Machined Surface Characteristics Research Articles

Optimization of Machining Parameters and Analysis of the Surface Characteristics in Micro-electrical Discharge Machining of 310 and 316 Stainless Steel

Optimization of Machining Parameters and Analysis of the Surface Characteristics in Micro-electrical Discharge Machining of 310 and 316 Stainless Steel

Effect of inter-electrode gap on surface characteristics in conventional electrochemical machining

Conventional electrochemical machining (CECM) is an established toolroom process for the machining of conductive workpiece (W/P) substrates. In CECM, the material removal takes place through an electrochemical reaction between the cathode and anode. Significant studies have reported process parametric optimization of CECM with input parameters like voltage, feed rate, type of electrolyte and electrolyte concentration, etc., and their effect on the material removal rate (MRR), and surface roughness (Ra). But hitherto little has been reported on the effect of inter-electrode gap (IEG) and other CECM parameters in combination with a different tool and work materials. This study outlines the experimental investigations on CECM with a different tool and work materials based on Taguchi L18 orthogonal array (OA) on surface characteristics of machined surface for tool room applications in line with sustainable development goal (SDG) (with a special target on the industry, innovation, and infrastructure). The results suggest that for Ra, IEG is the most significant factor at a 95% confidence level. The results have been supported by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and Ra analysis (with amplitude distribution function (ADF), and peak count (PC).

Multi-objective parametric optimization of electrochemical machining of Inconel-625 superalloy

The high hardness value of Inconel-625 super alloy makes it difficult to machine with traditional machining methods. In this study, the machining of Inconel-625 has been attempted with electrochemical machining. The influence of input process parameters—voltage, feed rate, and flow rate of electrolyte has been studied on the output responses—material removal rate (MRR) and average surface roughness (SR). The experiments were performed following the central composite rotatable design of the response surface methodology. Analysis of variance has been used to test the significance of the process parameters and the model. A comprehensive empirical model representing the relationship between the process parameters and the response parameters has been developed. Further, the desirability function approach was used to acquire the optimal set of parameters. The optimal values of MRR and SR obtained in the study are 0.192837 gm./min and 0.99 μm, respectively, corresponding to the optimum settings of voltage, feed rate of the tool, and flow rate of electrolyte at 13.7 V, 0.20 mm/min, and 2.8 lit/min, respectively. The optimum settings so attained have been substantiated using confirmation experiments. The Confirmation tests show that the error between predicted and experimental values of MRR and SR was 2.02% and 4.8%, respectively, which fall in the acceptable range. Moreover, the surface characteristics of the machined area have been investigated using field emission scanning electron microscopy and 3D optical profilometer to analyze the machined surface's microstructure and 3D surface characteristics.

Novel use of cryogenic cooling conditions in improving the machining performance of Al 8011/nano-SiC composites

The inclusion of nanoparticles makes the composite not only stronger but also lighter and highly resistant towards wear among many other positive attributes. However, the high hardness and abrasive characteristics of the composites make machining a formidable task. Hence to surmount these challenges, various coolant conditions have been entailed like dry machining, flood cooling, minimum quantity lubrication (MQL), and cryogenic (cryo) CO2 cooling. This investigation encompasses the influence of diverse coolant techniques during the machining of as casted aluminium with nano silicon carbide (Al/n-SiC) composite. This study further incites the analysis of the machining temperature, surface characteristics, flank wear, and chip morphology under each coolant techniques. The outcomes of this investigation furnish a comprehensive understanding of the impact of distinct coolant environments on the machining performance of Al/n-SiC composite. The cutting temperature under cryo-CO2 was found to be lowered by 41–47%, 15–21%, and 8–12% when compared to the usage of dry, flood, and MQL, respectively. The study unveils that cryo-CO2 cooling developed the lowest machining temperature, followed by MQL, flood cooling, and dry machining. Furthermore, cryo-CO2 cooling and MQL exhibited the best outcome in terms of flank wear and surface characteristics. The verdicts of this investigation suggest the use of cryo-CO2 cooling and MQL makes eloquent improvement in the machining performances of Al/n-SiC composites.

