Wear Surface Roughness Research Articles

Optimization through NSGA-II during machining of A356Al/20%SiCp metal matrix composites using PCD Tool

Metal matrix composite (MMC) has established growing usages in the engineering for lightweight high-strength application. However, because of abrasive nature of the reinforcement particles in MMC, machinability is reduced, tool wear is high, yet only diamond tools are appropriate for machining MMC. Being a complex process, it is very complicated to establish optimal parameters for improving cutting performance. Tool flank wear (VBmax) and Average surface roughness (Ra) are the most significant output responses, which decide the machinability of a material. The effect of cutting parameters on output responses of tool flank wear and average surface roughness are conflict with each one another so there is no single optimal mixture of cutting parameters. In this study multi regression model function, based on NSGA-II was used to optimize the machining of Al/20%SiCp MMC using tipped polycrystalline diamond (PCD) tool and also characterize the relationship among input parameters and output performance. The NSGA-II based non dominated solutions of 30 combinations chosen from 100 and presented; none of them superior to any other each and every one are best based on engineer requirement.

Tool condition monitoring in CNC end milling using wavelet neural network based on machine vision

The monitoring of tool condition in machining processes has significant importance to control the quality of machined parts and to reduce equipment downtime. This study investigates the application of a special variant of artificial neural networks (ANNs), in particular, wavelet neural network (WNN) for tool wear monitoring in CNC end milling process of high-speed steel. A mixed level design of experiments with machining parameters of cutting speed, feed rate, cutting depth, and machining time is developed, from which 126 experiments are conducted. For each experiment, tool wear and surface roughness of machined workpiece are measured. The tool wear images are processed, and the descriptor of wear zone is extracted. The WNN is then applied to predict the flank wear of the cutting tool and compared with commonly used types of ANNs and the statistical model. Different input combinations with the inclusion of wear zone descriptor and surface roughness of machined parts are used to evaluate the performance of all models. Results show that the WNN with the input parameters of cutting speed, feed rate, depth of cut, machining time, and descriptor of wear zone predicts the degree of tool wear most accurately.

Machining performance of 3D-printed ABS electrode coated with copper in EDM

PurposeRapid tooling (RT) technique using rapid prototyping (RP) process has been looked upon as an approach which reduces time and cost of production. This study aims to produce electrode for electrical discharge machining (EDM) from acrylonitrile butadiene styrene (ABS) material using the fused deposition modeling (FDM) process of RP. The electrode is coated with copper to a depth of 1 mm by using electroplating to make it conductive. This electrode is termed as RP electrode. The performance of RP electrode having square shape is compared with that of solid electrode of copper having identical size.Design/methodology/approachIn this study, the work piece material is chosen to be titanium Grade-V alloy (Ti-Al6-V4). The input parameters on the EDM machine such as discharge current, pulse on time and voltage are studied, and experiments are designed using the Taguchi method.FindingsThe results pertaining to the material removal rate (MRR), electrode wear rate (EWR) and surface roughness (Ra) are reported. It is found that the performance of a coated RP electrode is equally satisfactory when compared with that of a solid electrode.Originality/valueThis paper reports the machining performance of a square-shaped ABS electrode coated with copper. This technique, particularly when the electrode is of intricate shape, saves on cost and time of production of electrode to be used for EDM.

High-speed micro electrical discharge machining with fine surface quality in atmospheric pressure nitrogen plasma jet

Characteristics of dielectric significantly influence machining performance of micro electrical discharge machining (EDM). A high material removal rate and large tool wear are obtained in micro EDM in liquid dielectric. Tool wear in gas dielectric is small, but the material removal rate is extremely low. In previous study, it was found that micro EDM in atmospheric pressure nitrogen plasma jet (APPJ) obtained a higher material removal rate than that in gas dielectric. However, material removal rate is still much lower than in liquid dielectric. To improve the machining performance of micro EDM in APPJ, this paper proposes micro EDM in APPJ assisted with coaxial mist (APPJ + mist). Effects of both flow rate of mist and discharge pulse energy on the critical breakdown distance, material removal rate, tool electrode wear ratio, surface roughness and profile are investigated. Experiments in nitrogen with coaxial mist (nitrogen + mist), deionized water and pure mist are also conducted for comparison. Experimental results indicate that critical breakdown distances in APPJ + mist, nitrogen + mist and mist are larger than in APPJ and deionized water. To understand the effect of misted droplets on critical breakdown distance, electric field intensity of the gap in deionized water and mist were simulated. Theoretical analysis reveals that electric field intensity on the surface of water droplet is much larger than that of tool electrode rim, resulting in the easy breakdown of gap with misted droplet. Material removal rate increases from 200 μm3/s (without mist) to 1252 μm3/s (with 5 mL/min mist) in APPJ in the case of open voltage of 100 V and capacitance of 8200 pF, which is higher than material removal rate in deionized water (1096 μm3/s) under the same discharge parameters. There is almost no tool electrode wear in APPJ + mist. The surface roughness of machined groove in APPJ + mist is 538 nm much lower than that in deionized water (672 nm), nitrogen + mist (627 nm) or pure mist (691 nm). Straighter side walls and flatter bottoms of micro grooves were obtained in APPJ + mist and nitrogen + mist than those in deionized water and mist. A micro cavity is also generated by using the proposed method without compensation of tool electrode wear.

