Machining Of AISI Research Articles

An investigation on surface integrity and microstructure behaviour of AISI 304 stainless steel machined by die sinking EDM

Machining of AISI 304 enables the customization of parts to meet specific mechanical and aesthetic requirements, ensuring optimal performance and durability in various applications. In this study, electrical discharge machining (EDM) is introduced to machine AISI 304 stainless steel. To accomplish the desired machining characteristics (MRR, SR), different EDM factors are chosen, such as discharge current, pulse on time, and pulse off time. The experiment is planned using central composite design in response surface methodology (RSM). The impact of EDM variables on metal removal rate (MRR) and surface roughness (SR) is examined through surface plot. Regression coefficient values for MRR and SR are 92.37% and 83.28%, respectively, indicating an empirical relation between the factors and responses. The lack of fit values for MRR and SR were 3.87 and 1.49, respectively, which were lower than the average values. Thus, the developed model was sufficient. It was observed that MRR and SR increases with increase in all parameters, but decreases at higher range of parameters. As current and pulse on time increase, the ionization temperature generated in the machining zone which removed more quantity of materials from the workpiece. Due to ionization temperature, more craters and voids formed which made surface irregular and hard, resulted increased SR. At lower level of discharge current and pulse on time, insufficient spark intensity is developed which made cracks and globules on the surface. The estimated error of actual and expected values for MRR and SR are 7.07% and 5.12% respectively. The desirability of optimization was calculated to be 0.9710, indicating that parameters are within acceptable conditions.

Influence of hybrid nanofluid on tool wear and surface roughness in MQL-assisted face milling of AISI 52100

ABSTRACT With escalating demand for machinability, economical production, health, and environment-related aspects are pushing the present industrial units to drop the usage of harmful-cutting fluid in machining. However, the adaption of this approach for machining difficult-to-cut materials does not ensure favourable outcomes of the tool performance, surface qualities, etc., as friction and heat seriously disturb machining efficiency. This study is focused on near-dry machining employing recently developed hybrid nanofluids-based lubrication in the machining of AISI 52,100 steel. Hexagonal boron nitride (hBN) and silicon carbide (SiC) nanoparticles are added to the lubrication oil to enhance the performance of the Minimum Quantity Lubrication (MQL) system. Taguchi’s method-based Grey relational analysis (GRA) is used for the concurrent optimisation of the tool flank wear and surface roughness. The best parametric setting for the multi-response is achieved as: a lubricant flow rate of 150 ml/h, depth of cut of 0.2 mm, and nanofluid with 0.8 wt % of hBN and 0.2 wt % of SiC nanoparticles. The confirmation experimentation concluded that the multi-response factor is enhanced by 2.48% at the optimum setting with the mean values of TFW and SR as 84 and 0.36 µm, respectively.

A study on the sustainable machining of AISI 630 stainless steel under minimum quantity lubrication

A study on the sustainable machining of AISI 630 stainless steel under minimum quantity lubrication

Wedm Process Optimization for Machining Characteristcis of AISI 52100 Grade Alloy Steel

The present study deals with one of such investigations, which focuses on optimization of the different machining parameters of WEDM for AISI 52100 grade steel. For this work, a standard design of experimentation (DOE) based on Taguchi L27 orthogonal array (OA) has been used by selecting 6 different input parameters of the WEDM for optimization of two output characteristics (surface roughness (Ra) and dimensional deviation (DD). The results suggest that Pulse on Time (Ton): 1µs, Pulse off time: 18µs; Wire Feed (WF): 12mm/min, Spark Gap Set Voltage (SV): 20V, Wire Tension (WT): 1650, and Servo Feed (SF): 8units) are the best condition for the machining AISI 52100 grade steel as the roughness value (Roughness value: 1.02Ra) and dimensional deviation (Dimensional deviation: 0.02) obtained for these settings came to be least. From the result analysis of the current study, the pulse on time (Ton) was ranked at 1st, spark gap voltage came to be as 2nd rank parameter and pulse off (Toff) time was ranked 3rd, and wire tension was ranked at 4th position which significantly contributed towards the wire-EDM machining of AISI 52100 grade steel. Morphological analysis such as semi electron microscopic (SEM) analysis and 3D surface rendering also supported the observed surface and dimensional behaviour.

Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert.

The present study investigates the CNC milling performance of the machining of AISI 316 stainless steel using a carbide cutting tool insert. Three critical machining parameters, namely cutting speed (v), feed rate (f) and depth of cut (d), each at three levels, are chosen as input machining parameters. The face-centred central composite design (FCCCD) of the experiment is based on response surface methodology (RSM), and machining performances are measured in terms of material removal rate (MRR) and surface roughness (SR). Analysis of variance, response graphs, and three-dimensional surface plots are used to analyse experimental results. Multi-response optimization using the data envelopment analysis based ranking (DEAR) approach is used to find the ideal configuration of the machining parameters for milling AISI 316 SS. The variables v = 220 m/min, f = 0.20 mm/rev and d = 1.2 mm were obtained as the optimal machine parameter setting. Study reveals that MRR is affected dominantly by d followed by v. For SR, f is the dominating factor followed by d. SR is found to be almost unaffected by v. Finally, it is important to state that this work made an attempt to successfully machine AISI 316 SS with a carbide cutting tool insert, to investigate the effect of important machining parameters on MRR and SR and also to optimize the multiple output response using DEAR method.

Hard turning of AISI D2 steel with cubic boron nitride cutting inserts

Industries use heat treated steel for various components due to its strength and other mechanical properties. Usually hardening of machining is carried out by energy and cost intensive grinding process. Recently, hard machining has replaced grinding for certain specific applications. In this study, Cubic boron nitride (CBN) of specification CNMG120408is employed to machine AISI D2 steel of 46 HRC hardness. Nine machining experiments established by L9 orthogonal array were conducted. Surface roughness and cutting force were taken as response variables. From the signal to noise ratio analysis, the optimum combination of cutting process parameters for surface roughness is found out to be 80 m/min (Cutting speed) 0.109 mm/rev (Feed) and 0.1 mm (depth of cut). From Analysis of variance (ANOVA), the share made by every process parameter on the machining performance is found out for this CBN tool-work piece combination. Feed rate has the maximum contribution (56 %) for main cutting force while Cutting speed has the maximum contribution (72 %) for surface roughness. Cutting speed exerts greater influence on surface finish compared to feed rate in hard machining.

Optimization of MQL parameters and experimental investigations using vegetable oil-based cutting fluid during machining of AISI 4140

Optimization of MQL parameters and experimental investigations using vegetable oil-based cutting fluid during machining of AISI 4140

Wear Mechanism of Multilayer Coated Carbide Cutting Tool in the Milling Process of AISI 4340 under Cryogenic Environment.

Cryogenic technique is the use of a cryogenic medium as a coolant in machining operations. Commonly used cryogens are liquid nitrogen (LN2) and carbon dioxide (CO2) because of their low cost and non-harmful environmental impact. In this study, the effects of machining conditions and parameters on the wear mechanism were analysed in the milling process of AISI 4340 steel (32 HRC) under cryogenic conditions using a multilayer coated carbide cutting tool (TiAlN/AlCrN). A field emission scanning electron microscope with energy-dispersive X-ray analysis was used to examine the wear mechanisms comprehensively. At low machining parameters, abrasion and adhesion were the major wear mechanisms which occurred on the rake face. Machining at high machining parameters caused the removal of the coating material on the rake face due to the high temperature and cutting force generated during the cutting process. In addition, it was found that continuously adhered material on the rake face would lead to crater wear. Furthermore, the phenomenon of oxidation was also observed when machining at high cutting speed, which resulted in diffusion wear and increase in the crater wear. Based on the relationship between the cutting force and cutting temperature, it can be concluded that these machining outputs are significant in affecting the progression of tool wear rate, and tool wear mechanism in the machining of AISI 4340 alloy steel.

