Mm Depth Of Cut Research Articles

Investigation of the effect of vibration in the multi-objective optimization of dry turning of hardened steel

PurposeThis study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.Design/methodology/approachIn this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).FindingsThe optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.Research limitations/implicationsThe MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.Originality/valueMost studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.

Utilization of Minimum Quantity Lubrication (MQL) Chip Fan on SS304 During Milling Process to Increase Carbide Tool Life

Minimum quantity lubrication (MQL) is the most used recent method in the milling process that is economical and environmentally friendly. The MQL method can reduce the temperature during the milling process. The high temperature that occurs in the carbide tool will affect the tool’s life. The use of cooling fluid is a common method to reduce high temperatures. However, the remaining cooling fluid has an impact on the pollution of the environment. Therefore, in this study, a novel approach for a cooling system based on the combined MQL method and fan cooling device was introduced and called an MQL Chip fan. The effect of the MQL Chip fan on the temperature, tool life, and surface roughness was investigated. The Taylor equation was used to calculate tool life based on temperature data from an experimental investigation. Subsequently, the quality inspection was conducted by using a surface roughness tester. The spindle speed and depth of cut have proven to make a great impact on the peak temperature, but, there is an optimal point where spindle speed made a turbulence and the tool had a passive cooling system. The utilization of the MQL Chip fan has decreased temperature by more than half at a medium speed of 2241 rpm and made a high contribution for low-speed processing and only a slight contribution for high-speed processing. Based on Tool Life prediction, 3600 RPM with a 3 mm depth of cut has more efficient performance compared to 2241 rpm with the same depth of cut. The utilization of the MQL Chip fan contributes significantly to the roughness value; the Ra value decreased from 1.374 μm to 0.461 μm. It has been proven that the utilization of an MQL Chip fan in the milling process reduces temperature and also increases the tool life.

Performance of Al2O3/TiO2 Hybrid Nano-Cutting Fluid in MQL Turning Operation via RSM Approach

Cutting fluids can be used to cool workpieces at high cutting speeds and remove chips from cutting zones. The effectiveness of cutting fluids may be improved with the addition of hybrid nanoparticle dispersion. This study evaluates the effectiveness of an Al2O3-TiO2 hybrid as a cutting fluid in turning operations. The Al2O3-TiO2 hybrid nano-cutting fluid was prepared using a one-step method in computer numerical control (CNC) coolant with concentrations of up to 4%. Utilizing air-assisted nano-cutting fluids injected through a minimum quantity lubrication (MQL) setup, the effectiveness of turning cutting performance, cutting temperature (°C), average surface roughness (Ra), and tool wear (%) were evaluated. Then, the response surface method (RSM) was utilized as the design of experiment (DOE) to optimize the turning cutting performance parameters. The combination of 4% hybrid nano-cutting fluid concentration, 0.1 mm/rev feed rate, and 0.55 mm depth of cut yielded the lowest cutting temperature, surface roughness, and tool wear values of 25.3 °C, 0.480 µm, and 0.0104%, respectively. The 4% concentration of Al2O3/TiO2 hybrid nano-cutting fluid inclusion achieved the highest surface roughness reduction that led to better surface finish and the lowest tool-wear reduction led to longer tool life. Therefore, Al2O3/TiO2 hybrid nano-cutting fluids were strongly recommended in turning operations for CNC lathes.

Cost and Quality Optimization Taguchi Design with Grey Relational Analysis of Halloysite Nanotube Hybrid Composite: CNC Machine Manufacturing.

