roughness. For such application, several machining parameters are considered to be significantly affecting cutting forces and surface roughness. These parameters include the lubrication modes, feed rate, cutting speed, and depth of cut. Finally, conformation tests were carried out to investigate the improvement of the optimization. The result showed a reduction of 25.5% in the cutting forces and 41.3% improvement on the surface roughness performance.     

Wire electrical discharge machining of ASP30 tool steel

Wire electrical discharge machining is a non-traditional cutting process for machining of hard and high strength materials. This study analyzed the effects of the main input parameters of wire electrical discharge machining of ASP30 steel (high alloyed Powder metallurgical [PM] high speed steel) as the workpiece on the material removal rate and surface roughness. The input parameters included spraying pressure and electric conductivity coefficient of the dielectric fluid, linear velocity of the wire and wire tension. The machined surface quality was evaluated using SEM pictures. Results indicated that increasing the spraying pressure of dielectric fluid leads to a higher material removal rate and surface roughness and that increasing the wire tension, linear velocity of wire, and electric conductivity of the dielectric fluid decreases the material removal rate and surface roughness.

     

Multi response optimization of wire EDM operations using robust design of experiments

In this present study a multi response optimization method using Taguchi’s robust design approach is proposed for wire electrical discharge machining (WEDM) operations. Experimentation was planned as per Taguchi’s L16 orthogonal array. Each experiment has been performed under different cutting conditions of pulse on time, wire tension, delay time, wire feed speed, and ignition current intensity. Three responses namely material removal rate, surface roughness, and wire wear ratio have been considered for each experiment. The machining parameters are optimized with the multi response characteristics of the material removal rate, surface roughness, and wire wear ratio. Multi response S/N (MRSN) ratio was applied to measure the performance characteristics deviating from the actual value. Analysis of variance (ANOVA) is employed to identify the level of importance of the machining parameters on the multiple performance characteristics considered. Finally experimental confirmation was carried out to identify the effectiveness of this proposed method. A good improvement was obtained.     

Hard turning: Parametric optimization using genetic algorithm for rough/finish machining and study of surface morphology

The present study reports the effect of different process parameters on machining forces, surface roughness, dimensional deviation and material removal rate during hard turning of EN31, SAE8620 and EN9 tool steels. Feed rate followed by hardness, cutting speed and nose radius-depth of cut significantly affected machining forces whereas feed rate had the largest effect on surface roughness. The four responses were subsequently optimized for both rough and finish machining using genetic algorithm to determine the optimum combination of input parameters. Machined surfaces were subsequently analyzed using XRD followed by analysis of grain size and crystallite size of the machined samples and SEM analysis. Higher chromium content was observed at the machined surface as manganese dissolves in cementite and may replace iron atoms in the cementite lattice after machining. High heat is generated when machining at higher cutting speeds causing severe strain. The depth of the white layer decreases with increasing tool nose radius and increases at larger feeds because of greater heat generation. The SEM observations showed a smooth pattern with very low undulations with almost no crack damage.     

Multi-objective optimization of machining parameters considering energy consumption

This paper deals with multi-objective optimization of machining parameters for energy saving. Three objectives including energy, cost, and quality are considered in the optimization model, which are affected by three variables, namely cutting depth, feed rate, and cutting speed. In the model, energy consumption of machining process consists of direct energy (including startup energy, cutting energy, and tool change energy) and embodied energy (including cutting tool energy and cutting fluid energy); machining cost contains production operation cost, cutting tool cost, and cutting fluid cost; and machining quality is represented by surface roughness. With simulation in Matlab R2011b, the multi-objective optimization problem is solved by NSGA-II algorithm. The simulation results indicate that cutting parameters optimization is beneficial for energy saving during machining, although more cost may be paid; additionally, optimization effect on the surface roughness objective is limited. Inspired by the second result, optimization model eliminating quality objective is studied further. Comparing the non-dominated front of three-objective optimization with the one of two-objective optimization, the latter is proved to have better convergence feature. The optimization model is valuable in energy quota determination of workpiece and product.     