Powder mixed electric discharge machining of high-speed steel T1 grade

PurposeThe purpose of this paper is to represent the innovative process of powder-mixed electrical discharge machining of high-speed steel T1 grade and to conduct experimental investigation to optimize the machining parameters associated with multiple performance characteristics using grey relational analysis. The machining of high-speed steel T1 grade via conventional machining is a difficult process. However, it can be easily machined by powder-mixed electric discharge machining.Design/methodology/approachCarefully selected machining parameters give the optimum output results. For experimentation, the following input parameters have been used: pulse on-time, discharge current, tool material and powder concentration. The effects of input parameters, namely, material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR), have been investigated in this research.FindingsGrey relational analysis and analysis of variance have been performed to optimize the input parameters for better output response. Optimized results show increment of TWR, MRR and SR, which is 63.24, 52.18 and 42.49 per cent, respectively.Originality/valueThis research paper will be beneficial for the industrial application. The GRA result gives the better output response.

Influence of process parameters in electrical discharge machining on H13 die steel

H13 die steel is characterized by its high hardness and need for special surface features that are obtained by nontraditional machining processes. Electrical discharge machining (EDM) is used to machine hard materials and to produce complicated shapes. In this work, different EDM process parameters are investigated on H13 die steel. Several experiments are conducted to study the effect of three process parameters: peak current (Ip), pulse on-time (Ton) and electrode material on the machining process of H13 die steel. The machining process is evaluated by material removal rate (MRR), electrode wear ratio (EWR%) and surface roughness (SR) as indicators of the process efficiency in terms of quality and cost. Taguchi method was used to investigate the significant effect of process parameters on the performance measurements and the optimal parameters of the EDM process. For analysis and explanations Minitab version 17 software was used. Different process parameters were experimentally investigated and statistically analyzed and the results showed that the copper electrode leads to the highest MRR and lowest EWR%; whereas the brass electrode leads to the lowest SR.

Analisa Kekasaran Permukaan Pada Proses Edm Sinking Menggunakan Metoda Response Surface Methodology

The development of technology in the manufacturing sector is very fast, the market demand is diverse will the needs of products and components with complex shapes and high level of precision and hardness of material that has high strength. High degree of hardness and precision are widely used nonconventional EDM machine sinking. the electrode wear rate (LKE) and surface roughness (KP) are at least the performance of the EDM sinking machine process to be achieved. The study was conducted to determine the contribution of process parameters in order to reduce the variation of response parameters simultaneously and to determine the appropriate process parameter setting value. Parameters varied current, on time, off time and machining voltage. This research uses experimental design from Response Surface Methodology (RSM) method. And obtained the most refined Ra roughness results on Ton 100 µs, and Toff 15 µs with 10 A Ampere, and the roughest Ra roughness is obtained at Ton 300 µs, and Toff 15 µs with Ampere 20 A.

RSM Modeling and Taguchi Analysis of EDM of B<sub>4</sub>C and Flyash Reinforced Hybrid Nanocomposites

In this research work, EDM investigation of Al7075-B4C-flyash hybrid metal matrix nanocomposites (HMMNCs) was performed. Taguchi method was used to improve the machinability coupled with response surface methodology (RSM) to estimate the relationship between the machining parameters and performance measures. Experiments were conducted using the L18 full-factorial design with a mixed orthogonal array. Analysis of variance (ANOVA) was used to determine the effects of the machining parameters viz. voltage (V), current (I), pulse-on-time (Ton) and pulse-off-time (Toff) on tool wear rate (TWR) and surface roughness (SR). The analysis results revealed that the current was the dominant factor affecting the performance measures (62.87% for TWR and 78.82% for SR). The RSM models show very close relation with the experimental and the predicted values with the R2 values of 98.91% and 97.35% for TWR and SR respectively. The Taguchi method can effectively optimize the EDM parameters and confirmation test results showed the minimum error of 6.00% for TWR and 9.67% for SR.