Researchers who work on manufacturing hybrid composites have significant concerns about holistically optimizing more than one performance characteristic, as in the case of cost and quality optimization. They usually trade off one for the other. Hence, this study employed statistical tools and grey relational analyses (GRA) design to model and optimize the surface roughness and cutting force of Computer Numerical Control (CNC) machine settings to manufacture halloysite nanotube hybrid composite. In this paper, the GRA was able to address the multiple optimization complications by producing 0.6 mm depth of cut, 1500 rpm spindle speed, and 40 mmpm feed rate as the CNC machine settings for high-quality and low-cost hybrid composite. It was noticed that the mathematical and interaction modeling of surface roughness, cutting force, and grey relational grade (GRG) allowed different CNC machines to manufacture hybrid composites. This can assist researchers and production engineers of CNC machines. Variance analysis and delta statistical characteristics revealed that the depth of a cut is the most significant machine setting, with a contribution of 49.12%. This paper outlines the possible CNC machine settings for high-quality composite manufacturing. In future studies, it is recommended for researchers in the field of CNC machine manufacturing to consider the modeling analysis aspect of the optimization, which comprehensively provides the opportunity for the adjustment of CNC machines for better material performance, which has been lacking in the literature.

Mechanical, chemical, metallurgical characteristics under HBSS solution and optimization of AZ91D-Ti functional graded composites using TOPSIS

ABSTRACT. Functional graded magnesium matrix composites (FGMMCs) are widely employed for biomedical, aerospace and thermal barrier applications because of their better mechanical properties, biocompatibility and bioactivity. In this study, AZ91D-wt. %Ti (x = 0, 4, 8, 12 and 16) composites are fabricated by ex-situ centrifugal casting method. The NaCl based solution is sprayed on all fabricated magnesium composites for 72 hours at the 1 kg/cm3 pressure spray and 6.9 pH value in salt spray chamber. The microhardness and flexural strength of fabricated composites are determined. The corrosion resistance of AZ91D-wt. %Ti fabricated composites is determined for 21 days immersion. The AZ91D -12wt. %Ti exhibits higher microhardness, flexural strength and corrosion resistance than other produced AZ91D-Ti composites. The optimization on micro machining process parameters is done on the AZ91D-12wt. %Ti with the help of Technique for order of preference by similarity to ideal solution (TOPSIS).The input process parameters are selected as cutting rate, feed rate, depth of cut and tool type and the response parameters are selected as feed force, normal force, tool wear rate, burr height and surface roughness. The computed optimal micro milling process parameters are at 120 m/min cutting speed, 0.5 µm feed rate, 0.15 mm depth of cut and the TiB2 coated tool.
 
 KEY WORDS: AZ91D -Ti, TOPSIS, Surface roughness, Tool wear loss, Cutting force
 
 Bull. Chem. Soc. Ethiop. 2023, 37(1), 77-89. 
 DOI: https://dx.doi.org/10.4314/bcse.v37i1.7

Effectiveness of hybrid Al2O3-TiO2 nano cutting fluids application in CNC turning process

The purpose of this study is to evaluate the effectiveness of hybrid Al2O3-TiO2 nano-cutting fluid in the turning process application under the selected significant machining parameters consisting of nano concentration, depth of cut and feed rate. The preparation of aqueous hybrid Al2O3-TiO2 water-based nano-cutting fluids and their application as the cutting fluid in turning operations are undertaken. The Al2O3-TiO2 hybrid nano-cutting fluids were prepared through a one-step method; by dispersing nanoparticles of Al2O3 (average diameter 30 nm) and TiO2 (average diameter 30-50 nm) in CNC coolant based at four different volume concentrations (1%, 2%, 3%, 4%). The effectiveness of turning cutting performance, namely cutting temperature (°C), average surface roughness (Ra), and tool wear (%), were assessed via air-assisted nano cutting fluids impinged through MQL setup in turning of Aluminium Alloy AA7075. The response surface method (RSM) was employed in the design of the experiment (DOE). The lowest cutting temperature, surface roughness, and tool wear of 25.8°C, 0.494 µm, and 0.0107%, are obtained, respectively, when the combinations of hybrid nano cutting fluid concentration of 4%, feed rate value of 0.1 mm/rev, and 0.3 mm depth of cut is used. The result in this paper is based on the experimental study of Al2O3-TiO2 hybrid nano-cutting fluid using CNC turning operation. The process focuses on the finishing process by using a finishing insert. Further work using roughing process may be suggested to observe the better performance of this cutting process using nano-cutting fluid towards reducing the wear rate. The use of Al2O3-TiO2 hybrid nano-cutting fluid coupled with MQL in the CNC turning process is considered a new method. Machining soft and delicate materials such as Aluminium should consider using this combination technique since it lowers the cutting temperature and removes the chips, reducing the adhesive wear. The hybrid nano-cutting fluid can replace the conventional cutting fluid and will perform better if combined with the MQL cooling technique; this new method should be considered by major industry players that require a high-precision finished product such as the product that involves aircraft and aerospace applications.