Construction of a surface roughness prediction model for high speed machining

In manufacturing environment prediction of surface roughness is very important for product quality and production time. For this purpose, the finite element method and neural network is coupled to construct a surface roughness prediction model for high-speed machining. A finite element method based code is utilized to simulate the high-speed machining in which the cutting tool is incrementally advanced forward step by step during the cutting processes under various conditions of tool geometries (rake angle, edge radius) and cutting parameters (yielding strength, cutting speed, feed rate). The influences of the above cutting conditions on surface roughness variations are thus investigated. Moreover, the abductive neural networks are applied to synthesize the data sets obtained from the numerical calculations. Consequently, a quantitative prediction model is established for the relationship between the cutting variables and surface roughness in the process of high-speed machining. The surface roughness obtained from the calculations is compared with the experimental results conducted in the laboratory and with other research studies. Their agreements are quite well and the accuracy of the developed methodology may be verified accordingly. The simulation results also show that feed rate is the most important cutting variable dominating the surface roughness state.     

Application of Taguchi and response surface methodologies for surface roughness in machining glass fiber reinforced plastics by PCD tooling

This paper discusses the use of Taguchi and response surface methodologies for minimizing the surface roughness in machining glass fiber reinforced (GFRP) plastics with a polycrystalline diamond (PCD) tool. The experiments have been conducted using Taguchi’s experimental design technique. The cutting parameters used are cutting speed, feed and depth of cut. The effect of cutting parameters on surface roughness is evaluated and the optimum cutting condition for minimizing the surface roughness is determined. A second-order model has been established between the cutting parameters and surface roughness using response surface methodology. The experimental results reveal that the most significant machining parameter for surface roughness is feed followed by cutting speed. The predicted values and measured values are fairly close, which indicates that the developed model can be effectively used to predict the surface roughness in the machining of GFRP composites. The predicted values are confirmed by using validation experiments.     

An experimental study on micro wire-EDM of polycrystalline diamond using a novel pulse generator

This paper presents a new pulse generator for cutting of polycrystalline diamond (PCD) by micro wire electrical discharge machining (micro wire-EDM). The pulse generator using anti-electrolysis circuitry and digital signal processor-based pulse control circuit was developed to suppress damages on the machined surface of PCD while achieving stable machining. A novel pulse control method was proposed to provide high-frequency pulse control signals with a period of off duty cycle for reionization of the dielectric in the spark gap so as to reduce the consecutive occurrence of short circuits. A series of experiments were carried out to investigate the effect of open voltage on machining performance in terms of material removal rate, slit width, thickness of the damaged layer on machined surface, and surface finish. An increase of open voltage increases peak current, thus producing greater discharge energy and, thereby, contributing to improvements in material removal rate, but leading to larger slit width and thickness of the damaged layer and worse surface finish. Experimental results not only demonstrate that the developed pulse generator could achieve satisfactory machining results but also have verified the applicability of this new technique in micro wire-EDM.     

Surface roughness aspects in milling MDF (medium density fibreboard)

Medium density fibreboard (MDF) is an industrial wood product. It is made out of wood waste fibres glued together with resin by heat and pressure. Nowadays MDF products are preferred over solid wood in many applications due to certain comparative advantages. Milling is the machining operation frequently used in manufacturing parts of MDF. The aim of this article is to study the influence of cutting parameters (cutting speed and feed rate) on surface roughness in MDF milling. A plan of MDF milling experiments was performed with prefixed cutting parameters. The objective was to establish correlation between cutting speed and feed rate with the surface roughness in MDF panels after milling. The surface roughness decreases with an increase of spindle speed and increases with the feed rate. The milling tests showed the important role spindle speed plays on the evolution of the surface roughness as a function of material removal rate (MRR). The advantage of using a high cutting speed in MDF milling is evident.     