Analysis of grey relational method of the effects on machinability performance on austempered vermicular graphite cast irons

In this study, vermicular graphite cast iron samples were operationalized to Austempering process in two different temperatures (315 and 375 °C) and three different waiting periods (60, 120 and 180 min). According to the selected cutting tools and cutting parameters, the effect of Austempering temperature and waiting period on the lifetime of the tools was investigated. The tests were conducted on a CNC milling machine by using coated cementite carbide cutting tools. The tests on tool wear were done in dry conditions, in a cutting speed of 120 m/min, a pitch rate of 0.15 mm/dev, and a depth of cut of 1 mm. Tool wear, cutting forces and average surface roughness rates of milled surfaces; which were occurred during the milling process, were analyzed by using grey relation method. It is observed that an increase of Austempering temperature leads to an improvement between 2.15 and 2.85 times in the lifetime of tools. By using grey relational analysis, the highest cutting performance was obtained with the sample with the temperature of 375 °C, and a waiting period of 120 min.

Cutting performance of multilayer coated tungsten carbide in milling of wood composites

ABSTRACTThe application of surface coating technology to tungsten carbide tools has been carried out to adapt the development of advanced wood composite technology. The purpose of this research was to investigate the cutting performance (wear resistance, surface roughness, and noise level) of TiAlN, TiAlN/TiSiN, and TiAlN/TiBON coated tungsten carbide in cutting wood composites. The wood composites of asbestos, wood plastic composite (WPC), laminated veneer lumber, and strand board were cut by the coated carbide tools in a computer numerical control router. The results show that the differences in structure among the wood composites resulted in the difference in clearance wear and surface roughness phenomenon. The abrasive materials in WPC and asbestos generated high clearance wear on the coated carbide tools tested. TiAlN/TiBON coated carbide tool provided the highest wear resistance, the lowest noise level, and better surface roughness.

Characterization, wear surface roughness and tensile failure analysis of Al7075-TiC-MoS2 hybrid composites using online acoustic emission

In this paper Al7075-TiC-MoS2 hybrid composites were prepared through stir-casting process and their microstructure, mechanical and tribological properties are analyzed. Aluminium 7075 was selected as matrix and reinforced with harder TiC to improve the mechanical strength and softer MoS2 to enhance the resistance to wear. The prepared samples were tested for their hardness, microstructure, XRD analysis, tensile strength through acoustic emission and wear surface roughness behaviour. All prepared composites exhibited an improvement in hardness; tensile strength and wear resistance through acoustic emission were investigated. It was observed that reinforcement was uniformly distributed across the matrix material which was attributed through continuous stirring. The surface morphology analysed through micro structural analysis revealed that the reinforcement was uniformly distributed in the matrix. The wear resistance was significantly improved with the MoS2 addition which acted as a lubricant in-between the sliding surfaces. Thus it is concluded that the hybrid composites exhibits good tensile strength, hardness and wear resistance properties. An Acoustic emission system was employed in all the tests to monitor the acoustic energy release during the whole deformation process and some useful conclusions were drawn.

Multi‐response optimization of the machining characteristics in electrical discharge machining (EDM) using span‐20 surfactant and chromium (Cr) powder mixed

AbstractEffects of Chromium (Cr) powder concentrations (Cp) and Span‐20 surfactant concentrations (Cs) on AISI D2 hardened steel were evaluated using response surface methodology (RSM) and parameter processing parameter were optimized for optimal parameter conditions using multi‐response desirability function. Responses taken involved material removal rate (MRR), electrode wear rate (EWR) and surface roughness (Ra). The experimental plan was based on the face centered, central composite design (CCD) using version 10.0 of the Design Expert software. The results identified that Cp is the most important parameter to maximize material removal rate (MRR) and minimize electrode wear rate (EWR) and surface roughness (Ra). With the topmost desirability solution, the suggested optimum parameter condition of Cp and Cs were 2.155 g/L and 10.000 g/L, respectively.