Experimentation and Optimization of Milling Machine Parameters Using Taguchi Method

In this research work, the problem is to reduce the surface roughness of the Jacquard body which is a casting part to optimize the effects of different process parameters of surface roughness & to reduce surface roughness for milling operation by using the Taguchi method. Milling is better than other machines in the surface finish and accuracy. Greater quality product and higher productivity is the main vision of every entrepreneur. To achieve this, the process parameters of each process need to be optimized. In a milling machine, some of the important parameters like feed rate, depth of cut, speed, etc, play an important role in achieving the required quality product. To optimize these parameters, the most suitable and widely used method is the Taguchi method. The most significant objective of this research is to obtain effective quality parameters. Experimentation is done on the Jacquard body by varying the milling machine parameters. The experimental results indicate that the minimum surface roughness is obtained for the process parameters feed 0.7 mm per revolution, speed 225 rpm and 1.5 mm depth of cut. This study recommended that more surface finish be obtained by increasing speed, low feed rate, and depth of cut.

Study on machinability characteristics of novel additive manufactured titanium alloy (Ti-6Al-4V) fabricated by direct metal laser sintering

The pressing demand of Ti-6Al-4V (grade 5) in aerospace, medical, marine, and chemical processing industries has gained momentum in recent years due to its excellent properties such as high strength to weight ratio and corrosion resistance, bio-compatibility and a common material for additive manufacturing. Additive manufactured Ti-6Al-4V have higher mechanical properties as compared to wrought alloys due to difference in microstructure that negatively influences the machinability characteristics and also lacks ductility. The main limitation of fabricated additive manufactured (AMed) component is the poor surface quality, staircase effect and adhering of non-melted powder particles to the fabricated components. Again, fatigue life of components increases with decrease of surface roughness. Therefore the need of machining of AMed titanium alloys in recent years are gaining importance to eliminate these problems so that desired surface quality and tolerances can be achieved. Therefore the objective of the study is to develop additive manufactured Ti-6Al-4V through direct metal laser sintering process and investigate its machinability characteristics under flood cooling environment with respect to responses as tool wear, surface roughness, cutting temperature, and chip morphology. As most of the heat generated at the interfaces has been carried away through flood cooling, the rate of growth of tool wear, cutting temperature, surface roughness, and degree of serration decreases and thus makes the performance of AMed Ti alloys are comparable with wrought Ti alloys. The dominant tool wear mechanism during machining AMed Ti alloy have been found to be abrasion, chipping, adhesion, BUE, chemical interaction between titanium and cutting tool materials, coating delamination. Optimal parameters for multi-responses are 0.1 mm depth of cut, 0.1 mm/rev feed rate, and 70 m/min cutting speed and improved. Mathematical models are said to be significant and fitted well. Because of the improved machinability, AMed Ti alloys find itself suitable in industrial applications.

Assessment of sustainable dry and MQL-assisted hard machining using MTCVD multilayered coated carbide (TiN/TiCN/Al2O3) insert

ABSTRACT The application of minimum quantity lubrication (MQL) provides cooling, chip flushing and environment-friendly functions for sustainable manufacturing. Thus machinability study and surface characterisation of hardened AISI 4340 steel have been performed through multilayered coated MTCVD carbide (TiN/TiCN/Al2O3) insert under different cutting environments i.e. dry and MQL for sustainable machining. Flank wear in both cases (dry and MQL) is within the 0.2 mm failure criterion. Cutting speed influences more on flank wear more under dry conditions (65.26%), whereas depth-of-cut is for MQL (69.10%). Feed rate is the most significant parameter for surface roughness i.e. 73.40% and 75.96% contribution under dry and MQL, respectively. Average absolute errors for both artificial neural network (ANN) and regression models lie within 5%, with ANN giving better predictions. At 0.1 mm depth of cut, 0.04 mm/rev feed rate and 50 m/min cutting speed, tool life is 176.55 and 217.16 min (23% greater) in dry and MQL, respectively. In another condition of 0.1 mm depth of cut, 0.04 mm/rev feed rate and 100 m/min cutting speed, tool life under dry and MQL is 80.2 min and 131.2 min which contributes 63.6% greater than dry condition. MQL enhances the tool life and improves machinability and contributes towards sustainability.

Investigation of machinability properties of AISI H11 tool steel for sustainable manufacturing

In this experimental study, vibration, energy consumption, power consumption and surface roughness values that occur in the machining of AISI H11 tool steel under CO2, coolant and dry cutting conditions were investigated. The effects of different cutting parameters and cooling systems on machinability were investigated. Analysis of variance was done. Regression equations were obtained. Relationships between power consumption, vibration and surface roughness are explained with mathematical equations. Finally, the optimum CC were determined by the multiple optimization methods. According to the test results, while the instantaneous power consumption increases by increasing cutting parameters, energy consumption decreases as the processing time is shortened. Vibration value increases by increasing cutting parameters. The highest vibration value occurs in cutting with CO2. Compared to dry and CO2 cutting, the vibration is lowest in coolant cutting. The friction decreases with the coolant and the vibration value decreases. There is a similar relationship between vibration and surface roughness value. The most effective parameter on the surface roughness value is the feed rate. It was seen that the most suitable CC for the most efficient cutting, the lowest energy consumption, vibration and surface roughness value, under coolant cutting, 0.2 mm depth of cut, 175 m/min cutting speed and 0.119 mm/rev feed rate. With optimum CC, the vibration value was reduced by 5.18%, the surface roughness value by 37.12%, energy consumption by 36.19% and the machine efficiency was increased by 7.16%.

Research on optimization of cutting force in AISI D2 hardened steel ultrasonic vibration-assisted turning

This study utilized the self-developed ultrasonic vibration-assisted turning system to conduct turning experiments on AISI D2 hardened steel. The investigation is carried out by the Robust Design method via controlling different ultrasonic vibration-assisted turning factors and levels, including feed rate, spindle speed, depth of cut, and the magnitude of amplitude of the ultrasonic vibration tool tip. This study is carried out with optimal cutting force by the Robust Design goals. The optimal combination is A1 (0.5 mm depth of cut) B1 (0.08 mm/rev feed rate) C3 (20 μm amplitude) D2 (885 rpm spindle speed). The cutting force is 119.85 N which hugely decreased 28.6% by comparing with the lowest group. Through analysis of variance, the depth of cut and feed rate play a dominant role in cutting force. These two factors are used for obtaining the difference of cutting force and tool wear by comparing the two factors at different levels. The experimental results show that the optimal depth of cut and feed rate can be reduced by 15.8% and 28.4% in cutting force, and 72% and 81% in tool wear compared with other levels. When turning AISI D2 hardened steel, ultrasonic vibration-assisted turning systems can greatly improve the turning efficiency.

