, On-line prediction of surface finish and dimensional deviation in turning using neural network based sensor fusion, International Journal of Machine Tools and Manufacturing 37(9), 1997. – pp.1201–1217. 10. S.Y. Ho, K.C. Lee, S.S. Chen, S.J. Ho, Accurate modeling and prediction of surfaceroughness by computer vision in turning operations using an adaptive neuro-fuzzy inference system, International Journal of Machine Tools and Manufacture 42(13), 2002. – pp. 1441-1446. 11. T. Rajasekaran, K. Palanikumar, B.K. Vinayagam, Application of fuzzy logic for modelingsurfaceroughness in turning CFRP composites using CBN tool, Production Process 5(2), 2011. – pp. 191-199. 12. B. Savković, P. Kovač, K. Gerić, M. Sekulić, K. Rokosz, Application of neural network for determination of cutting force changes versus instantaneous angle in face milling, Journal of Production Engineering 16(2), 2013. – pp. 25-28. 13. P. Kovac, D. Rodic, V. Pucovsky, B. Savkovic, M. Gostimirovic, Application of fuzzy logic and regression analysis for modelingsurfaceroughness in face milling, Journal of Intelligent Manufacturing 24(4), 2013. – pp. 755-762.
uncoated carbide insert of very small depth of cut. This was done in order to remove the rust layer or hardened top layer from the outside surface and to minimize any effect of in homogeneity on the experimental results. A hole was drilled on the face of the work piece to allow it to be supported at the tailstock (fig. 1). In attempts to evaluate the effects of machining parameters on surfaceroughness values in hardturning by using experimental data, the working range was decided on the basis of data given in the hand book . The surfaceroughness of the turned surface was measured using a portable Mitutoyo surfaceroughness tester (Taylor Hobson, Surtronic 25) in terms of arithmetic average roughness (Ra). Typically, grinding or honing surface-finishing processes yield surfaces with a Ra in the range of 0.1– 1.6µm. We used 1.6µm as the control criterion for finish hardturning .
The maximum roughness, Ra=0,511μm, corresponds to the following experimental conditions: a p =0,15mm, f=0,075mm/rev, V c =160m/min and VB=0,2mm and the minimum roughness value in this experimental study is Ra=0,2211μm, obtained in the following experimental conditions: a p =0,2mm, f=0,05mm/rev, V c =120m/min and VB=0,15mm. However the most small values of roughness ≈2,5μm were obtained when the flank wear was VB≈0,1mm.
Surfaceroughness is widely used as an index of product quality in turning operation and in most cases a technical requirement for mechanical products. Achieving the desired surface quality is of great importance for the functional behavior of a part. Surfaceroughness is a measure of the quality of a product and a factor that greatly influences manufacturing cost. It can be generally stated that the lower the desired surfaceroughness the more the manufacturing cost and vice versa. The factors which influences the surface quality in turning processes are Finish ability of work material, Type and condition of cutting tool, Application of cutting fluid, Method of chip removal, geometry of cutting tool and the cutting variables like feed, depth of cut and cutting speed. In order to obtain better surfaceroughness, the proper setting of cutting parameters is crucial before the process takes place. One should develop techniques to evaluate the surfaceroughness of a product before machining in order to determine the required machining parameters such as feed rate, spindle speed and depth of cut for obtaining a desired surfaceroughness and product quality. Ceramic tool is used as the cutting tool material because of its high hot hardness, wear resistance and chemical inertness.
Dry machining is a machining process without coolant and it is more popular as a finishing process. The purpose of this research project is to optimize the parameters using Response Surface Methodology when dry turning AISI 1045 steel using CBN tool. The factors that are investigated are cutting speed, feed and depth of cut, Surfaceroughness(Ra) is the response variable investigated. The experimental design will be based on the central composite design. The experiment is designed using Response Surface Methodology. The empirical relationship to predict response, optimum value of parameters to minimize the response and the process parameters which are effecting the response are determined.
minimize any effect of in homogeneity on the experimental results. A hole was drilled on the face of the work piece to allow it to be supported at the tailstock (Figure 1). In attempts to evaluate the effects of machining parameters on surfaceroughness values in hardturning by using experimental data, the working range was decided on the basis of data given in the hand book 15 . The surfaceroughness of the turned surface was measured using a portable Mitutoyo surfaceroughness tester (Taylor Hobson, Surtronic 25) in terms of arithmetic average roughness (Ra). Typically, grinding or honing surface- finishing processes yield surfaces with a Ra in the range of 0.1–1.6μm. We used 1.6μm as the control criterion for finish hardturning 16 .