Effect of MQL flow rate on machinability of AISI 4140 steel

Abstract

Many studies were performed about the influence of minimum quantity lubrication (MQL) technique on cutting performance in the literature, but there is no paper examining the effect of different MQL flow rates and cutting parameters on machinability of AISI 4140 material as a whole. In this study, the effects of different MQL flow rates and cutting parameters on surface roughness, main cutting force and cutting tool flank wear (VB), with great importance among the machinability criteria, and forming as a result of the machining of AISI 4140, were revealed. At the end of the experiments, it was determined that rise of flow rate affected main cutting forces positively to a certain extent; yet, it exhibited no significant effect on surface roughness, but reduced VB. Also, it was observed that both main cutting force and surface roughness increased with the increase of feed, while generally decreased with the increase of cutting speed. It was seen that flank wear was positively affected by the increase in flow rate; and this decreased with the increase in flow rate. R² values obtained as 99.8% and 99.9% for main cutting forces and surface roughness values modeled statistically with the help of quadratic equations, respectively.     

Investigation of electro-discharge micro-machining of titanium super alloy

Being a difficult-to-cut material, titanium alloy suffers poor machinability for most cutting processes, especially the drilling of micro-holes using traditional machining methods. Although electrical discharge machining (EDM) is suitable for machining titanium alloys, selection of machining parameters for higher machining rate and accuracy is a challenging task in machining micro-holes. The present research attempts to optimize micro-EDM process parameters for machining Ti-6Al-4V super alloy. To verify the optimal micro-EDM process parameters settings, metal removal rate (MRR), tool-wear rate (TWR), over cut (OC) and taper were chosen as observed performance criteria. In addition, four independent parameters such as peak current, pulse-on time, flushing pressure, and duty ratio were adopted for evaluation by the Taguchi method. From the ANOVA and S/N ratio graph, the significant process parameters and the optimal combination level of machining parameters were obtained. It is seen that machining performances are affected mostly by the peak current and pulse-on time during micro-electro-discharge machining of titanium alloy. Mathematical models have been developed to establish the relationship between various significant process parameters and micro-EDM performance criteria. In-depth studies have also been made to examine the influence of various process parameters on the white layer and surface topography through SEM micrographs of machined micro-hole.     

Optimization of surface roughness in end milling Castamide

Castamide is vulnerable to humidity up to 7%; therefore, it is important to know the effect of processing parameters on Castamide with and without humidity during machining. In this study, obtained quality of surface roughness of Castamide block samples prepared in wet and dry conditions, which is processed by using the same cutting parameters, were compared. Moreover, an artificial neural network (ANN) modeling technique was developed with the results obtained from the experiments. For the training of ANN model, material type, cutting speed, cutting rate, and depth of cutting parameters were used. In this way, average surface roughness values could be estimated without performing actual application for those values. Various experimental results for different material types with cutting parameters were evaluated by different ANN training algorithms. So, it aims to define the average surface roughness with minimum error by using the best reliable ANN training algorithm. Parameters as cutting speed (V _c), feed rate (f), diameter of cutting equipment, and depth of cut (a _p) have been used as the input layers; average surface roughness has been also used as output layer. For testing data, root mean squared error, the fraction of variance (R ²), and mean absolute percentage error were found to be 0.0681%, 0.9999%, and 0.1563%, respectively. With these results, we believe that the ANN can be used for prediction of average surface roughness.     

Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool

Hard turning with multilayer coated carbide tool has several benefits over grinding process such as, reduction of processing costs, increased productivities and improved material properties. The objective was to establish a correlation between cutting parameters such as cutting speed, feed rate and depth of cut with machining force, power, specific cutting force, tool wear and surface roughness on work piece. In the present study, performance of multilayer hard coatings (TiC/TiCN/Al₂O₃) on cemented carbide substrate using chemical vapor deposition (CVD) for machining of hardened AISI 4340 steel was evaluated. An attempt has been made to analyze the effects of process parameters on machinability aspects using Taguchi technique. Response surface plots are generated for the study of interaction effects of cutting conditions on machinability factors. The correlations were established by multiple linear regression models. The linear regression models were validated using confirmation tests. The analysis of the result revealed that, the optimal combination of low feed rate and low depth of cut with high cutting speed is beneficial for reducing machining force. Higher values of feed rates are necessary to minimize the specific cutting force. The machining power and cutting tool wear increases almost linearly with increase in cutting speed and feed rate. The combination of low feed rate and high cutting speed is necessary for minimizing the surface roughness. Abrasion was the principle wear mechanism observed at all the cutting conditions.