Turning is one the most important machining operation in industries. The process of turning is influenced by many factors such as the cutting velocity, feed rate, depth of cut, geometry of cutting tool cutting conditions etc. The finished product with desired attributes of size, shape, and surfaceroughness and cuttingforces developed are functions of these input parameters. Properties wear resistance, fatigue strength, coefficient of friction, lubrication, wear rate and corrosion resistance of the machined parts are greatly influenced by surfaceroughness. Forces developed during cutting affect the tool life hence the cost of production. In many manufacturing processes engineering judgment is still relied upon to optimize the multi-response problem. Therefore multi response optimization is used in this study to optimization problem to finds the appropriate level of input characteristics.
Kohli and Dixit (2005)  proposed a neural-network-based methodology with the acceleration of the radial vibration of the tool holder as feedback. For the surfaceroughness prediction in turning process the back-propagation algorithm was used for training the network model. The methodology was validated for dry and wet turning of steel using high speed steel and carbide tool and observed that the proposed methodology was able to make accurate prediction of surfaceroughness by utilizing small sized training and testing datasets. Pal and Chakraborty (2005)  studied on development of a back propagation neural network model for prediction of surfaceroughness in turningoperation and used mild steel work-pieces with high speed steel as the cutting tool for performing a large number of experiments. The authors used speed, feed, depth of cut and the cuttingforces as inputs to the neural network model for prediction of the surfaceroughness. The work resulted that predicted surfaceroughness was very close to the experimental value.
Turningoperation is one of the most important machining operations to be carried out in different industries for manufacturing of various products. As it is a basic operation for various industries it is very essential to optimize the various parameters affecting turningoperation for the optimum operating condition. Turningoperation is affected by both cuttingparameters and geometrical parameters. The parameter influence most are cutting velocity, depth of cut , feed rate, geometry of cutting tool like principle cutting edge angle ,rake angle, nose radius etc. In order to control surfaceroughness and cutting force acting on material during turningoperation it is very necessary to control these parameters as the product with desired attributes are function of these parameter.
The present study highlights a multi response optimization approach to determine the optimal process parameters in wire electrical discharge machining process during taper cuttingoperation. Experiments have been conducted using six process parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension each at three levels for obtaining the responses like angular error, surfaceroughness, and cutting speed. Taguchi’s L 27 orthogonal array is used to gather information regarding the process with less number of experimental runs. Traditional Taguchi approach is insufficient to solve a multi response optimization problem. In order to overcome this limitation, utility theory has been implemented, to convert multi-responses into single equivalent response called overall utility index. The weight for each criterion (response) is obtained by analytical hierarchy process (AHP) instead of using intuition and judgement of the decision maker. ANOVA analysis is also carried out to find out the significant effect of the process parameters during taper cutting in WEDM process. Finally confirmation test has been carried out to verify the result.
P.V.S. Suresh et al. , The experimentation was carried out with TiN-coated tungsten carbide (CNMG) cutting tools, for machining mild steel work-pieces covering a wide range of machining conditions. W.S. Lin et al. , an abductive network is adopted to construct a prediction model for surfaceroughness and cutting force. M.Y. Noordin et al. , The performance of a multilayer tungsten carbide tool was described using response surface methodology (RSM) when turning AISI 1045 steel. D.I. Lalwani et al. , In the present study, an attempt has been made to investigate the effect of cuttingparameters (cutting speed, feed rate and depth of cut) on cuttingforces (feed force, thrust force and cutting force) and surfaceroughness in finish hard turning of MDN250 steel [equivalent to 18Ni(250) maraging steel] using coated ceramic tool. Davim. J et al. , presents a study of the influence of cuttingparameters on surfaceroughness in turning of glass-fibre-reinforced plastics (GFRPs). Dilbag Singh et al. , An experimental investigation was conducted to determine the effects of cutting conditions and tool geometry on the surfaceroughness in the finish hard turning of the bearing steel (AISI 52100). Ahmet Hasçalhk et al. , the effect and optimization of machining parameters on surfaceroughness and tool life in a turningoperation was investigated by using the Taguchi method. The experimental studies were conducted under varying cutting speeds, feed rates, and depths of cut. An orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) were employed to the study the performance characteristics in the turning of commercial Ti-6Al-4V alloy using CNMG 120408-883 insert cutting tools.
Sadasiva Rao et al. (2012) work was focused to study the effect of process parameters such as speed, feed and depth of cut and approach angle of the cutter on cutting force, tool life and surfaceroughness in face milling of Inconel 718. The experiments were designed based on L9 orthogonal array and carried out under dry conditions. Grey relational analysis was used to optimize the multi performance characteristics to minimize the cutting force and surfaceroughness and maximize the tool life criteria. Refaie et al. (2010) used Taguchi method grey analysis to determine the optimal combination of control parameters in milling. The measures of machining performance were material removal rate and surfaceroughness. Wang et al. (2006) utilized a hybrid algorithm combining Genetic algorithm (GA) and the Simulated Annealing (SA) to optimize multicriteria high speed milling process.
The Inconel is one of the most important materials used in the modern industries. In addition of the best properties in terms of high strength, corrosion resistance, heat resistance and fatigue resistance, the Inconel 718 has, also a low thermal conductivity (Lynch, 1989). Generally, this type of alloy is difficult to machine for the following reasons (Alauddin et al., 1996): High work hardening rates at machining, strain rates leading to high cuttingforces; abrasiveness; toughness, gummy and strong tendency to weld to the tool with forming the built-up edge; low thermal properties leading to high cutting temperatures. However, it has a wide variety of applications such as aircraft gas turbines stack gas reheaters, reciprocating engines, etc. For those special material properties, high cutting force, tool wear, and cutting temperature are the main characteristic features in the machining process. Surface integrity is relatively an important term used to describe the nature or condition of the surface region of a component (Sadat, 1987). In the study of wear behavior of nano-multilayered coatings, Biksa et al. (2010) obtained that the metallurgical design of the nano-multilayered coating should be tailored to its application and to achieve better tool life when machining aerospace alloys and the adaptive nano-multilayered AlTiN/MoN coating was recommended. A review of developments towards dry and high speed machining of Inconel 718 alloy, by Dudzinski et al. (2004) shows that the higher cutting speeds under dry conditions, certainly up to 100 m/min, may be carried out with coated carbide tools. Settineri et al. (2008) investigated properties and performances of innovative coated tools in turning aerospace alloy Inconel 718 and obtained that the all tested tools performed better than the uncoated inserts.
Abstract: Almost all machining process generates heat and friction which leads to damage of the cutting tools as well as the machined work piece. To reduce the friction, heat transfer and to remove metal particles away from the cutting zone normally cutting fluids are used in any machining operation. The present paper outlines an experimental study to optimize the effects of selected cuttingparameters i.e. Cutting Speed, Feed rate, Depth of cut and type of tool for SurfaceRoughness of EN-19 steel alloy using Al 2 O 3 Nano fluid by employing Taguchi robust design methodology. Taguchi orthogonal array is designed with three
Faculty, Department of Mechanical Engineering, Adhiparasakthi College of Engineering, Vellore, Tamilnadu, India --------------------------------------------------------------------------***---------------------------------------------------------------------------- Abstract - The present work concerned an experimental study of turning on Steel grade of EN8, Mild steel and OHNS by a Tungsten and cemented coated carbide insert tool. The primary objective of the ensuing study was to use the Taguchi Methodology in order to determine the effect of machining parameters viz. cutting speed, feed, and depth of cut, On the Temperature, Hardness and Surfaceroughness of the machined material. The objective was to find the optimum machining parameters so as to minimize the surfaceroughness and Temperature for the work materials in the chosen domain of the experiment. Temperature was measured using a digital thermometer; SurfaceRoughness was measured using a Mitutoyo surface tester and hardness with the help of a Brinell hardness tester. The data was compiled into MINITAB 18 for analysis. Taguchi and Analysis of Variance (ANOVA) were used to investigate the significance of these parameters on the response variables with the machining parameters as the independent variables, with the help of a MINITAB. Results showed that cutting speed is the most significant factor affecting the surfaceroughness and hardness, closely followed by feed and depth of cut, while the only significant factor affects the temperature was found to be the depth of cut.
Today any component that has been manufactured undergoes some sort of machining process. Turning is one of the important processes that is widely used to create cylindrical components and it is also used for surface finish the product to make it smooth. Nowadays, plastic materials are widely used for making variety of components. To make a component with high dimensional accuracy, turningoperation is used. Quality parameters are those parameters which has direct influence on the quality, cost and productivity of the product. Some of the influential parameters for turningoperation are SurfaceRoughness, Material Removal Rate, CuttingForces, and Tool Life etc. These parameters are in turn affected by various factors such as speed, feed, depth of cut, nose radius, tool material, lubricant etc.
The normal probability curve for surfaceroughness (Ra) validates the experimental data obtained while machining the titanium alloy on CNC. The linear line is the expected values and the dots are the observed values and the dot along the line shows that the experiment is good. The versus fit drawn around the 0 line and the randomness is observed in the graph which also validate the experiment. It is valid because of randomness. The histogram is the transformation of versus graph using any operation (mainly logarithmic), The versus order is graph drawn by connecting the observed values around a initial line of 0.
