pressure coolant supplies resulted to increased feed forces with increasing cutting speed. This is an expected phenome- non and it is attributable to the inability of the coolant to sig- nificantly reduce tool temperatures at higher speeds as a result of the conditions of intimate contact, or seizure, that occur over the major part of the chip-tool area. This part of the con- tact area is not accessible to the water based lubricant (even at high flow pressure) except for minimum quantity lubrication (MQL) through a well defined nozzle angle [33, 34]. Some- times, it is possible that cutting fluids can slightly penetrate to the friction region at the rear of the tool-chip contact length, and also into the area created by the ragged edge of the chip, these effects do not greatly influence the temperature, cutting forces or tool life at higher speeds . At lower cutting speed conditions, there is the tendency of an increased coefficient of friction. This increases the cutting force and decreases the shear angle. A small shear angle along the shear plane increas- es the shear plane area thereby increasing the shear force that are required to produce stresses for deformation [25, 36]. 3.4 Power Consumption when machining Nitronic33steelalloy at high speed conditions
In the machining operations, final surfacefinish and dimensional accuracy are the most specified customer requirements. Hard turning machining operation using cubic boron nitride tool as an alternative of grinding process is a type of turning operation in which hardened steel are machined with the hardness greater than 45 HRc. During the hard turning operation because of the hard condition, the variations of surfacefinish and dimensional accuracy are completely different from that of the traditional turning operation. Thus, the variation of surfacefinish and dimensional accuracy under various cuttingparameters has been investigated in the hard turning with cubic boron nitride tools. The extracted knolwdge can be used for developing a knowledged base expert system. In order to have a comprehensive study, the variation of vibration, cutting forces, and tool wear has also been considered. The obtained results showed that depth of cut and spindle speed have the greatest effect on the dimensional accuracy, while feed rate is the most important factor affecting the surface roughness. The analysis of the vibration and tool wear proved that the flank wear has insignificant influence on the dimensional accuracy, whereas the vibration effect is considerable. The experimental results showed that when the feed rate is gradually increased from 0.08 to 0.32, the dimensional deviation first decreases unexpectedly until the lowest value is achieved at 0.16 mm/rev, then by further increasing the feed from 0.16 to 0.32 mm/rev, the dimensional deviation increases significantly. It was also seen that the best dimensional accuracy is achieved at the lowest level of the cutting depth, the medium level of the feed rate, and the spindle speed lower than its moderate level. The best surface roughness of 0.312 μ m was obtained at 0.08 mm/rev feed rate, 0.5 mm depth of cut, 2000-rpm speed, and 1.2 mm insert nose radius, which is comparable with the surfacefinish obtained by the grinding operation.
Abstract - Hot machining is one of the popular technique mainly used for machining of difficult to cut materials. Machining of these materials is difficult because of very high hardness, less thermal conductivity, and abrasive wear resistance. Time and cost require less as compare to other conventional & non conventional machining processes. Hot machining is generally performed by providing external heat to the material it softens material & facilitates machining. Various Cuttingparameters have effect on different performance Characteristics such as SurfaceFinish, metal removal rate, Tool life, Tool wear. This review paper focuses on the effect of hot turning process on the SurfaceFinish of material. Surfacefinish is an important & necessary requirement for proper functioning of machine parts, Tool life, fatigue life, aesthetic appeal, and tribological properties of machined material. By studying various research & experimental work this review will give information about effect of various cuttingparameters in hot turning on surfacefinish of difficult to cut material.
STEP 4: The process of turning has been done in the following three cases Varying speed while keeping the Depth of Cut and Feed Rate constant Varying Feed Rate and keeping the Spindle Speed and Depth of Cut constant. Varying Depth of Cut while keeping the Spindle Speed and Feed Rate constant
Abstract— The importance of temperature prediction for the machining processes has been well recognized in the machining research due to its effects on tool wear and its constraints on the productivity. It is well observed that particularly the rate of wear is greatly dependent on the tool– chip interface temperature. Most of the heat generated during the machining flows into the tool causing severe thermal stresses on the cutting tool accelerates tool fatigue and failures due to fracture, wear or chipping. Furthermore, if the temperature exceeds the crystal binding limits, the tool rapidly wears due to accelerated loss of bindings between the crystals in the tool material. Heat has critical influence on machining; to some extent, it can increase tool wear and then reduce tool life due to thermal deformation. Near dry machining is the goal of today’s metal cutting industry that tirelessly endeavors to reduce machining costs and impact from chemicals in the environment. In Hard turning, high amount of heat is generated at the tool-chip interface which not only increase the tool wear but also deteriorates the job quality in terms of surfacefinish. This study deals with turning round bars of 25 mm diameter of Oil Hardening Non- Shrinking Die Steel (OHNS – AISI O1 grade) hardened to 53-57 HRC by TNMG 160404 MT TT5080 insert under Near Dry Machining (NDM) condition. For this purpose MQL set- up was manufactured and machining was carried out at three levels of Cutting Speed (vc), Feed Rate (f), and Depth of cut (ap). To investigate the performance, Surface Roughness (Ra), Tool-chip interface temperature and Machining time (tc) was selected as output responses. Full factorial (3k) DOE was employed and 27 experiments were analyzed by using Response Surface Methodology (RSM) and regression equations were developed. ANOVA was used to find out the significant parameters. Feed rate was found to be the most influential factor in increasing the surface roughness and decreasing machining time, whereas Depth of cut is the most influential factor in increasing the avg tool-chip interface temperature.
degree of ductility and work hardenability [1, 2, 4, 5]. The problems such as poor surfacefinish and high tool wear are common while machining these materials . Therefore, attempts have been made to improve the machinability of austenitic stainless steel by adding free machining elements like lead, sulfur, tellurium and selenium . In the machining process, one of the most noteworthy mechanical requirements of the customers is surfacefinish. To improve the fatigue strength, corrosion resistance, aesthetic appeal and tribological properties of the product; a sensibly good surfacefinish is required. Nowadays, fabricating commercial ventures are particularly concerned with dimensional precision and surface completion. Our main objective is to study effect of cuttingparameters on AISI 316 austenitic stainless steel workpiece surface roughness and hardness by employing design of experiments via Taguchi methods and Analysis of Variance (ANOVA) using tungsten carbide tool on CNC lathe under wet environment. Austenitic grade of stainless steel is one of the vastly consumed steel (70 percentage) universally [4, 8]. The austenitic alloys used most often are those of the AISI 300 series. Grade 316 is the standard molybdenum-bearing grade. Molybdenum gives 316 preferable corrosion resistance properties over crevice corrosion in chloride environment. It has excellent forming and welding characteristics. AISI 316 austenitic stainless steel has wide range of applications such as it is used in chemical processing equipment; aerospace components; for food, dairy and beverage industries; for surgical embeds inside of the threatening environment of the body; in deck components for boats and ships in marine environment; and for heat exchangers [3, 4]. 1.1 Taguchi Parameter Design
Absract-- Present work aimed to improve the quality and minimize the cost during turning operation of Ti-6Al-4V alloy. The optimum cost and quality can be achieved by the selection of optimum machining parameters. Series of experiments were conducted to find the effect of machining parameters during turning operation. The main parameters taken for the study are feed rate, cutting speed(spindle speed),concentration of coolant and depth of cut and their effect is observed on the surfacefinish and material removal rate (MRR) of Ti-6Al-4V Alloy. A mathematical tool called Design of experiment was developed in terms of output parameters (surface roughness and MRR). The effect of machining parameters on the surface texture and material removal rate has been investigated by using three factor box behnken Response Surface Method (RSM). 3D plots were constructed to find the optimum parameters required for better surfacefinish and higher material removal rate. The conclusion is drawn that the feed rate is the main machining parameter that affects the surface roughness. A small change in feed results in major change on surface roughness. The surface irregularities were found to be directly proportional to feed as increase in the feed rate results in increase in surface irregularities.
An ANOVA table is commonly used to summarize the tests performed. It was statistically studied the relative effect of each cuttingparameters on the surface roughness (Ra) by using ANOVA. Table 5.3 shows the results of the ANOVA (analysis of variance) with the surface roughness for CVD coated carbide tool when coolant on. Here the contribution of speed rate for CVD coated carbide tool on surface roughness is 87.63%, it is more significant and cutting feed factor is 8.45% have statistical and physical significance on the surface roughness obtained for EN14 steel. The feed rate is more significant factor than the other factors. The error associated is 3.21% respectively. From the result, the role of depth of cut is minimum in obtaining good surfacefinish. It is indicated that in order to achieve good surfacefinish, always use high cutting speed and low feed rate.
in manufacturing industry that Involves generation of high cutting forces and temperature. With variation in rake angles and Lubrication techniques, becomes critical to minimize the effects of these forces and temperature, on life of cutting tool and Surfacefinish of the work. In metal industry, the use of coolant has become more problematic in terms of both workpiece quality, employee health and environmental pollution. On this account it has become necessary to investigate the effects of cuttingParameters and lubricants on tool life and surfacefinish. This paper describes a review of basic terms and visualizations of the major components of the cutting tool geometry and lubrication techniques in turning process. The parameters like rake angle, depth of cut, feed rate, temperature, cutting speed and role of coolant implementation techniques are taken in to account so as to predict their effects on tool life and surface roughness of the work.
finish and cutting speed has very little influence on surfacefinish for both ceramic and CBN cutting tool. Sahin and Motorcu  indicated that the feed rate was found out to be dominant factor on the surface roughness, but it decreased with decreasing cutting speed, feed rate, and depth of cut in turning AISI 1050 hardened steels by CBN cutting tool. The RSM predicted and experimental surface roughness values were found to be very close. Likewise, the effects of machining parameters (i.e. cutting speed, feed rate and depth of cut) on surface roughness and cutting forces during machining of AISI 52100 steel with CBN tool were investigated by Bouacha et al.  using three level factorial design (3 3 ). Results showed how much surface roughness is mainly influenced by feed rate and cutting speed and the depth of cut exhibited maximum effect on the cutting forces. Aouici et al.  investigated the effects of cutting speed, feed rate, workpiece hardness and depth of cut on surface roughness and cutting force components in hard turning. AISI H11 steel, hardened to 40, 45 and 50 HRC respectively, was machined using cubic boron nitride tools. Results showed that the cutting force components were influenced principally by depth of cut and workpiece hardness; however, both feed rate and workpiece hardness had statistical significance on surface roughness. Chavoshi and Tajdari  modelled the surface roughness in hard turning operation of AISI 4140 using regression analysis and artificial neural network. They concluded that hardness had a significant effect on the surface roughness and with the increase of hardness until 55 HRC, the surface roughness decreased; afterwards surface roughness represented the larger values increasingly. The studied range of spindle speed has a partial effect on the surface roughness. Ozel et al.  conducted a set of analysis
Abstract: This paper focuses on analysis of cuttingparameters using regression analysis which is a set of statistical processes for estimating the relationships among variables, is used to analyse surface roughness (SR). A full factorial 27 experiment is engaged to scrutinize the cutting characteristics of mild steel bars using carbide cutting tool. The key objective is to analyze the effect of cutting speed, feed and depth of cut on SR of mild steel in turning operation using carbide tool. The specimen was turned under different level of constraints and the SR was established using a Taylor Hobson’s Surtronic 3+. From the result, it is concluded that higher cutting speed and lower feed produce better surfacefinish. The optimum cutting constraints were 119.380m/min, 0.04mm/rev and 0.6mm, which produced minimum surface roughness of 1.33μm. According to the non-linear regression equation, the optimum surface Roughness comes out to be 1.35μm which gives the error of 1.5%.
Prianka B. Zaman and N. R. Dhar  in their research work studied the effects of minimum quantity lubrication (MQL) by different cutting fluids (soluble oil, vegetable oil and VG 68 cutting oil) on the cutting performance of hard turned part, as compared to completely dry cutting with respect to cutting temperature, chip thickness ratio, tool wear and machined surface quality have been studied. In the study, MQL is provided with a spray of air and cutting fluid. In this experiment Hardened AISI 4320 steel bars having surface hardness of 45 HRC with diameter and length of 74 mm and 230 mm respectively was turned in a lathe (China, 10 hp) by coated carbide inserts with ISO designation SNMG 120408 TN 4000. Tool holder used was PSBNR 2525 M 12 (WIDIA) and the working tool geometry was -6°, -6°, 6°, 6°,15°, 75° and 0.8mm. The experiment was carried out with different cutting velocities (V) of 82, 114, 163 m/min and feed rates (f) 0.10, 0.12, 0.14 mm/rev at a constant depth of cut 1.0 mm under dry and MQL by vegetable oil, cutting oil and soluble oil conditions to study effect of MQL on different machinability characteristics. Flow Rate of the MQL supply was 150 ml/hr, where air pressure and oil pressure was 23 bar and 25 bar, respectively. The results indicated that the use of MQL with VG 68 cutting oil performed better in comparison to other cutting fluids in respect of chips thickness ratio, cutting temperature, tool wear, surface roughness and dimensional deviation.
To obtain the maximum machining rate as well as minimum machining cost, the cutting parameter is very important factor. The high productivity and high material removal rate for drilling process can be achieve by changing the process parameters such as drilling diameters, cutting speed, feed rate and many more. The drilling performance like tool life and material rate removal also can improve. Study on the influence of cuttingparameters such as cutting velocity, feed rate, cutting time on drilling metal – matrix composites and concluded that interaction of cutting speed/feed is the most important factor contributing towards surface roughness of drilled holes (J Paulo davim, 2003).
For the survival of the industry to achieve optimal quality fast with low cost is essential. In the machining process, it would be possible with proper and intelligent selection of machining parameters. In this study, using professional knowledge base, an algorithm has been provided on machining parameters during the process of machining which carries out the smart selection of machining parameters to achieve desired quality with respect to the presented information. In the turning process the most important parameter are feed rate, cutting speed and depth of cut. Typically, quality refers to a better surfacefinish and production tolerance. In this respect, the depth of cut, material and surfacefinish of the work-piece are considered as the input, and the cutting speed and feed as the output. To estimate the surface roughness after machining some proper functions have been employed. Finally, to do this work a software is prepared and presented results are favourable. Machining is one of the most widely used manufacturing processes and plays a key role in the quality of most products. For example, with accurate analysis and expressing the complexity of the machining process it can be understood that increasing the cuttingparameters can be more economical than increasing the tool’s life by reducing the cuttingparameters. It means that, 20% increase in cuttingparameters will decrease the costs by 15%. However, increasing tool’s life by up to 50%, will only reduce the total cost of production by 1%. . Or according to estimates 80 percent of the production time of the final products is spent on modern manufacturing and production systems and machining, however, in traditional machine tools only 5% of time spent on machining operation . Considering this data, the correct meaning of smart and intelligent selection of economical machining parameters can be better understood.
ASTM A182, Gr.F1 finds its application in Oil & Gas, Petrochemical, Chemical & Fertilizers, and Power Generation components such as Pipe Flanges, Forged Fittings, and Valves and Parts for High-Temperature Service. Predicting process of machinability models and determining the optimum values of controlled process parameters in manufacturing system have been areas of interest for researchers and manufacturing engineers. The surface roughness of machined parts is a significant design specification that is known to have considerable influence on mechanical properties such as wear resistance, fatigue strength and refers to deviation from the nominal surface. This material is attractive because of its properties such as high hardness, toughness, yield strength, excellent ductility and compatibility at high-temperature service. But machining of this material is difficult than carbon and low alloysteel because of high strength, and a higher degree of ductility and work hardenability [1, 2]. The problems such as poor surfacefinish and higher tool wear are common while machining these materials. In the machining process, one of the most notable mechanical requirements of the customers is surfacefinish. To improve the fatigue strength, wear resistance, and aesthetic appeal, a good surfacefinish is required. A substantial amount of studies have investigated the general effect of process parameters (cutting speed, feed rate, depth of cut, insert radius) on process functions such as surface roughness, tool life, cutting forces etc. [3, 4]. Most of these models are based on the regression analysis (RA), very few researchers used computational neural networks techniques (CNN) [5-9]. In this paper our main objective is to study the influence of cuttingparameters on ASTM A182, Gr.F91 alloysteel workpiece surface roughness by employing design of experiments via Taguchi methods and Analysis of Variance (ANOVA) using carbide insert on CNC lathe machine. Four machining parameters were considered (Cutting speed (v, m/min.), Feed rate (f, mm/rev.), Depth of cut (d, mm), Insert radius (r, mm)). Therefore this paper presents the following contributions: at first, it applies Taguchi concept to design the process for machining using an orthogonal array. Secondly, it
Several information has been extracted from previous study. a carbon content is crucial to induce the superficial hardening process to take place in grinding. It is also suggested that the severe cutting condition will assist in martensite formation in microstructure level of workpiece. Workpiece with high carbon content will be applied in this study. In addition, a good surfacefinish is also a response to the experiment done. How the cuttingparameters influence the value of the surface roughness and the surface hardness will be determine through the study work. Furthermore, what are the optimum value to achieve the best for both response.
Further analysis of the data was done to understand the main effect plot and interaction effect plots of cuttingparameters which are affecting surfacefinish and their vibration response. The plots represent the variation of individual response with the selected three cuttingparameters such as feed rate, spindle speed and depth of cut separately. The relative influence amongst the parameter levels are determined more accurately in ANOVA analysis and was performed for the number of cycles in order to find out the most influencing parameter affecting this response. In the following plots (4, 5, 6 & 7), the x-axis demonstrates the obtained selected parameter at three different levels whereas, y-axis represents their response value. Main Effect Plot were used to illustrate the optimum design circumstances to attain minimum surface roughness (Ra) on workpiece and their vibration (peak amplitude) effects on tool insert while, Interaction Effect Plots were used for the effect of level of one factor depending on the level of the other factors and the greater is the degree of interaction when the larger is the difference between two lines.
The determination of the machinability of materials is done by the measure of surfacefinish. Surface roughness is an important measure of product quality since it greatly influences the performance of mechanical parts as well as production cost. The Optimization of machining parameters increases the utility for machining economics and the product quality increases to a great extent as well. EN24 is a high quality, high tensile, alloysteel and combines high tensile strength, shock resistance, good ductility and resistance to wear 1 . EN24 is most suitable for the
In the present work, an attempt was made to study the effect of MQL turning of steel AISI 4340 by CBN insert on cutting forces, surfacefinish and its comparison with dry and wet turning. In addition to the cutting environments, the process parameters used were cutting speed and feed rate. The cutting environmental conditions were changed in three levels like dry, wet and MQL. The response variables selected to achieve better machining and tool performance were surface roughness, cutting force components and tool wear. The experiments were conducted using the standard L 27 Taguchi orthogonal array. The experimental conditions are
Predicting process of machinability models and determining the optimum values of process parameters in manufacturing system have been areas of interest for researchers and manufacturing engineers. To allow for high productivity, high flexibility hard turning is now a days an alternative to grinding in the finishing of work pieces. The surface roughness of machined parts is a significant design specification that is known to have considerable influence on properties such as wear resistance and fatigue strength and refers to deviation from the nominal surface. The quality of a surface is a factor of importance in the evaluation of machine tool productivity. Hence it is important to achieve a consistent surfacefinish and tolerance because it plays an important role in many applications such as precision fits, fastener holes etc. In a turning operation an important task is select the appropriate cuttingparameters for achieving high cutting performance. Cuttingparameters affect surface roughness, surface texture of the product.