Measuring Surface Characteristics in Sustainable Machining of Titanium Alloys Using Deep Learning-Based Image Processing

Measuring Surface Characteristics in Sustainable Machining of Titanium Alloys Using Deep Learning-Based Image Processing

A Precision Analysis of Machining Incoloy 901 Aerospace Materials with Cemented Carpide Tools by the Taguchi Method

In this research work, was made a study on the effects of turning conditions on incoloy 901 nickel-based superalloy and performed a precision analyzes using the Taguchi L27 orthogonal array. Using the results of variance analysis (ANOVA) and signal-to-noise (S / N) ratio and taking into account the "smaller is better" approach were statistically investigated to establish a correlation amongst the speed of cutting, feed rate and cutting tool with respect to surface quality and cutting forces. KCU10, K313 and KCU25 cemented carpide cutting tool were used in experimental study. The experimental results have revealed the most important factor influencing the cutting force and surface quality was the type of the cutting tool and it’s had a serious effect on both, KCU10 and followed by KCU25 was found better than the other cutting tool. Optimum parameters for the cutting forces were found 0,150 mm/rev., 90 m/min. with KCU10 cutting tool The found findings can help for revealed the optimization of machining parameters and surface characteristics of Incoloy 901 during high speed turning.

Characterization of surface topography during multi-pass WEDM of MWCNT alumina composites

The thermal spalling action of material removal associated with electrical discharge machining of ceramics results in severe surface debris, cracks, pores, etc. This led to a rough machined surface, ultimately rendering the machined component not susceptible for direct applications. Such a behavior points towards the need to further process the machined surface so as to reduce the net severity of the machined surface. The current work utilizes multi-pass wire electrical discharge machining to enhance the machined surface characteristics of alumina composites. Detailed comparison of the surface characteristics with regards to amplitude, spatial, hybrid and functional volume parameters depicted a superior and homogenous machined surface post multi-pass process. The recast layer severity was minimal as well by incorporation of multi-pass. Furthermore, a detailed analysis of the structural fingerprints of the surface elements depicts actual breakage and subsequent burn-out of the filler material.

Effect of Process Parameters on Material Removal Rate and Surface Characteristics in WEDM Machining of Titanium Grade 7 Alloy

Wire Electrical Discharge Machining (WEDM) is a modern machining technique. WEDM is electro-thermal non-conventional machining processes follow to cut very hard materials. WEDM is non-traditional material cutting operation employed to machine complex geometries and shapes. The present paper attempts to study surface and sub-surface variations during WEDM of titanium grade 7 alloy with Brass wire coated with Zn. This paper presents experimental studies with varying three key process parameters viz. pulse ON time (TON), pulse OFF time (TOFF), peak current (IP). The investigation is focused on assessment of material removal rate, surface roughness as well as recast layer. Scanning electron Microscope (SEM) examinations are carried out on surface textures and are discussed in the article. The obtained results indicated that the stretched pulse time discharges more energy causes rough surface finish. The MRR is also strongly influenced by TON.

A comparative study relating machining properties and surface characteristics of Inconel 625 during powder mixed electric discharge machining

In the current study, the machinability during the machining with powder mixed electric discharge machining was studied on Inconel 625 sample along with their surface characteristics. During the machining, separatelythree powders viz. titanium, graphite and silicon carbide were mixed in EDM oil dielectric fluid with a concentration of 4 g/l. The other electric parameters were kept constant. The comparative study was made to study the changes in MRR, surface roughness and tool wear rate. The analysis clearly indicates that. by the addition of titanium, graphite and silicon carbide in the order, the MRR decreases, surface roughness increases and tool wear rate increases. The SEM results of the machined sample indicate that the surface unevenness is increasing with changing of powders. The EDX result of the surface correlated the amount of copper transferred to the surface and the tool wear rate . Like the SEM result, EDX result also indicated the enhancement of the tool wear during the machining of above-said order of the powders.

Development and analysis of scalable laser machined surface utilizing low power nanosecond laser on Ti-6Al-4V alloy

ABSTRACT A low-power fiber laser system was utilized for machining a scalable surface area on the Ti-6Al-4V alloy surface through the track overlapping process. The effect of laser power and track overlapping on laser machined surfaces was investigated. The experimental results revealed that the laser machined surface characteristics, i.e. machining depth, resolidified layer thickness, heat affected zone (HAZ) size, and surface roughness, depend on the average laser power and track overlapping. The increased laser power from 30 W to 50 W at 50% track overlapping increases the machining depth from 88 µm to 981 µm due to a higher energy supply. Further, laser processing at higher power, i.e. 50 W, shows a significant increase in resolidified layer (up to 727 µm). The laser machined surface generated at higher power and track overlapping increases the surface roughness. The laser machined surface developed at 30 W and 50% track overlapping indicates surface roughness (Ra) of 2.9 µm and increases to 6.5 µm for surface processing at 80% track overlapping. Further, the surface roughness of the laser machined increases up to 14 µm for laser processing at higher power (50 W) and high track overlapping (80%).

A Multiphysics Model for Predicting Microstructure Changes and Microhardness of Machined AerMet100 Steel.

The machined-surface integrity plays a critical role in corrosion resistance and fatigue properties of ultra-high-strength steels. This work develops a multiphysics model for predicting the microstructure changes and microhardness of machined AerMet100 steel. The variations of stress, strain and temperature of the machined workpiece are evaluated by constructing a finite-element model of the orthogonal cutting process. Based on the multiphysics fields, the analytical models of phase transformation and dislocation density evolution are built up. The white layer is modeled according to the phase-transformation mechanism and the effects of stress and plastic strain on real phase-transformation temperature are taken into consideration. The microhardness changes are predicted by a model that accounts for both dislocation density and phase-transformation evolution processes. Experimental tests are carried out for model validation. The predicted results of cutting force, white-layer thickness and microhardness are in good agreement with the measured data. Additionally, from the proposed model, the correlation between the machined-surface characteristics and processing parameters is established.

Quantitative evaluation method of tool wear based on morphological characteristics of machined surfaces

Tool wear monitoring techniques have been extensively applied in the modern manufacturing sectors to carry out predictive maintenance and to avoid the massive loss induced by sudden downtime. However, the online tool wear detection based on either the machining vibration or the variation of cutting power always encounters the interference caused by the excessive change of workpiece materials or even by the fluctuations of the coolant pressure. In the present work, a rapid half-online tool wear monitoring method based on the standard sample cutting and focus-variation scanning technique (FVST) was designed to quantify the tool wear extents. Invar alloy was used as the standard sample due to its low thermal expansion and ductile machinability. The results show that the texture of the machined surface is determined by the change of the cutting edge, and thus the surface morphologies can be regarded as the index of tool wear. Tool wear condition was revealed and quantified through the assessment models established based on the characteristic parameters including the width/depth of the texture and the surface roughness of the standard sample machined by new and worn tools under the identical cutting conditions. The results show that the tool wear can be revealed efficiently via the help of the surface morphological analysis, and the method is more none-destructive, rapid, and reliable compared with the conventional tool wear monitoring methods. In sum, the quantitative evaluation method of tool wear based on the morphological characteristics of the machined standard sample surfaces is confirmed capable of improving the accuracy and efficiency of tool wear monitoring.

Experimental analysis of subsurface integrity during fine turning of OFE copper for radiofrequency cavity manufacturing