Analysis of surface roughness during Machining of AISI H-13 steel using EDDFG

Electric Discharge Machining (EDM) is well known AMP as it can easily machine the complex shaped, hard, and difficult to machine materials. EDM involves removal of material by thermal erosion, due to which recast layer may be formed and the surface quality may degrade. To reduce recast layer generation and improvement of surface quality, Electric discharge face grinding is developed. Electric discharge face grinding process is a HMP in which material removal occurs by mechanical abrasion as in conventional grinding process and thermal erosion as in EDM. Surface roughness is important aspect in analyzing the surface quality of the processed product. This paper shows the impact of input parameters viz. Ton, Ip, and Toff on ASR during machining of AISI H-13 steel workpiece. Influence of tool RPM on MRR is also studied. After performing experiments using ‘one parameter at a time’ strategy, it was found that by increasing tool RPM, MRR first increases then decreases. It was also found that by increasing Ton & Ip, ASR increases and by increasing pulse off time, average surface roughness first decreases then increases.

Study of the performance of Cu-Gr composite tool during EDM of AISI 1020 mild steel

Copper and graphite are the commonly used tool materials in Electric Discharge Machining (EDM). The use of copper as tool material increases the material removal rate (MRR) of workpiece during EDM. However, the tool wear rate (TWR) of graphite electrode is less as compare to copper electrode. In the current work, an attempt has been made to find the performance of Cu-Gr composite material as EDM tool. Four EDM tools of different copper-graphite composition have been used to machine AISI 1020 mild steel. Both MRR and TWR have been considered to measure the performance of EDM. The results reveal that the increase of graphite percentage in Cu-Gr composite tool reduces TWR up to 83 % by reducing MRR 73%.

Effect of single and hybrid pattern textured tools on turning process performance

ABSTRACT High tool wear, poor product quality, and environmental damage are the outcomes during conventional machining of AISI 316 material with the conventional cutting tool. To minimize these decremental effects, textured tools were developed in the present work and machinability studies were conducted on AISI316 with developed tools under dry and Minimum Quantity Lubrication (MQL) environment. In the present work, single pattern textured tools (T-1 tool) and hybrid pattern textured tools (T-2 tool) were fabricated using laser technology. From the present study, paramount results were found in the MQL condition with textured tools over the dry condition. However, the T-2 tool considerably reduced the cutting temperature (Tc), tool flank wear (Vb), and surface roughness (Ra) to a maximum of 18, 9, and 36% respectively over the T-1 tool under MQL condition. The proposed hybrid textured tools under MQL are a promising technique meeting the demand of higher productivity and sustainability associated with environment and coolant cost.

Modeling of Residual Stresses by Correlating Surface Topography in Machining of AISI 52100 Steel

Abstract The residual stresses could affect the ability of components to bear loading conditions and also the performance. The researchers considered workpiece surface as a plane and ignored the effect of surface topography induced by the intermittent cutting process when modeling residual stresses. The aim of this research develops an analytical model to predict workpiece residual stresses during intermittent machining by correlating the effect of surface topography. The relative motions of tool and workpiece are analyzed for modeling thermal-mechanical and surface topography. The influence of dynamic cutting force and thermal on different positions of surface topography is also considered in the analytical model. Then, the residual stresses model with the surface topography effect can be developed in intermittent cutting. The analytical models of dynamic cutting force, surface topography, and residual stresses are verified by the experiments. The variation trend of evaluated values of the residual stress of workpiece is basically consistent with that of measured values. The compressive residual stress of the workpiece surface in highest point of the surface topography is higher than that in the lowest point.

Thermomechanical finite element simulation and correlation analysis for orthogonal cutting of normalized AISI 9310 steels

A coupled thermomechanical finite element analysis is performed in order to simulate orthogonal cutting of normalized AISI 9310. Damage parameters are optimized to define the behavior of the material subjected to orthogonal cutting. AISI 1045, AISI 4140, and A2024-T351 are selected as precursors to validating the present finite element approach for orthogonal cutting of normalized AISI 9310. The numerical results obtained in this study include the average cutting force, residual stresses and strains, chip morphology, and tool temperature. These results are validated for each material with experimental results found in literature. The current study optimizes the Johnson–Cook damage parameters for steel materials in order to capture physical chip morphology. A correlation analysis is then performed using the validated finite element model for the AISI 9310 material to better understand the effect of specific input parameters such as the damage parameters, coefficient of friction, fracture energy, heat generation fractions and tool velocity on output results such as stresses and strains in the workpiece, chip thickness ratio and tool temperature. This analysis provides input-output relations for a physically reasonable range of input parameters and supports that the damage parameters, coefficient of friction, and fracture energy have a very strong influence on the residual stresses and strains, and the chip morphology. The coefficient of friction has a strong influence of tool temperature. Correlation analysis results can help manufacturers in understanding the nature of residual stresses and distortion, and in choosing optimized process parameters suitable for and applicable to the specific workpiece material. Tool wear that is observed in actual cutting of normalized AISI 9310 is also discussed. This study will benefit the manufacturing industry with the understanding of how specific cutting processing parameters will impact the distortions and residual stresses in the machined AISI 9310 parts.

Experimental Investigation of the AISI H-13 die steel by Wire-Cut EDM

The current study is done to provide a comprehensive report on the machining of AISI H-13 Die Steel with bare and coated wire electrodes. The study is carried out for the pulse duration-on time and pulse duration-off time process parameters effect on both electrodes and surface roughness is taken as response parameter of material along with the best viable combination of process parameter for machining.

Decision making on the machining parameters of Electrical Discharge Machined AISI D2 tool steel by AHP and PROMETHEE method

This paper determines the optimum process parameters of the non-conventional electrical discharge machining (EDM). The performance of the EDM machine depends upon the process parameter used. In this analysis weight percentage, pulse current (Ip), discharge voltage (V) and pulse duration (Ton) used as process parameters. The optimized output parameters are MRR, TWR, surface roughness and flatness. By using face centered composite design nine trials were conducted on the work piece which is made up of AISI D2 tool steel. The trial results obtained were used in AHP and PROMETHEE multi attribute decision making method. The weights of the responses were determined by the AHP method and select the best alternative by AHP and PROMETHEE method. machining parameters and accuracy of the component produce by EDM can be control by using the obtained results

Influence of biodegradable lubricant on the ecology, lubrication, and machining process in minimum quantity lubrication

In minimum quantity lubrication (MQL) processing, lubricating oil is passed through the air flow field in the form of oil droplets. The oil droplets penetrate the field and are adsorbed by it to form a film in the capillary tube at the workpiece–tool interface. Therefore, the type, atomization, penetration, and adsorption of the lubricating oil have crucial influences on the lubrication quality. Three types of lubricant—trimethylolpropane trioleate, vegetable oil, and polyethylene glycol—were used in this research. To protect the environment and meet application requirements, the biodegradability, oxidation stability, and placement stability of the aforementioned three oils were tested in accordance with the relevant national standard. The biodegradation rate and storage stability of vegetable oil 6000 were high; however, its oxidation stability was poor. A three-dimensional particle dynamic analyzer was used to measure the atomization of oil droplets, and the amount of oil penetrating the tool–workpiece contact area was quantitatively evaluated using a specially designed penetration sampling device. The contact angles of the droplets on AISI 1045 carbon steel and TiN coating were measured, and experiments were performed on the MQL machining of AISI 1045 carbon steel. According to the experimental results, the main cutting force, coefficient of friction, surface morphology, and roughness obtained using vegetable oil 6000 were superior to those obtained using polyethylene glycol 400 and trimethylolpropane trioleate, because a more focused oil drop distribution, higher amount of penetrated oil, and higher wettability were obtained with vegetable oil 6000.

Optimizing process parameters of die sinking EDM in AISI D2 steel by using TOPSIS using EDM oil as dielectric

A prodigious research work is being effectuated to endorse the optimal machining parameters while entailing present day machining techniques to bring outclassy products. This research work insisted on suggesting the optimum process parameters of die sinking EDM with 8mm diameter copper electrode during machining AISI D2 steel using TOPSIS.Taguchi’s L9 Orthogonal Array method was adopted to design 9 experiments in total and Pulse on time (Ton), Servo voltage (SV) and Peak current (IP) are chosen as input parameters. Three levels of each parameter were selected for designing the experimentation. EDM oil which is a synthetic oil is selected as dielectric and all the values of Material Removal Rate (MRR), Tool Wear Rate (TWR) and Surface Roughness (SR) for each experiment were noted as the output responses. Analysis of Variance (ANOVA) was done to recommend the impact of each input parameter on output responses. Analytical Hierarchy Process (AHP) was used to select the weightage of each response and then Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which is a multi-criteria decision analysis method, was accompanied for determination of ideal parameters for machining AISI D2 steel. Eventually it is descried that the amalgamation of level 3 of pulse on time, level 3 of Peak Current and level 3 of servo voltage propounds the optimum result.

Parametric Optimization of Die Sinking EDM in AISI D2 Steel considering Canola oil as Dielectric using TOPSIS and GRA

A colossal research work is being consummated to propose the optimal machining parameters while necessitating current machining techniques to attain elegant products. This research work foregrounded the optimum process parameters of die sinking EDM with 8mm diameter copper electrode during machining AISI D2 steel. Taguchi’s L9 OA method was adopted to design 9 experiments in total and Pulse on time (Ton), Servo voltage (SV) and Peak current (IP) are chosen as input parameters. Three levels of each parameter were selected for designing the experimentation. A natural vegetable oil named Canola oil which is an extract from Canola seeds is taken as dielectric and all the values of Material Removal Rate (MRR), Tool Wear Rate (TWR) and Surface Roughness (SR) for each experiment were noted as the output responses. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Grey Relational Analysis (GRA) which are two Multi-Criteria Decision Making (MCDM) methods were accompanied for determination of ideal parameters for machining AISI D2 steel. Ultimately it is espied that the coalescence of level 3 of pulse on time, level 2 of Peak Current and level 2 of servo voltage propounds the optimum result by performing TOPSIS and GRA.

Surface integrity of machined AISI D2 steel and its effect on the adhesion of a PVD-AlCrN coating

The permanent importance of molds and dies in the industry motivates new studies to obtain optimized parameters and processes, which contribute to the reduction of their wear and increase of their life cycle. Regarding this, coated forming tools are often applied and this paper aims to investigate the influence of the surface preparation of hardened AISI D2 steel substrate on the adhesion characteristics of an AlCrN coating deposited by physical vapor deposition (PVD). For this, an end milling process with different cutting conditions was applied and the coating was tested by indentation and scratch tests. From the obtained results, it could be observed that cermet cutting inserts used in milling process led to higher compressive residual stresses and lower roughness values in the substrate in comparison to cemented tungsten carbide inserts, increasing the critical load required for coating failure. Although scratch tests demonstrated enough sensitivity to differentiate substrate surface properties, indentation tests had no success.

Optimization of EDM process parameters using TOPSIS for machining AISI D2 steel material

There is a tremendous scope for research work that is being carried out to recommend the optimal machining parameters while involving latest machining techniques to produce high quality products. This research work emphasised on suggesting the optimum process parameters of die sinking EDM with 8 mm diameter copper electrode during machining AISI D2 steel using TOPSIS.Taguchi’s L9 OA method was adopted to design 9 experiments in total and Pulse on time (Ton), Servo voltage (SV) and Peak current (IP) are chosen as input parameters. Three levels of each parameter were selected for designing the experimentation. A non-volatile oil extracted from the seeds of Helianthus annuus namely sunflower oil was picked as dielectric and the values of Material Removal Rate (MRR), Tool Wear Rate (TWR) and Surface Roughness (SR) for each experiment were noted as the output responses. Analysis of Variance (ANOVA) was done to recommend the impact of each input parameter on output responses. Analytical Hierarchy Process (AHP) was used to select the weightage of each response and then Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which is a multi-criteria decision analysis method, was accompanied for determination of ideal parameters for machining AISI D2 steel. Finally it is observed that the combination of level 3 of pulse on time, level 2 of Peak Current and level 2 of servo voltage suggests the optimum result.