Experimental investigation into face milling of Inconel X750 super alloy: a study on cutting force and surface topography

PurposeThis work aims to describe the face milling analysis on Inconel X-750 superalloy using coated carbides. The formed chips and tool wear were further analyzed at different cutting parameters. The various impact of cutting parameters on chip morphology was also analyzed. Superalloys, often referred to as heat-resistant alloys, have exceptional tensile, ductile and creep strength at high operating temperatures and good fatigue strength, and often better corrosion and oxidation resistance at extreme heat. Because of these qualities, these alloys account for more than half of the weight of sophisticated aviation, biomedical and thermal power plants today. Inconel X-750 is a high-temperature nickel-based superalloy that is hard to machine because of its extensive properties. At last, the discussion regarding the tool wear mechanism was analyzed and discussed in this article.Design/methodology/approachThe machining parameters for the study are cutting speed, feed rate and depth of cut. One factor at a time approach was implemented to investigate the effect of cutting parameters on the cutting forces, surface roughness and material removal rate. The scatter plot was plotted between cutting parameters and target functions (cutting forces, surface roughness and material removal rate). The six levels of cutting speed, feed rate and depth of cut were taken as cutting parameters.FindingsThe cutting forces are primarily affected by the cutting parameters, tool geometry, work material etc. The maximum forces Fx were encountered at 10 mm/min cutting speed, 0.15 mm/rev feed rate and 0.4 mm depth of cut, further maximum forces Fy were attained at 10 mm/min cutting speed, 0.25 mm/rev feed rate and 0.4 mm depth of cut and maximum forces Fz were attained at 50 mm/min cutting speed, 0.05 mm/rev feed rate and 0.4 mm depth of cut. The maximum surface roughness value was observed at 40 mm/min cutting speed, 0.15 mm/rev feed rate and 0.5 mm depth of cut.Originality/valueThe effect of machining parameters on cutting forces, surface roughness, chip morphology and tool wear for milling of Inconel X-750 high-temperature superalloy is being less researched in the present literature. Therefore, this research paper will give a direction for researchers for further studies to be carried out in the domain of high-temperature superalloys. Furthermore, the different tool wear mechanisms at separate experimental trials have been explored to evaluate and validate the process performance by conducting scanning electron microscopy analysis. Chip morphology has also been evaluated and analyzed under the variation of selected process inputs at different levels.

EVALUATION OF ENERGY CONSUMPTION, CUTTING FORCE, SURFACE ROUGHNESS AND VIBRATION IN MACHINING TOOLOX 44 STEEL USING TAGUCHI-BASED GRAY RELATIONAL ANALYSIS

This paper presents the Toolox 44 steel’s experimental and statistical machinability optimizations conducted for achieving minimum output parameters (energy consumption ([Formula: see text]), cutting force ([Formula: see text]), surface roughness ([Formula: see text]), and vibration (Vib)). Turning experiments have been performed under dry machining conditions on a CNC lathe at different cutting parameters according to the Taguchi L27 orthogonal array. Taguchi-based gray relational analysis (GRA) has also been used to optimize output parameters simultaneously. Moreover, analysis of variance (ANOVA) has been applied to determine the effects of cutting parameters on output parameters. As a result, the lowest Ec was measured 0.06 kW at the 1.5 mm depth of cut, 220 m/min cutting speed and 0.4 mm/rev feed rate. At 0.5 mm depth of cut, 220 m/min cutting speed and 0.1 mm/rev feed rate, the lowest [Formula: see text], [Formula: see text] and Vib are measured at 132.28 N, 0.69 [Formula: see text]m and 2.25 m/s2, respectively. According to GRA, the best machining combination in terms of energy consumption ([Formula: see text]), cutting force ([Formula: see text]), surface roughness ([Formula: see text]), and vibration (Vib) was A1B3C1, and the percentage of improvement in the gray relational degree has been calculated to be 25.25%. Validation test results showed that the optimization of cutting parameters was successful in the machining process of Toolox 44 steel according to the multiple output parameter values.

Optimization of process parameters in turning of magnesium AZ91D alloy for better surface finish using genetic algorithm

This research examined at the optimum cutting parameters for producing minimum surface roughness and maximum Material Removal Rate (MRR) when turning magnesium alloy AZ91D. Cutting speed (m/min), feed (mm/rev), and cut depth (mm) have all been considered in the experimental study. To find the best cutting parameters, Taguchi's technique and Response Surface Methodology (RSM), an evolutionary optimization techniques Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed. GA gives better results of 34.04% lesser surface roughness and 15.2% higher MRR values when compared with Taguchi method. The most optimal values of surface roughness and MRR is received in multi objective optimization NSGA-II were 0.7341 µm and 9460 mm3 /min for the cutting parameters cutting speed at 140.73m/min, feed rate at 0.06mm/min and 0.99mm depth of cut. Multi objective NSGA-II optimization provides several non-dominated points on Pareto Front model that can be utilized as decision making for choice among objectives

EFFECT OF CUTTING PARAMETERS ON LOW CARBON STEEL SURFACE ROUGHNESS IN THE CONVENTIONAL TURNING PROCESS

In the turning process, the surface roughness is affected by cutting parameters such as cutting speed, depth of cut, feed rate, and so on. However, there is not much information about the relationship or interaction between cutting parameters and the resulting surface roughness. This study aimed to examine the effect of cutting parameters on the surface roughness value of low carbon steel. This research was conducted experimentally using a conventional lathe with a HSS insert without the use of cutting fluids. It was concluded that the cutting parameters had a significant effect on the surface roughness. The lowest surface roughness value was obtained at 280 rpm spindle speed, 0.5 mm depth of cut and 0.2 mm/rev. feed rate with a roughness value of 2.968 µm. The contribution of each parameter to the surface roughness were 42.2% of spindle speed, 10% of depth of cut and 20.3% of feed rate respectively.

Evaluation of Mango Kernel Seed (Mangifera indica) Oil as Cutting Fluid in Turning of AISI 1525 Steel Using the Taguchi-Grey Relation Analysis Approach

The hunt for environmentally friendly cutting fluids is underway as the problems of conventional cutting fluids become more evident. To achieve environmentally conscious machining, the current study examines the use of Mango Kernel Seed Oil (MKSO) as a cutting fluid during the turning of AISI 1525 steel. According to the 24 complete factorial techniques, the vegetable-oil-based cutting was produced by dissolving four different additives in mango kernel seed oil: emulsifying, antimicrobial, anti-corrosive, and antifoam substances. Afterward, the formulated vegetable oil was characterized both physically and chemically to determine its capability. The developed MKSO was mechanically evaluated using a Taguchi L9 orthogonal array. Spindle speed, depth of cut, and feed rate served as the input parameters, while surface roughness, cutting temperature, machine sound level, and machine vibration rate were the responses. Taguchi-based Grey Relational Analysis was used to perform multi-objective optimization. It was used to determine the best machining conditions. The best parameters for mango kernel seed oil are a spindle speed of 0.683 rev/min, feed of 0.617 mm/rev, and depth of cut of 0.620 mm, while the optimum parameter for Mineral-Oil-based Cutting Fluid (MOCF) is 0.7898 rev/min spindle speed, 0.6483 mm/rev feed, and a 0.6373 mm depth of cut. This research revealed that, when compared to the feed rate and the depth of cut, the spindle speed has the highest influence on multi-responses in turning operations with both cutting fluids. Generally, MOCF outperformed mango kernel seed cutting fluid in most machining conditions.

Study on the influence of heat treatment process on machinability behaviour of aluminium alloy 6060

In this work, the impact of full annealing heat treatment process on the machinability behaviour of Aluminium alloy 6060 has been studied elaborately. The samples were kept at 300 degree celsius (6 h) and subsequent cooling process was done at room temperature. Three levels in three input parameters (Spindle speed 300, 600, 900 rpm, Feed rate 0.05, 0.10, 0.15 mm/rev and Depth of Cut 0.50, 1.00, 1.50 mm) and two output parameters (Material Removal Rate and Surface Roughness) were selected for this study. 17 experimental runs were used in this study for optimization process. The experiments were conducted at CNC lathe using HSS tool and the results were compared between the heat treated and non - heat treated samples. The heat treated samples showed 34.67% better MRR and 11% reduction in surface roughness than non - heat treated samples. The optimal results in heat treated workpiece was achieved at 893 rpm spindle speed, 0.15 mm/rev feed rate, 1.5 mm depth of cut. The confirmatory test was conducted and the results obtained shows negligible error percentage which further extends the scope of this study in real applications like railings, motor housings, and heat sinks.

Investigation on surface defect machining of AISI 4340 steel

Hardened steel turning is now an issue due to the needed less machining force and surface roughness. Due to it having medium carbon (0.4% C) it is high strength martensitic steel. AISI 4340 steel has been utilized for this experiment on surface defect machining (SDM). In demanding applications such as aerospace and automotive transmissions, this material is particularly significant. In order to machine ferrous alloy having a hardness of over 45 HRC, for removing the material cutting tool with single point operating at high speeds. A typical approach is used to process hard steel, and those procedures require a large amount of money and time. The need for annealing and grinding is eliminated when compared with surface defect machining. Researchers are keeping on looking for the ideal amalgamation of inserts in HT, where the life of the tool is important because of the expense and the desire for a superior surface finish. For finding the most ideal parameters for surface defect machining by considering input parameters such as feed rate, depth of cut, and cutting speed. Taguchi technique was utilized with an L9 orthogonal array and for ANOVA the Grey Relational Analysis (GRA) has been used. The results were obtained by performing Surface Defect Machining on hardened AISI 4340 steel. For this typical Surface Defect Machining, the Grey relation grade is used with the thought of machining force and Surface Roughness (SR) as the level of variables and the best combinations has found as 0.05 of feed mm/rev, 0.5 mm depth of cut and 900 rpm of cutting speed.

Influence of tool geometry on cutting zone temperature during turning of aluminium alloy AA2219

Machining of aluminium alloys is considered to be highly important owing to their wide spectrum of applications. Analysis of machinability with respect to the cutting zone temperature decides the behaviour of the material when used in various functional areas. Current research aims to investigate the cutting zone temperature during the turning of aluminium alloy using cemented carbide inserts. From the results, it could be noted that the feed and nose radius were the most dominant factors which influenced the cutting zone temperature. A regression model was developed by using the Taguchi’s full factorial design of experiment. Cutting zone temperature regression model exhibited least deviation when compared with the actual response within the range of considered turning process parameters. The adequacy and accuracy of the regression equation was justified by using a comparative study. It was found that the optimal combinations of machining parameters to minimize the temperature were 0.4 mm nose radius, 0.1 mm/rev of feed rate, 1500 rpm speed and 0.3 mm depth of cut.

Parametric analysis and simulation of surface roughness and tool flank wear in machining of low carbon alloy steel

Austenitic SS influences in most frequently applied corrosion resistance or in higher surface loading were it is required. The present investigation represents the quality attributes namely surface roughness and tool wear rate in turning of AISI 316L steel using DoE. Taguchi method has been employed with L9 (34) orthogonal array of the three significant factors, i.e., speed, feed and depth of cut, to achieve the minimum surface roughness and tool wear rate. The Analysis of variance was performed to identify the influencing factors which affect the responses. The outcomes from the research reveal that the minimum surface roughness was achieved at cutting speed 170 m/min, feed rate 0.10 mm/rev, depth of cut 0.15 mm and the minimum too wear rate was attained at 170 m/min cutting speed, 0.07 mm/rev feed rate and 0.15 mm depth of cut was determined using the experimental study and compared with the prediction model from design of experiments. The results shows that both the values were good in agreement with experimental as well as prediction results.