Machining oxygen-free electronic (OFE) copper could be challenging but is not widely studied because few industrial or critical components requires to master the machined sub-surface characteristics. CERN radio frequency cavities are one of the applications, especially because the turned surface is not the functional one of the final products. The niobium coating post process, which gives superconductive properties to the cavity, largely depends on the machined surface characteristics. The present study relies on an experimental approach of the cutting process, through thermal and mechanical probing of high precision, pollution free, turning. Cutting forces and thermal load on the tool are detailed for finish turning. The critical uncut chip thickness, defined at macroscale as the limit between cutting and ploughing behavior, is also a frontier at microscale. Consequently, surface integrity is evaluated by advance microstructural analysis (EBSD and FIB), imposed by the thinness of the affected layer. Grain recrystallization appears in the first 0.6 micrometers below the surface and deformed grains are observed up to 4 micrometers for cutting regime, while the thickness of the layers is three time larger in case of ploughing regime. Hence surface integrity of OFE copper finish turning is characterized and optimal cutting conditions are defined. The research shows that simple cutting tests can quickly narrow down to optimal cutting condition, which are then confirmed through metallurgical analysis, even in the edge case of pure OFE copper, hence relevant to other material.

Characterization of Machined Surfaces of Al-based Automotive Alloys with Different Levels of Si Content under Up Milling and Down Milling Operation

This paper aims to investigate and compare the characteristics of machined surfaces and chips formation of aluminium-based automotive alloys with varying silicon content. The milling operations are performed using horizontal milling machine under two peripheral up milling and down milling methods with an HSS slab milling cutter. The experiment has conducted for different cutting speeds in dry condition while the depth of cut and machining feed are kept constant throughout the evaluation. The study reveals that the down-milled surface has higher hardness and better surface finish resulting in lower roughness as the cutting force is compressive in nature. On the contrary, the up-milled surface has lower hardness and micro cracks on it, which resulted in relatively higher surface roughness as the cutting force is tensile shear in nature. In addition, the surface hardness increases with the increment of silicon content in the alloys for both milling methods for the presence of hard Si rich intermetallics. The chips produced during up milling are shorter whereas the chips produced during down milling are longer for creation of higher temperature and pressure. Higher Si added alloy shows the curly like chips for its lower elongation behaviour. Fracture behaviour of higher Si alloy also confirms crack propagation obtained by the massive cleavage of the brittle and plate-types Si rich intermetallics.

Impact of MWCNT in CFRP composite during end milling process

ABSTRACT Incorporation of nanofillers upto a certain weight percentage in polymeric matrix has been established to enhance the performance of composites. Machining is an integral part of any manufacturing process and the effect of machining on nanocomposites has been a subject of various studies. The present study investigates the influence of multi-walled carbon nanotube (MWCNT), spindle speed (SS), and feed rate (FR), on end milling performances, such as, delamination factor (DF) and surface roughness (Ra) by using the TOPSIS methodology. The investigation has showed that incorporation of MWCNTs in the CFRP composites optimizes the machining performances. The investigation, using multi-objective TOPSIS-based analysis of variance approach, showed that SS is the most governing factor, followed by FR and MWCNT wt%, which influence the overall performance of the composites. Field emission scanning electron microscope (FESEM) has been used to show the dispersion of MWCNT in the epoxy matrix. Improvisation on machining surface characteristics along with optimal performance parameters are accomplished successfully.

Characterization of Machined Surface Topography Based on the Normal Declination Angle of Microfacets.

It is important to characterize surface topography in order to study machined surface characteristics. Due to the features of periodicity and randomness of machined surface topography, the existing topographical parameters may not describe its features accurately. A novel characterization method called the normal declination angle of microfacet-based surface topography is thus proposed for this task. The topography of machined surfaces is measured and the data on the normal declination angle are obtained. Then, surface topography is analyzed via the distribution of the normal declination angle. The lognormal distribution characterization model of machined surface topography is established, and the accuracy of the model is verified by error analysis. The results show that the calculated results of the present characterization model are generally consistent with the distribution of the normal declination angle, where the maximal root mean square errors (RMSE) is 4.5%. Therefore, this study may serve as an effective and novel way to describe the characteristics of the machined surface topography.

Vision based prediction of surface roughness for end milling

Abstract Measurement of surface roughness helps to assess the machined component's functionality. In the past three decades, several scientists have contributed to the computation of surface roughness. This research article deals with two distinct methods for prediction of surface roughness employing the surface profilometer and machine vision for AISI 1040 steel specimens prepared by varying cutting parameters of end milling viz. feed rates, speed and cutting depth. Using a surface profilometer, the surface roughness parameters are evaluated. At the other hand, the texture features were extracted using a Gray Level Co-occurrence Matrix Algorithm (GLCM) and a computer vision system. Correlations are formed among characteristics of machined surface and the texture feature such as contrast, entropy, energy, and homogeneity. The comparable findings revealed a maximum relative error of −8% using contrast and energy, − 11% using entropy and −10% using homogeneity.

Processing Characteristics of Micro Electrical Discharge Machining for Surface Modification of TiNi Shape Memory Alloys Using a TiC Powder Dielectric.

Titanium-nickel shape memory alloy (SMA) has good biomedical application value as an implant. Alloy corrosion will promote the release of toxic nickel ions and cause allergies and poisoning of cells and tissues. With this background, surface modification of TiNi SMAs using TiC-powder-assisted micro-electrical discharge machining (EDM) was proposed. This aims to explore the effect of the electrical discharge machining (EDM) parameters and TiC powder concentration on the machining properties and surface characteristics of the TiNi SMA. It was found that the material removal rate (MRR), surface roughness, and thickness of the recast layer increased with an increase in the discharge energy. TiC powder’s addition had a positive effect on increasing the electro-discharge frequency and MRR, reducing the surface roughness, and the maximum MRR and the minimum surface roughness occurred at a mixed powder concentration of 5 g/L. Moreover, the recast layer had good adhesion and high hardness due to metallurgical bonding. XRD analysis found that the machined surface contains CuO2, TiO2, and TiC phases, contributing to an increase in the surface microhardness from 258.5 to 438.7 HV, which could be beneficial for wear resistance in biomedical orthodontic applications.

Experimental Investigation Into Micro-Textured Surface Generation by Through-Mask Electrochemical Micromachining

Micro texturing with dimples is one of the most established methods for the enhancement of lubrication and tribological performance. In this work, a novel approach of through-mask electrochemical micromachining is instigated to fabricate high-aspect-ratio circular micro-dimples utilizing a low-cost photoresist (AZ-4903) as mask. Experiments were performed to understand the influence of the applied voltage along with the electrolyte type and concentration on the machining precision and surface characteristics of the generated micro array. The influence of three electrolytes has been studied and it has been experimentally established that 10% NaCl + 10% NaNO3 is favorable during maximization of the depth of the generated micro-dimples to 39.03 µm whereas undercut is minimized to 15.15 µm by utilizing 20% NaNO3. The surface quality of the generated micro-dimples has been found to be the finest, i.e. 0.062 µm, for the samples machined with 10% NaNO3. Patterned arrays containing micro-dimples having maximum depths of 30 μm, 35 μm, and 40 μm were successfully fabricated over a stainless steel (SS304) substrate by using these electrolytes with considerable accuracy and repeatability. The experiments confirm possibility to obtain high-aspect-ratio micro-dimples with the least degree of undercut using this technique. Further, friction test results were analyzed to figure out the alterations in the frictional coefficient of the micro-dimples with different depths as well as with non-dimpled samples.

Tool wear and machined surface characteristics in side milling Ti6Al4V under dry and supercritical CO2 with MQL conditions

Ti6Al4V alloy is a typical difficult-to-cut material. In order to improve its machinability and realize cleaner production, eco-friendly cooling/lubrication techniques are applied. Therefore, this study aims to investigate the tool wear, surface topography, cutting torque, and surface profile in side milling Ti6Al4V under four sustainable conditions, i.e., dry, supercritical carbon dioxide (scCO2), scCO2 with antifreeze water based minimum quantity lubrication (scCO2-WMQL), and scCO2 with oil-on-water based MQL (scCO2-OoWMQL) conditions. A theoretical model of flank wear width VB with average prediction error 15.87% is established. scCO2-OoWMQL reduces VB by 67.2% compared to scCO2 alone due to improved lubricity. Detailed characteristics of machined surface profile are investigated using continuous wavelet transform. The performance of scCO2-OoWMQL as a new sustainable and efficient cooling/lubrication technique is superior to scCO2 alone.