Preliminary investigations on the tribological performance of hexagonal boron nitride nanofluids as lubricant for steel/steel friction pairs

With laminated structure like graphite, hexagonal boron nitride nanoparticle (nano-hBN) performed excellent anti-wear and friction-reducing properties. In this paper, hBN nanofluids were prepared using sodium polyacrylate (PAAS) as dispersant in water. Four-ball tribometer and pin-on-disk tribometer were employed to evaluate the tribological performance and lubrication behavior of the above-prepared lubricating fluids during steel/steel friction. The worn surface of balls and disks was analyzed by scanning electron microscope (SEM), energy dispersive spectrometer (EDS) and x-ray photoelectron spectrometer (XPS). The minimum lubricating film thickness was calculated by Hamrock and Dowson equation. Results showed that 0.7 wt% was the optimum concentration of nano-hBN in water which significantly reduced the coefficient of friction (COF) and wear scar diameter (WSD) by about 29% and 15%, respectively. The lubricating film thickness was lower than both nanoparticles diameter and worn surface roughness. From the above it was concluded that the worn area could be divided into direct contact, particle lubricating and liquid lubricating area with rolling mehanism, interlayer sliding mechansim, polishing mechansim and mending mechansim of nanoparticles. A protective film was formed on friction surface by PAAS molecule, FeOOH and FeO due to the absorption effect and tribochemical reaction between the nanofluids and worn surface, which further reduced the friction and wear rate.

Statistical evaluation and performance analysis of electrical discharge machining (EDM) characteristics of hard Ti-6Al-2Sn-4Zr-2Mo alloy

Nowadays, electrical discharge machining process is successfully employed to machining hard titanium alloys compared to other non-conventional machining processes. The generation high temperature is utilized to melt and vaporize the hard titanium alloy during electrical discharge machining. The process parameters are highly influenced on the machining performance and need to be studied for optimum results. In the present research, the hard Ti-6Al-2Sn-4Zr-2Mo alloy was machined by EDM process and machining characteristics such as material removal rate, tool wear rate and surface roughness were analyzed statistically to get the optimum performance. The experiments were carried out based on the Taguchi orthogonal array method. From the statistical analysis of experimental results, the most significant parameters were identified as peak current, pulse on time and voltage. In addition to that SEM analysis was used to characterize the machined surface. The results of SEM analysis indicated that craters, surface cracks, globules and recast layer present on the machined surface.

Wear Behavior of Different Materials Applied on Horizontal Mixer Blades Used in the Processing of Total Mixed Rations

Abstract. A horizontal mixer can realize the cutting and mixing of coarse and fine feeds and achieve the purpose of scientific feeding. Studying the wear resistance of the mixer blades can improve the service life of a horizontal mixer. The wear performance of blades made of three different materials (manganese steel, tool steel, and spring steel) was studied under laboratory conditions and working conditions. In laboratory conditions, the wear scar morphology and surface elements were analyzed by means of three-dimensional topography, scanning electron microscopy, and energy spectrum analysis. The results show that the friction coefficient, wear quality, and surface roughness of manganese steel blades had the lowest values of 0.49158, 0.0061 mg, and 4.341 µm in three groups of tests. In working conditions, the wear amount and surface roughness of the manganese steel blades in different zones of the mixer were the lowest. In addition, electron backscatter diffraction (EBSD) results showed that the grain size of the manganese steel blades was the smallest. Therefore, compared with the tool steel and spring steel blades, the manganese steel blades showed excellent wear resistance.HighlightsThe wear characteristics of horizontal mixer blades with different materials were studied.The wear characteristics of the blades were studied under laboratory and working conditions.The effect of grain on the wear performance of the blades was studied by electron backscatter diffraction. Keywords: Blade, Grain, Horizontal mixer, Wear resistance, Wear test.

Performance Study of Eco-friendly dielectric in EDM of AISI 2507 Super Duplex Steel using Taguchi -Fuzzy-TOPSIS Approach

In the present study, the application of Pongamia natural ester as a renewable green dielectric (GD) applied in the electric discharge machining (EDM) of AISI 2507 super duplex steel. This investigation aims to study the effect of Pongamia green dielectric in the EDM process. The major process variables such as pulse-on time (TON), pulse-off time (TOFF), peak current (IP), voltage (v) and inter-electrode gap (IEG) on performance measures like material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR). The Taguchi's orthogonal array (OA) L27 has been selected for this experimentation. The choice of optimal input parameter settings that are attained by multi-response optimisation of performance measures using Taguchi-fuzzy-TOPSIS technique is TON = 500 μs, TOFF = 30 μs, IP = 15 A, v = 40 V and IEG = 180 μm. The optimal settings have increased the productivity aspects by the four decision makers (DM) order priorities. The optimised results, shown the improvement in MRR with the minimised EWR and SR. The optimal settings of the process for improved machining responses were identified by Taguchi's response graph and analysis of variance (ANOVA). The recast layer and micrographs were examined utilising scanning electron microscopy (SEM).