Titanium and its alloys has played a significant role in the field of aerospace, energy, chemical and bio medics due to its high strength to weight ratio and exceptional mechanical and chemical properties. Machining of titanium alloys are a major low thermal conductivity that prevents dissipation of heat easily from the tool chip interface, which in turn heats up the tool due to increasing temperature resulting in lower tool life. 2) Titanium forms alloys easily due l reactivity that causes weld and smear rapid cutting tool destruction.3) Titanium has comparatively low elasticity modulus than steel. Therefore work piece has a tendency to move away from the . Also thin parts may deflect under tool pressures, causing chatter, tool wear and tolerance problems.  Selection cutting conditions, tool material and its coating and cutting edge geometry is important not only to increase the productivity of machining operation but also to obtain a desirable surface integrity (i.e. residual stresses roughness, etc.) of the finished machined part. Hence, comprehensive reviews on machinability of Roughness plays a interaction of a material with its surroundings. Rough surfaces deteriorate quickly and have greater coefficient of friction than smooth surfaces. Roughness often predicts the performance of a mechanical component, as he formation of nucleation sites for cracks or corrosion . Measurement of surface
N.A. Abukhshim et al  explained that the cutting temperature is a key factor directly affecting cutting tools and wear, workpieces surface and precision machining accuracy according to the relative movement between the cutting tool and workpieces. The heat generated amount varies with the kind of operated material and the cutting factors, particularly the cutting speed. These cutting factors such as speed, depth of cut and feed rate were studied using 3-D temperature field of tool during machining and compared with experimental work on C45 workpiece using carbide cutting tool inserts. Cutting speed, surface quality and cuttingforces depend mainly on the temperature that high temperatures can cause high mechanical stresses which lead to early tool wear and reduce tool life. Therefore, considerable attention was paid to determine the tool temperatures. The experiments were carried out for dry and orthogonal machining condition. It showed that an increase of tool temperature depended on depth of cut and especially cutting speed in high range of cutting conditions . However, S.R. Das  presented an optimal method of the cuttingparameters (cutting speed, depth of cut and feed) in dry turning of AISI D2 steel to achieve minimum tool wear and low workpiece surface temperature. The experimental layout was designed based on the Taguchi’s L9 Orthogonal array technique and analysis of variance (ANOVA) was performed to identify the effect of the cuttingparameters on the response variables. The results confirmed that the depth of cut and cutting speed were the most important parameter influencing the tool wear. The minimum tool wear was found at cutting speed of 150 m/min, depth of cut of 0.5 mm and feed of 0.25 mm/rev. Similarly, low work piece surface temperature was obtained at cutting speed of 150 m/min, depth of cut of 0.5 mm and feed of 0.25 mm/rev. Thereafter, optimal ranges of tool wear and workpiece surface temperature values were predicted.
The machining of materials is a working process where a workpiece obtains its required shape and dimensions by removing the material from the surface layer. The most widespread machining method is turning where material is being removed in the form of chips based on the mutual interaction of the tool and workpiece (Žitňanský et al., 2014a). Based on a long-term development of cutting materials, it is not possible to expect in the near future the development of a completely new cutting material; therefore, the research of leading manufacturers of tools and cutting materials is aimed especially at improving the existing materials, specifying the optimum parameters of machining, and exactly deﬁ ning the areas of their use.
study, L18, which is a multilevel experiment. So, cutting speed, feed rate, depth of cut and nose radius was selected as input parameters whose values were selected from the existing literature. Three levels of each parameter were chosen for testing in the current research. The chosen range of cutting speed was (2000 to 4000 rpm), the feed rate was (1 to 5 mm/min) and depth of cut was (1 to 10 µm). There are two levels for tool nose radius so for this we are going for mixed-level for making DOE. To compare the machining of Ti6Al4VELI is done with a single point diamond tool in cutting mentioned above conditions. Machining parameters and observation are shown in Table 2.2.1.
ABSTRACT: This paper deals with finding optimal control parameters to get the minimum Surfaceroughness. It considers the analysis of effect of the process parameters, cutting speed, feed rate and depth of cut on cuttingforces during turningoperation. Machining is the process of removing the excess material from the work piece or unwanted material from the work piece using cutting tool. Surface finish obtained in machining process depends upon so many factors like work material, tool material, tool geometry, machining conditions, cutting fluids used and feed rate etc. In this experimental work it is planned to study the effect of process parameters on surface finish obtained in the machining process of materials like stainless steel and aluminum.
The study o f the machinability results also in obtaining the guidelines for the development o f the cutting tools. It has contributed to very intensive development o f the cutting tools, particularly in the area o f high-speed machining, hard machining and dry m achining. Im provem ent o f ex istin g and development o f new cutting tool materials, same as the new concepts o f machine tools, provide new p o s s ib ilitie s an d c h an g e q u a n tita tiv e ly the machinability indicators. Therefore, the study o f machinability represents a continuous process  to .
The surfaceroughness and cutting force are important machining characteristics for evaluating the productivity of machining processes. In milling processes, by using Taguchi method and ANOVA analysis, the cuttingforces and surfaceroughness could be investigated based on a number of factors, such as depth of cut, feed rate, cutting speed, cutting time, workpiece hardness, etc. Several research works had been conducted in different conditions and had also been applied for different workpieces and tool materials, such as Kıvak , Ozcelik and Bayramoglu , Turgut et al. , Karakas et al. , and Jayakumar et al. .