BerendDenkena et al., has an experimental investigation was conducted to determine the effects of cutting conditions and tool geometry on the surfaceroughness in the finish hardturning of the bearing steel (AISI 52100). Mixed ceramic inserts made up of aluminum oxide and titanium carbonitride (SNGA), having angles, were used as the cutting tools different nose radius and different effective rake. This study shows that the feed is the dominant factor determining the surface finish followed by nose radius and cutting velocity.
The study concluded that low feed rate was good to produce reduced surfaceroughness and also the high speed could produce high surface quality within the experimental domain . Mahmoud and Abdelkarim (2006) studied on turning operation using High-Speed Steel (HSS) cutting tool with 45 0 approach angle. This tool showed that it could perform cutting operation at higher speed and longer tool life than traditional tool with 90 0 approach angle. The study finally determined optimal cutting speed for high production rate and minimum cost, tool like, production time and operation costs. Doniavi et al. (2007) used response surface methodology (RSM) in order to develop empirical model for the prediction of surfaceroughness by deciding the optimum cutting condition in turning. The authors showed that the feed rate influenced surfaceroughness remarkably. With increase in feed rate surfaceroughness was found to be increased. With increase in cutting speed the surfaceroughness decreased. The analysis of variance was applied which showed that the influence of feed and speed were more in surfaceroughness than depth of cut.. Kassab and Khoshnaw (2007) examined the correlation between surfaceroughness and cutting tool vibration for turning operation. The process parameters were cutting speed, depth of cut, feed rate and tool overhanging. The experiments were carried out on lathe using dry turning (no cutting fluid) operation of medium carbon steel with different level of aforesaid process parameters. Dry turning was helpful for good correlation between surfaceroughness and cutting tool vibration because of clean environment. The authors developed good correlation between the cutting tool vibration and surfaceroughness for controlling the surface finish of the work pieces during mass production. The study concluded that the surfaceroughness of work piece was observed to be affected more by cutting tool acceleration; acceleration increased with overhang of cutting tool. Surfaceroughness was found to be increased with increase in feed rate. Thamizhmanii et al. (2007) applied Taguchi method for finding out the optimal value of surfaceroughness under optimum cutting condition in turning SCM 440 alloy steel. The experiment was designed by using Taguchi method and experiments were conducted and results thereof were analyzed with the help of ANOVA (Analysis of Variance) method. The causes of poor surface finish as detected were machine tool vibrations, tool chattering whose effects were ignored for analyses. The authors concluded that the results obtained by this method would be useful to other researches for similar type of study on tool vibrations, cutting forces etc. The work concluded that depth of cut was the only significant factor which contributed to the surfaceroughness.
Abstract: Machining of materials by super hard tools like cubic boron nitride (cbn) and poly cubic boron nitride (pcbn) is to reduce tool wear to obtain dimensional accuracy, smooth surface and more number of parts per cutting edge. wear of tools is inevitable due to rubbing action between work material and tool edge. however, the tool wear can be minimized by using super hard tools by enhancing the strength of the cutting inserts. one such process is cryogenic process. this process is used in all materials and cutting inserts which requires wear resistance. the cryogenic process is executed under subzero temperature -186º celsius for longer period of time in a closed chamber which contains liquid nitrogen. in this research, cbn inserts with cryogenically treated was used to turn difficult to cut metals like titanium, inconel 718 etc. the turning parameters used is different cutting speeds, feed rates and depth of cut. in this research, titanium and inconel 718 material were used. the results obtained are surfaceroughness, flank wear and crater wear. the surfaceroughness obtained on titanium was lower at high cutting speed compared with inconel 718. the flank wear was low while turning titanium than inconel 718. crater wear is less on inconel 718 than titanium alloy. all the two materials produced saw tooth chips.
A. K. Sahoo and B. Sahoo  mentioned about optimization of process para- meters to surfaceroughness and tool wear in hardturning finish of D2 steel with ceramic tools using the neural network model of radial function, being suitable for selecting the functional process parameters. Currently, research and experi- mentation in machining processes continues, in order to maximize useful life of the cutting tool and maintain surface and dimensional quality of the pieces within established specifications in the manufacturing industry. The current li- terature reports many investigations using PCBN and ceramic tool on hardened steel, but the research work carried out by multilayer coated carbide inserts on hardturning are very limited.
ABSTRACT: The introduction of newly developed coated cutting tools has made hardturning more widespread. The present work deals with the investigation of the performance of CVD coated carbide tool and optimization of cutting parameter when turning with EN14 die steel. In this work, an attempt has been made to analyze the influence of cutting speed, feed, depth of cut on surfaceroughness and material removal rate by using Taguchi method and Minitab software is used to analyze the predicted values of surfaceroughness and material removal rate. Turning was done under dry and wet cutting condition by using various cutting speed, feed, depth of cut. The experimental plan was based on Taguchi L9 orthogonal array. The parametric analysis indicates that cutting speed has most significance on surfaceroughness. The ANOVA is a statistical tool is used to determine the significance of independent parameter on responses; it showed cutting speed has more significance on surfaceroughness and material removal rate followed by feed and depth of cut. Regression analysis shows that experimental and predicted values are near.
The objective of response surface methodology (RSM) is to determine a relationship between independent input process parameters with the studied responses (Gaitonde et al., 2010). This procedure includes following six steps (Aouici et al., 2012). These are, (1) definition of independent input variables and the desired output responses, (2) adoption of an experimental design plan, (3) performing regression analysis with the quadratic model of RSM, (4) calculate analysis of variance (ANOVA) for the independent input variables in order to find significant parameters that affect the responses, (5) determination of the situation of the quadratic model of Response Surface Methodology and decide whether the model of RSM needs screening variables or not and finally, (6) optimization, conduction of confirmation experiments and verifying the predicted performance characteristics. In the current study, the relationship between the input, called the cutting conditions, cutting speed (Vc), cutting time (t), tool hardness (TH) and the output Y, defined as the desired machinability (tool wear, surfaceroughness,) is given as
The purpose of this paper is to examine how the surfaceroughness of alloy steel EN47 is affected by hardturning. Tests were conducted on the CNC lathe using different cutting parameters. The surface was evaluated in terms of surfaceroughness. Tests showed that hardturning provide good surface finish. Process parameters (insert radius, cutting speed, depth of cut and feed rate) are used as input parameters. Taguchi method is implemented to find out the optimum cutting parameters for surfaceroughness (Ra) in hardturning. The L9orthogonal array , signal to noise ratio and analysis of variance has been employed to study the performance characteristics in turning of alloy steel EN 47 using carbide inserts ( TNMG 160408-FMTN8135). Experimental data have been used to generate, compare and evaluate the proposed model of surfaceroughness for the considered material.
Crater wear is dished out section which it develops on the rake face of the tool. The formation of crater wear occur little away from the cutting edges. In fact at low cutting speed, crater wear is usually insignificant compared with flank wear in normal operations. There is no standard available for maximum depth of the crater specification like flank wear. Deeper crater will lead to failure of the cutting edge. When machining using CBN, PCBN inserts and other high strength inserts the formation of wear take longer time. At high cutting speeds crater wear formation would be more severe and depth of crater K T will be deeper. While turning difficult to cut
the conventional machining but effective investigation about force and friction conditions are still to be taken up. No work related to modeling addressing the dominance of radial force could be found. As in most cases, actual cutting involves a very small amount of multiphase material being removed; hence the force modeling should be performed on microstructure level as the tool would be removing different phases simultaneously. But no literature could be found discussing the modeling of hardturning process at microstructure level as it has being done for micro machining processes. It has been concluded by many researchers that the white layer formation is due to phase transformation to marten site and that the hard turned surfaces have tensile residual stresses, but a very little work has been done in order to reduce these tensile stresses on the machined surface that too without compromise the cutting parameters required for a specified surface finish.
The built up edge acts as another cutting edge with restricted contact length and therefore effectively reduce tool – chip contact length. The stainless steels are low thermal conductivity materials and retention of heat was low by the work materials. At low cutting velocity, the area of contact by tool tip with work materials surface is more and this caused more friction. The friction increased the rubbing of the tool tip and work which generated heat at cutting zone. The heat generated was not shared by work material, tool tip and chips which normally take place in turning. The heat generated was observed by stainless steel and shared by tool tip and chips. If the there was retention of heat by work material and this help the materials to be softer. In the absence of the above, more cutting force recorded while turning stainless steel than by alloy steel. In actual situation, the heat was shared by work material, tool tip and chips by alloy steel. The retention of heat on work materials help to soften the chips and less cutting force is required to remove the material. The force by CBN tool was more on stainless steel than alloy steel. PCBN tool required less cutting force due to less wear. Figure 5 (a), (b), (c) and (d) show the graphical representation of cutting forces. Cutting force by PCBN tool on SCM 440 was low than stainless steel.
In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hardturning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surfaceroughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surfaceroughness and the depth of cut is the most significant control parameter for Material removal rate.
Hardened steel possess a wide range of applications in industrial field like, cutting tools, bearing, thread rolls, burnishing rolls and dies manufacturing etc. . Die making industry widely make use of AISI H13 hot working steel for manufacturing of various types of hot working dies. This material possesses a blend of various properties like, good hardness, toughness and ability to retain hardness at elevated temperature . Generally the material used for die making has the hardness range in between 45-60 HRC. Conventional methods of machining for hard material includes various steps, such as rough turning in annealed condition, heat treatment and then finishing process with the grinding. The conventional method of finishing was a time consuming and very costly . Hardturning is a process which facilitates the manufacturers to machine hardened material of hardness more than 45 HRC in a single setup. Even hardturning can achieve a surface finishing less than 0.3 micron and maintain up to +/- 0.010mm size tolerance. As hardturning deals with the machining of hardened material, therefore the cutting forces are more than the conventional turning operation.
finish and cutting speed has very little influence on surface finish for both ceramic and CBN cutting tool. Sahin and Motorcu  indicated that the feed rate was found out to be dominant factor on the surfaceroughness, 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 surfaceroughness values were found to be very close. Likewise, the effects of machining parameters (i.e. cutting speed, feed rate and depth of cut) on surfaceroughness 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 surfaceroughness 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 surfaceroughness and cutting force components in hardturning. 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 surfaceroughness. Chavoshi and Tajdari  modelled the surfaceroughness in hardturning operation of AISI 4140 using regression analysis and artificial neural network. They concluded that hardness had a significant effect on the surfaceroughness and with the increase of hardness until 55 HRC, the surfaceroughness decreased; afterwards surfaceroughness represented the larger values increasingly. The studied range of spindle speed has a partial effect on the surfaceroughness. Ozel et al.  conducted a set of analysis
When the chips moving on the rake face with heat moves slowly and forms crater. The heat at tool tip interface is enough to soften the tool edge and loose its cutting strength. As the process is continuously performed, more crater wear occurred. This wear occurs on the rake face of the tool. The crater wear affects the tool geometry. The most important factors which influence crater wear are temperature at the tool tip interface and the chemical affinity between tool and work material . The high contact temperature and stresses at the interface caused significant crater wear in the form highly localized shear deformation. The temperature at tool chip interface generates heat and the chips are moving on the rake face with enough heat which causes to form crater. The formation of crater wear was due to temperature of the chips and rubbing of the surface. The hard carbides or hard martensite structure of the work material abrades the rake face in combination of the heat formed crater wear. The heat at tool tip interface is enough to soften the tool edge and loose its strength. The tools which undergone more number of passes experienced extensive chipping of the tool material by the irregular flow of chip over the tool rake face. A.Deville et al  noted that the depth of crater increased as the cutting speed increased.