Effect of Feed Rate On Difficult to Cut Metals on Surface Roughness and Tool Wear Using Surface Treated and Untreated Tools

Abstract Machining is a process of removing unwanted material by the effective use of cutting tools to reduce the lead time. The material like Titanium, Stain steel and Inconel are considered difficult to cut metals. The difficult to cut metals require tough cutting edges to reduce the tool wear and to get smooth surface finish and product size. The cutting tools are required to be tough enough to resist wear by surface treatment like cryogenic treatment. In this research, CBN cutting inserts was used. The CBN tools was kept in nitrogen atmosphere at -176 degree centigrade in closed chamber for more than 36 hours to produce tough cutting edge, which is known as cryogenic process. In this research, treated CBN cutting tools used to turn Titanium and Inconel 718 materials. The operating parameters used were cutting speeds of 30, 40 and 50 m/min, feed rates of 0.05, 0.10 and 0.15 mm /rev and depths of cut of 0.5, 0.75 and 1.00 mm. The treated cutting inserts produced less flank wear and smooth surface roughness compared to un-treated tools. The crater wear is not in the scope of this research.

A Comparative study on machining of AlSiCp metal matrix composite using Electrical discharge machine with and without nano powder suspension in dielectric

Abstract The rising demand for metal matrix composites (MMCs) in current trend has led to the advancement of hard-to-cut materials. Of all MMCs, Aluminium metal matrix composite owing to its exceptional properties as compared to that of other metals, has gained popularity among researchers. Thus in the present study, aluminium with particulate silicon carbide (SiCp) composite is used and aim to evaluate the comparative effect of process parameters such as pulse on time, pulse off time, and peak current on metal removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) during Electrical discharge machining (EDM) on Al-SiC12% metal matrix composite with the use of nano particles mixed in the dielectric fluid and without the use of particles. The uses of powders have led to the increase in spark gap between the tool and the electrode. Here, nano powders are used for better efficiency. Experimental work is followed by Central composite design with various combinations of process parameters. Response surface methodology (RSM) is taken up for mathematical modelling and correlating the EDM parameters with responses. Analysis of variance (ANOVA) is used to analyse significance of the model. The SEM micro-graphs reveal the difference in either of the case during machining with and without nano powders in dielectric.

Multi Criteria Optimization Approaches in Electric Discharge Machining

Abstract Electrical Discharge Machining (EDM) is a prime technique employed to the materials that are almost impossible to be cut by conventional machining. Performance of the EDM is assessed on the ground of Material Removal Rate (MRR), Tool Wear Rate (TWR), Relative Wear Ratio (RWR) and Surface Roughness (SR). The major factors affecting the above performance are Voltage, Pulse on time, Current, Pulse off time, Inter Electrode Gap & Duty cycle. An extensive work had been performed by the pioneer researchers in the field of optimization for aforesaid performance measures against several process parameters. Every researcher uses different materials with different levels of parameters whereas some use same materials but with a different input, output parameters and different levels to variate and see the differences. To solve the problem efficiently different researchers used various optimization techniques some of which are Taguchi, RSM, ANOVA, MOGA II, Passing Vehicle Search Algorithm, Genetic Algorithm, GRA, Full Factorial Approach, VIKOR index, Stochastic Algorithm etc. It was felt that a review would be essential to know the comparison and the subsequent contribution of the different parameters, performance output, algorithm & various optimization techniques being used to optimize the process parameters and their resulting effect on the performance. The purpose of this paper is to study the emerging trends and researches done in the area of EDM. Various multi criterion optimization techniques have been reviewed in this paper.

Tubing String Thread Sealing Surfaces Damage Evaluation Based on Acoustic Elasticity Theory

During the processing of tubing premium threaded made up, the degree of the thread sealing surface intactness will directly affect the sealing performance of the string. Nevertheless, there are some difficulties to detect the damage of the engaged sealing surface effectively. In the present study the sealing surface damage was judged by the sealing surface contact stress’s relative changes according to the acoustic elasticity theory,. At the same time, the wear defects generated at the tubing sealing surface, during the tubing made up, contrasted with the wear and unworn surface roughness of coupling ultrasonic detected about the sealing surface. The results showed that with the acoustic amplitude evaluated the sealing contact stress was susceptible to the influence of surface roughness of coupling. But the reflection wave with the center frequency on the sealing surface characterization of the contact stress could avoid this problem effectively.