Machining Behavior of En24 and En36c Steels

Transcription

1 Machining Behavior of En24 and Enc Steels Nikhil Bharat, Vishal Mishra 2, Dr Kalyan Chakraborty 3,2 M.Tech (Mechanical) Student, Department of Mechanical Engineering National Institute of Technology, Silchar, Assam 3 Associate Professor, Department of Mechanical Engineering National Institute of Technology, Silchar, Assam Abstract EN24 and ENC steels are among the steels that are used in dynamic environment and in heavy duty applications. The paper presents the machinability of EN24 and ENC steels with reference to turning of the work materials on lathe using carbide insert. Principal aim of investigation was to know the mechanism of chip formation and von Mises stress (VMS) generation during machining. Severe plastic deformation occurs in the primary deformation zone (PDZ) and subsequently chip forms and von Mises stress generates. Cutting velocity, feed and depth of cut (d.o.c) are the input parameters for machining on work material and chip reduction co-efficient (CRC) and von Mises stress (VMS) are the output parameters. 3 3 factorial design of experiment was considered to conduct the experiment. The von Mises stress (VMS) was determined employing CRC and material properties namely strain hardening exponent n and strength coefficient K. Presence of residual stress on machined item has to be identified as this may cause some detrimental effect on machined component. Therefore, presence of such stress was identified through XRD study in the present work. Finally, behavior of chip material during formation was also observed by SEM and EDX examination. Keywords Chip reduction coefficient (CRC); von Mises stress (VMS); Chip formation mechanism. I. INTRODUCTION EN24 and ENC steels are usually used for production of various mechanical components. These materials are processed extensively by machining. Therefore, present study is aimed at to determine machinability of these materials. Machining response parameters like tool wear, surface roughness, cutting forces etc are usually considered for machinability assessment. Induced von Mises stress (VMS) on machined surface can be another factor to be considered for machinability assessment. Machining process is based on plastic deformation of work material. Machining chip is formed through plastic deformation only. Chip reduction coefficient(ξ) can be considered as an index of plastic deformation. Machining process is very much influenced by deforming behaviour of work material. It is therefore necessary to incorporate CRC as an index for determination of induced von Mises stress (VMS) on the machined item. Generated von Mises stress (VMS)on the machined component is also strongly influenced by property of the work material. Present work illustrates the method for determination of von Mises stress (VMS) based on deformation index (CRC) and material property namely strength coefficient K and strain hardening exponent n. This method for determination of von Mises stress (VMS) employing ξ, n and K can be considered as most appropriate consideration since von Mises stress (VMS) generation is directly related toplastic deformation and subsequently to property of materials. Literature considering this procedure to determine the von Mises stress (VMS) on the machined component employing ξ, n and K is scarce. Vishal Mishra et al. [] performed machining on EN24 and ENC steels using carbide tool and found that tool wear takes place through adhesion and chipping while machining EN24 steel. They also observed that for machining with ENC steel, tool wear takes place through abrasion. Vishal Mishra et al. [2] studied the effects of von Mises stress (VMS) generation during Machining on ENC steel. It was observed that ENC steel showed better results during maching at cutting speed: 6m/min, feed:.63mm/rev and doc: mm. Geethanjali KS et al. [3] studied the effects of machining on tool forces, power consumption and surface roughness. It was observed that for EN9 steel and EN24 steel, cutting speed has a significant effect on power. Nikhil Bharat et al. [4] conducted experiment on EN24 steel on lathe using carbide tool and concluded that EN24 steel can be machined at higher speed, feed and depth of cut (d.o.c). II. EXPERIMENTAL PROCEDURE In the present study EN24 and ENC steels are used as work materials having 4mm of length and mm of diameter. Machining was performed on central lathe by using tool insert of coated carbide grade. Table and table 2 show the chemical compostion of work material. Volume 2 Issue 4 March 29 2 ISSN:

2 Table. Chemical composition of EN24 steel %Fe %C %Mn %Si %P %Cr %Mo %Ni %Al %S Balanced Table 2. Chemical composition of ENC steel. %Fe %C %Mn %Si %P %Cr %Mo %Ni %Al %S Balanced Central lathe was employed for machining on the work material which has speed range of 45 rpm to rpm and feed range of.6 mm/rev to.72 mm/rev. 2.. Tool Specification Holder specification: ASBNR 25*25 M2-A Holder Specifications Designation System Assigned Values A Clamping system Double clamping S Insert shape Square B Cutting edge style Principle Cutting edge angle=5o N Relief angle of insert o R Hand of tool Right hand 25*25 Shank size 25mm*25mm(height*width) M Holder length 5mm 2 Insert size 2mm A Machining insert Turning Insert Specification: SNMG 244 TM T925 Insert Specifications Designation System Assigned Value S Insert shape Square with hole N Relief angle o M Accuracy Tolerance G Groove Cylindrical hole 2 Cutting edge length 2mm 4 Thickness 4mm 4 Corner radius 4mm TM Chip breaker symbol TM T925 Stocked grade Coated Cutting speed, feed and depth of cut (d.o.c) are the input process parametrs used for the experimentation. The experimentation was based on 3 3 factorial design. Table 3 shows the arrangement of input process parameters with given level of cutting. Table 3. Input parameters used for machining. Factors Level (lowest level) Level 2 (moderate level) Level 3 (highest level) Coding - Speed (m/min) 6 Feed (mm/rev) D.O.C (mm).67.5 Volume 2 Issue 4 March ISSN:

3 Formulation for the selection of input process parameter values for the level. Where, Code(v,f,d)=values for various codes with reference to speed,feed and d.o.c (v,f,d)m= cutting speed, feed and doc at moderate level. (v,f,d)max= cutting speed, feed and doc at highest level. Based on the above given input process parameters, 3 3 factorial design of experiment was done which provided 27 different combinations. Table factorial design is showing the input parameters for machining. S.No. Assigned Codes Velocity (V) Feed (f) V F d m/min mm/rev Depth of cut (d) mm Cutting velocity V= (m/min) Where, N = Spindle speed (rpm). D = diameter of work material (mm) Volume 2 Issue 4 March ISSN:

4 Based on the coding and the assigned values as mentioned in table 4, machining of the work material was carried out for a time period of 3 seconds. From the experimentation, 27 different types of chip samples were collected. Each chip was takenand its corresponding weight and length were measuredandfurther the chip thickness was determined. Figure (a). ENC steel mounted on lathe. Figure (b).en24 steel mounted on lathe.[4] Figure(c). Tool insert with holder. Figure (d). Carbide tool insert. After completion of 27 experiments, tensile testing specimen of the work material was prepared according to ASTM E8 standard and it was subjected to tensile test by INSTRON 95 UTM machine and the true stress-true stress curve was obtained from experimental data. From the curve, three points within the yield point and ultimate stress point were selected and were then plotted on log-log graph paper. The straight line that was obtained on the log-log graph was extrapolated and the strength coefficient K and the strain hardening exponent n of the work material was recorded. In the same context, on getting the value of K and n, power equation (σ = Kɛ n ) was obtained as σen24 = 24ɛ.27 σenc = 495ɛ.78 Where, σ = true stress (MPa). ɛ = true strain Figure 2(a). True stress vs True strain log-log graph for EN 24 steel.[4] Volume 2 Issue 4 March ISSN:

5 Figure 2(b). True stress vs True strain log-log graph for ENC steel. [2] Formulations Uncut chip thickness (t )= f * sinϕ Where ϕ = Principal cutting edge angle (degree). f = feed (mm/rev) Formed chip thickness (t 2)= W (mm) Where ρwl W = weight of chip (gm). l = length of chip (mm). w = width of chip (mm) ρ = density of steel (.8 gm/mm 3 ). Width of a chip (w) = d (mm) cos(9 Ѳ) Where d = depth of cut (mm). Ѳ = Principal approach angle (degree) Chip reduction coefficient (ξ) = t 2 (mm) t Von Mises stress σ v =.74*K*(lnξ) n (MPa) Another set of experiments were conducted by face turning on the workpiece at Cutting speed = m/min. Feed =.86 mm/rev. Depth of cut =.2 mm. Machined region from the face surface was sectioned by using hacksaw to prepare sample inorder to identify the presence of any residual stress through XRD study. Cu target was used for the purpose. Sample from the unmachined region was also prepared for the same study. EDX analysis was performed to identify material deposition if any from work material to tool rake face. III. RESULTS AND DISCUSSIONS Analysis of variance considering the experimental data for CRC was done. Results of ANOVA are shown in table 5 and table 6. Table 5. ANOVA analysis for CRC of EN24 machining chip Result Details Source SS df MS Between-treatments F = Within- treatments Volume 2 Issue 4 March ISSN:

6 Total The f-ratio value is The p-value is The result is signification at p <.5. Table 6. ANOVA analysis for CRC of ENC machining chip Result Details Source SS df MS Between-treatments F = Within- treatments Total The f-ratio value is The p-value is The result is signification at p <.5. It is apparent that the experimental CRC data for both EN24 and ENC steels are statistically acceptable (p<.5) and therefore, further study can be explored. From the input and output data, second order regression equations for CRC and von Mises stress are obtained for both the steels using MINITAB software which are mentioned below: - For EN24 Steel b CRC = x -.225x x x ² +.x 2² -.35x 3² -.3x x x x 3 -.6x 2x 3 (eq.a)[4] b VMS = x x x x ² x 2² x 3² x x x x x 2x 3 (eq.b)[4] For ENC Steel b CRC = x -.322x x x +.474x x 3 +.6x x x x x 2x 3 (eq. c)[2] b VMS= x 25.x 2-7x 3-324x x x 3 +.5x x x x 3-374x 2x 3 (eq. d)[2] Using above equations, 3D plots were made using MATLAB software considering depth of cut as constant factor which are mentioned below: - At lowest depth of cut (-) CRC FOR DOC - CRC FOR DOC= - CRC CRC Figure 3(a). Variation of CRC w.r.t cutting speed and feed code for d.o.c code - for EN24 steel. Figure 3(b). Variation of CRC w.r.t cutting speed and feed code for d.o.c code - for ENC steel. From Figure 3(a) at code -, for EN24 steel, CRC increase with increase of speed was observed. Increased speed causes temperature rise in primary deformation zone leading to thermal softening. This causes increased CRC at high speed. Effect of feed on CRC is found to be minimized. From Figure 3(b) at code -, for ENC steel, it was observed that CRC reduced with increase of speed. Strain hardening of the work material occurs at higher speed leading to brittleness transition of the work material. This causes lower CRC at higher speed. Effect of feed on CRC is found to be minimized. Volume 2 Issue 4 March ISSN:

7 VMS FOR DOC - VMS FOR DOC= VMS (in MPa) VMS (in MPa) Figure 4(a). Variation of VMS w.r.t cutting speed and feed code for d.o.c code - for EN24 steel. Figure 4(b). Variation of VMS w.r.t cutting speed and feed code for d.o.c code - for ENC steel. From Figure 4(a) at code -, it is apparent that for EN24 steel, VMS increases with increase of speed. Increase in CRC at higher speed causes increase of VMS. This is attributed to thermal softening during chip formation. Effect of feed on VMS is found to be negligible. From Figure 4(b) at code -, it is seen that for ENC steel, VMS reduces with increase in speed. Reduced VMS at higher speed is owing to brittleness transition of work material. Increased feed causes increase of VMS. Such increase of VMS is due to thermal softening leading to higher CRC. At moderate depth of cut () CRC FOR DOC CRC FOR DOC= CRC 2.2 CRC FEED Figure 5(a). Variation of CRC w.r.t cutting speed and feed code for d.o.c code for EN24 steel Figure 5(b). Variation of CRC w.r.t cutting speed and feed code for d.o.c code for ENC steel..5 VMS FOR DOC VMS FOR DOC= VMS VMS (in MPa) Figure 6(a). Variation of VMS w.r.t cutting speed and feed code for d.o.c code for EN24 steel. Figure 6(b). Variation of VMS w.r.t cutting speed and feed code for d.o.c code for ENC steel. From Figure 5(a) and Figure 5(b), it is observed that at code,en24 and EnC steel follow similar trend as with Figure 3(a) and Figure 3(b). Volume 2 Issue 4 March ISSN:

8 From Figure 6(a), it is seen that at code for EN24 steel, VMS increases with increase in speed which is attributed to thermal softening effect at higher cutting speed. VMS reduces with increase of feed because of brittleness transition of the work material at this cutting condition. From Figure 6(b), it is observed that at code for ENC steel, effect of feed on VMS is seemed to be less significant. Otherwise trend is similar as with Figure 4(b). At highest depth of cut () CRC FOR DOC CRC FOR DOC= CRC 2.8 CRC Figure 7(a). Variation of CRC w.r.t. cutting speed and feed code for d.o.c code for EN24 steel Figure 7(b). Variation of CRC w.r.t. cutting speed and feed code for d.o.c code for ENC steel. From Figure 7(a) at code, for EN24 steel, it is apparent that similar trend is obtained as with Figure 5(a). CRC increases with increase in speed. CRC reduces with increase in feed, which is attributed to the strain hardening effect at higher feed. From Figure 7(b) at code, for ENC steel, almost similar trend is observed as with Figure 5(b). VMS FOR DOC VMS FOR DOC= VMS (in MPa) Figure 8(a). Variation of VMS w.r.t. cutting speed and feed code for d.o.c code for EN24 steel. VMS (in MPa) Figure 8(b). Variation of VMS w.r.t. cutting speed and feed code for d.o.c code for ENC steel..5 From figure 8(a) at code, for EN24 steel, similar trend as with Figure 6(a) is found. VMS reduces with increase of feed because of strain hardening of the work material during chip formation. Such phenomenon causes brittleness transition of work material during chip formation process.sem examination of under surface of the chip (Figure 9(a)) showed the presence of massive crack indicating brittleness transition of the material during chip formation. SEM examination of fractured surface of the chip also showed the chip fracture by brittle mode (Figure 9(b)). Figure 9(a). SEM image of chip under surface Figure 9(b). SEM image of a fractured chip at a cross at 5X magnification for EN24 steel. [4] section at 25X magnification for EN24 steel. [4] Volume 2 Issue 4 March ISSN:

9 From Figure 8(b) at code, it is seen that for ENC steel, VMS increases with increase in speed because of thermal softening. Chip side edge along with top surface was viewed under scanning electron microscope and found that much deformation had taken place in the chip through ductile mode. (Figure (a)) [2]. Moreover, SEM examination of chip fractured surface indicated ductile separation of chip during fracture. Numerous dimples are observed in SEM micro-graphof chip fractured surface (Figure (b)). This finding illustrates the dominating role of temperature so as to cause ductile transition of the material at primary deformation zone during the process of chip formation. VMS reduces with increase in feed. Higher feed causes more strain hardening of the work material leading to reduced VMS at higher feed. Figure (a). SEM image of the side edge of Figure(b). SEM image of the fractured surface of chip at 3X magnification for ENC steel. [2] chip at X magnification for ENC steel. [2] 3. Experimental and predicted analysis Figure (a) and Figure (b) show the variation between experimental and predicted values for CRC of EN24 chip and ENC chip. Figure (a).comparison chart between experimental CRC and predicted CRC for EN24 chip. Figure (b).comparison chart between experimental CRC and predicted CRC for ENC chip. Volume 2 Issue 4 March ISSN:

10 Figure 2(a) and Figure 2(b) show the variation between experimental and predicted values for VMS of EN24 and ENC steels respectively. Figure 2(a).Comparison chart between experimental VMS and predicted VMS for EN24 steel. Figure 2(b).Comparison chart between experimental VMS and predicted VMS for ENC steel. XRD analysis of the work material For EN24 steel Figure 3 (a) Phase position for core region Figure 3(b) Phase position for face turningsurface (un-machined region) obtained from XRD. at V = m/min, f =.86 mm/rev and d.o.c =.2mm obtained from XRD. Volume 2 Issue 4 March 29 3 ISSN:

11 For ENC steel Figure 4 (a).phase position for core region (un-machined region) obtained from XRD Figure 4 (b) Phase position for face turning surface at V = m/min, f =.86 mm/rev and d.o.c =.2mm obtained from XRD. Figure 3(a) and Figure 3(b) show the peaks (α-fe) of the un-machined and machined samples for EN24 steel. From XRD data, it is observed that there is some difference with reference to the peak position considering two conditions. This illustrates the presence of residual stress within the machined sample. Figure 4(a) and Figure 4(b) show the peaks (α-fe) of the un-machined and machined samples for ENC steel. Using XRD data It is seen that there is also peak shift with the machined sample with respect to the peak position for the un-machined sample. This finding confirms the presence of residual stress within the machined workpiece for ENC steel. EDX analysis Considering machining parameters foren24 steel, V = 25m/min, f =.86mm/rev, d.o.c =.5mm and time period (t) = 3min. Table 7. Chemical composition of diffused and deposited element on tool rake face Result Type Weight % Spectrum Label Spectrum 7 C O 6.5 Al.9 Si.76 P. Ti 5.3 Cr. Mn. Fe.5 Ni.4 Mo 3.3 Total. Volume 2 Issue 4 March 29 3 ISSN:

12 Material deposit location. Figure 5(a) Material deposited at location on tool rake face (EDX) Figure5(b). Composition of material deposit at location on tool rake face(edx). Figure 5(a) &Figure 5(b) showthe material deposited location (EDX) and EDX spectrum respectively for EN24 material deposition on tool rake face. It is seen that work material deposit takes place on the tool rake face in addition of which some transport from tool occurred to the deposited material through diffusion (Table 7) Considering machining parameters for ENC steel at V = 25m/min, f =.86mm/rev, doc =.5mm and time period (t) = 3min Table 8. Chemical composition of diffused and deposited element on tool rake face Result Type Weight % Spectrum Label Spectrum 3 C 74.6 Al 4.7 Si 5.8 P.25 S.42 Cr.6 Mn.5 Fe 2.9 Ni.7 Mo.87 Total. Volume 2 Issue 4 March ISSN:

13 Material deposit location 2 Figure 6. (a) Material deposit at location 2 on tool rake face (EDX) Figure 6. (b)composition of material deposit at location 2(EDX). Figure 6(a) &Figure 6(b) show the material deposited location2 (EDX) and the EDX spectrum for ENC material deposition on tool rake face respectively. Material deposition from work material to tool rake face (along with tool elemental diffusion to deposited material) is identified (Table 8) IV. CONCLUSION Effect of feed is to lower the VMS at different depth of cut conditions for EN24 steel. Effect of speed is to raise the VMS at various depth of cut conditions for EN24 steel. Effect of feed at highest depth of cut condition is to reduce the VMS for ENC steel. However, at lowest depth of cut VMS increases with feed. Effect of speed at highest depth of cut is to raise the VMS for ENC steel. However, at lowest depth of cut VMS reduces with speed with ENC steel. Residual stress is found to be present in both the steelswhen machined at higher speed, feed and d.o.c condition. Material transport from work material to tool and tool to work material takes place during machining on EN24 and ENC steels through diffusion. Volume 2 Issue 4 March ISSN:

14 V. ACKNOWLEDGEMENT The authors sincerely and gratefully acknowledge the assistance provided by IIT Kanpur while using various laboratories at IIT Kanpur. VI. REFERENCES [] Vishal Mishra, Nikhil Bharat & Kalyan Chakraborty, Comparative assessment on the machinability of EN 24 and EN C Steels. International Journal of Engineering and Advanced Technology (IJEAT) Volume-8 Issue-3, February 29) ISSN: [2] Vishal Mishra & Dr. Kalyan Chakraborty, Machinability of Nickel Chromium Case Hardened Steel (ENC). Global Journal of Researches in Engineering: A Mechanical and Mechanics Engineering Volume 9 Issue Version. Year 29. Online ISSN: Print ISSN: [3] Geethanjali KS, Ramesha C.M, Chandan B.R, Comparative Studies on Machinability of MCLA Steels EN9 and EN24 Using Taguchi Optimization Techniques. Materials Today: Proceedings 5 (28) [4] Nikhil Bharat, Dr. KalyanChakraborty, "Machinability of en24 steel (87m4)", International Journal of Latest Trends in Engineering and Technology Volume 2 Issue 3 January 29, pp.-7https:// Volume 2 Issue 4 March ISSN: