Optimization of process parameters during turning of Inconel 625

Optimization of process parameters during turning of Inconel 625

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Materials Today: Proceedings xxx (xxxx) xxx

Contents lists available at ScienceDirect

Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr

Optimization of process parameters during turning of Inconel 625 Shankar P. Waghmode ⇑, Uday A. Dabade Walchand College of Engineering, Sangli 416415, India

a r t i c l e

i n f o

Article history: Received 23 July 2019 Accepted 5 August 2019 Available online xxxx Keywords: Inconel 625 High speed turning Surface roughness ANOVA Taguchi method

a b s t r a c t One of the important machining technology is high speed machining, It is used for difficult to machine materials like nickel base alloy, titanium etc. For grinding process important alternative is came in to consideration is hard turning process. In this study, high speed turning operation is carried out on Inconel 625. Inconel 625 material is nickel base material which is having good corrosion resistance, heat resistance alloy etc. It is majorly used in chemical processing, oil and gas industry, nuclear power plant, submarine manufacturing industry. Because of high strength and several work hardening tendency it is difficult to machine. High speed machine of Inconel 625 and other Inconel alloy is severally used in machining of power plant equipment, aerospace components, sub-marine parts etc. The main objective of this experimentation is to examine and observe on response parameter like cutting forces and surface roughness on input parameter such as cutting speed, feed rate and depth of cut. Experimentation was conducted as per Taguchi’s L9 orthogonal array during turning operation. The results are analyzed using analysis of variance (ANOVA) method. This analysis shows the percentage contribution of parameters. Ó 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 1st International Conference on Manufacturing, Material Science and Engineering.

1. Introduction In a global situation were a complete industrialization is growing fast and manufacturing processes have an increasing importance in order to improve productivity in those industries. Nowadays, a competition for quality results has gained importance over the years, being better or producing better quality finish results in the products released that satisfy requirements and specifications posed by functional demands is a manner to establish a difference. This difference is only achieved by continues improvement in manufacturing processes. Inconel 625 is used for its high strength, creep, tensile strength. Due to outstanding property of Inconel 625, it is used in sea water equipment. It is having excellent weld ability, braze ability, fabricability and corrosion resistance. It is necessary to fulfill the demand of industry and satisfy customer demand in all aspect. 2. Literature review D’Addona and Raykar [1] investigated OHNS steel is used as work piece. Average is taken of three points on each experiment ⇑ Corresponding author. E-mail address: [email protected] (S.P. Waghmode).

for surface roughness value. Hard turning give advantages for turning operation like it can be used to remove material with single machine set up where set up time is saved. The turning process is used for the investigation of various parameters to achieve surface roughness value with the help of Wiper geometry insert of 1.2 mm nose radius. Feed rate and depth of cut is required less, cutting speed is required more it is desirable in order to lower the tool wear rate and reduce surface roughness. Suresh et al. [2] performed dry turning experiments on AISI 4340 and after analysis author concluded that statistical as well as physical influence made by feed parameter on machining. As the depth of cut and feed rate increases the forces are also going to be increase. Cutting force decreases as the cutting speed goes on increasing. This is because of rise in temperature in the share plan area, which results in decrease in shear strength of the work material. Das et al. [3] performed experiment on Al 7075/SiCp material work piece. Turning is done with the help of uncoated tungsten carbide inserts in dry cutting condition, the surface roughness reduced with rise in cutting speed but there was increase with increase in either depth of cut or feed. As the feed rate or depth of cut increases the surface roughness value increase means surface quality degraded. Dry cutting condition high speed machining at low levels of depth of cut and feed rate is good for surface excellence. Kosaraju et al. [4] conducted turning tests on Inconel alloy

https://doi.org/10.1016/j.matpr.2019.08.138 2214-7853/Ó 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 1st International Conference on Manufacturing, Material Science and Engineering.

Please cite this article as: S. P. Waghmode and U. A. Dabade, Optimization of process parameters during turning of Inconel 625, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.08.138

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625 with the help of L9 orthogonal array. The view behind conducting the experiment is to observe the effect of various cutting conditions on surface roughness and cutting force. Concluded that was optimum combination of controllable factors and their levels are 75 m/min cutting speed, 0.103 mm/rev feed, 0.2 mm depth of cut is good for minimum force and surface roughness. Bharilya et al. [5] had researched the optimize process parameters for turning process on the material like aluminium alloys, brass and carburized mild steel. This material is machined on CNC turning machine. It is observed that there are three parameters that are optimized such as spindle speed, depth of cut and feed rate that affects surface finishing and combination of experiment array for Carburized Mild Steel, Aluminium Alloys and Brass for surface quality. Kartheek et al. [6] have done experiment on the Inconel 718 material, up to 40 HRC hardness heat treated. He concluded that GRG used for measuring combined effect of many responses. It is influenced by feed rate (63.70%) and depth of cut (18.98%), cutting speed (6.92%) are having a minimum effect. Dabade and Jadhav [7] discuss in literature that material al/SiCp metal matrix composition machining was done with preheating condition with the help of PVD coated insert. Material size is taken as diameter 22 mm and 60 mm length. Author observes that after performing and analysis of experiment, feed and depth of cut have important effect on cutting forces. Feed and preheating have important impact on surface roughness. Feed rate and depth of cut at 95 percent level are responsible for all three machining forces.

Table 4.1 Taguchi optimization process parameter. Cutting Parameter

Unit

Cutting speed Feed rate Depth of cut

m/min mm/rev mm

Level of factor 1

2

3

75 0.08 0.1

100 0.10 0.2

125 0.12 0.3

3. Selection of work piece and tool material The experiments have to carry out for suggesting the optimum parameters for performing hard turning operation. The literature reviewed to select the work piece and cutting tool material.

Fig. 4.1. Experimental setup for turning operation.

3.1. Work piece material

4.1. Design of experiment based on Taguchi design

This experiment was performed in the dry condition. The experiments conducted are based on the orthogonal array design. Work piece material used for investigation is Inconel 625. This material is difficult to cut material. High strength and corrosion resistance is the main property of this material. Turning operation is conducted on diameter 25 mm and length 400 mm solid round bar.

The experimental work is designed as per Taguchi method. In the present study, L9 orthogonal array is employed. Orthogonal array provides the minimum number of experiment which is different at each level. In this, three controlled factor is selected that are as follows cutting speed, feed rate, depth of cut. This is varied in the three levels each to effectively cover up the whole range accessible by machine tool. Table 4.1 show the process parameter selected for this experimentation.

3.2. Cutting tool material Selected tool material for turning operation is CNMG 120408 MS, PVD coated carbide inserts. Tool holder used for this type of specification insert holding is MTJNL2525M12. Table 3.1 shows the specifications of cutting insert. 4. Methodology The workpiece material and tool material has selected for hard turning material based upon the literature review. The experiments has to performed with specified level of input parameter and output parameter considered for optimize the results to suggest best parameters for performing hard turning operation. Table 3.1 Cutting inserts specification. Parameters

Dimension

Included angle Clearance angle Thickness Nose radius

80° 0° 4.76 mm 0.8 mm

4.2. Experimental set up The experiments conducted are based on the orthogonal array experimental design. Dynamometer is mounted on turret for measuring the forces. Cutting force, thrust force and feed force is measured by using dynamometer shown in Fig. 4.1. Dynamometer used in this experimentation is made up of Kistler. Piezoelectric sensor is used to measure forces in this dynamometer. 5. Result and discussion The experimental work was organized based on the L9 Orthogonal array design. Repetition of L9 orthogonal array is taken with the same parameter and levels. The average of the both reading has taken for each response variables to result the Taguchi. The results instated from the experimental runs executed, according to the orthogonal array design shown in Table 4.1. The influence of the turning parameters and its consequence on the surface roughness and various cutting forces has been analysed. Table 5.1 shows the results of experiment performed. In this table Fy indi-

Please cite this article as: S. P. Waghmode and U. A. Dabade, Optimization of process parameters during turning of Inconel 625, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.08.138

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S.P. Waghmode, U.A. Dabade / Materials Today: Proceedings xxx (xxxx) xxx Table 5.1 Experimental result for Taguchi L9 orthogonal array. Cutting velocity (m/min)

Feed rate(mm/rev)

Depth of cut (mm)

Surface roughness (µm)

75 75 75 100 100 100 125 125 125

0.08 0.1 0.12 0.08 0.1 0.12 0.08 0.10 0.12

0.1 0.2 0.3 0.2 0.3 0.1 0.3 0.1 0.2

0.9 0.99 1.4 0.85 2.01 0.7 0.91 0.61 1.18

Forces (N) Fy

Fx

Fz

56.32 111.06 126.42 110.3 115.38 75.03 75.24 90.64 115.77

39.28 90.9 141.07 101.52 100.88 58.41 68.80 70.40 100.32

25.8 60.13 70.84 59.27 59.73 19.92 45.81 32.99 55.14

Table 5.2 ANOVA for cutting force. Parameters

DF

Contribution (%)

F-Value

P-Value

Cutting Speed (m/min) Feed rate (mm/rev) Depth of Cut (mm) Error Total

2 2 2 2 8

1.36 27.5 55.05 16.09 100

1.08 11.71 13.42

0.922 0.049 0.026

R- sq = 83.91% R-sq (adj) = 75.63%.

Fig. 5.1. Main effect plot for SN ratios of cutting force.

Fig. 5.2. Main effect plot for SN ratios of thrust force.

cates cutting force, Fx indicates thrust force and Fz indicates feed force. After noting down results, analysis of variance for each response variable is analysed with Minitab 17 software. Table 5.2 shows ANOVA for cutting force which show feed rate and depth of cut are the most influencing factor for cutting speed. Depth of cut contributes 55.05% and p value of 0.026 and having fvalue is 13.42. As the cutting speed increases the force required for cutting is decreasing. For cutting force signal to noise ratio must be smaller

the better. Preferably the optimum parameter for cutting force is cutting speed 125 m/min, feed rate 0.08 mm/rev, depth of cut 0.1. Fig. 5.1 shows signal to noise ratio. Analysis of variance shows that depth of cut is key factor influencing on thrust force. F-value 8.45 for depth of cut and p-value is 0.011. R-square is 77.24 present. Table 5.3 shows contribution of parameter for thrust force. For thrust force SN ratio must be smaller as shown in Fig. 5.2. As the feed rate and depth of cut increases the forces also increases. As

Table 5.3 ANOVA for thrust force. Parameters

DF

Contribution (%)

F-Value

P-Value

Cutting Speed (m/min) Feed rate (mm/rev) Depth of Cut (mm) Error Total

2 2 2 2 8

2.42 18.99 55.83 22.76 100

3.11 10.83 8.45

0.140 0.055 0.011

R- sq = 77.24% R-sq (adj) = 68.97%.

Please cite this article as: S. P. Waghmode and U. A. Dabade, Optimization of process parameters during turning of Inconel 625, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.08.138

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Table 5.4 ANOVA for feed force. Parameters

DF

Contribution (%)

F-Value

P-Value

Cutting Speed (m/min) Feed rate (mm/rev) Depth of Cut (mm) Error Total

2 2 2 2 8

3.85 3.37 83.39 9.39 100

4.21 10.36 8.88

0.509 0.036 0.010

R- sq = 90.61% R-sq (adj) = 62.43%.

ter. Contribution of Rsquare is 90.61% Signal to noise ratios must be smaller the better for forces because smaller the forces longer the tool life. Fig. 5.3 shows the main effect plot for SN ratios for feed force. Table 5.5 shows the contribution of depth of cut is more in percentage value. R square value is 81.11%. Error in this analysis is 18.89%. Most influencing parameter is depth of cut and second most affecting parameter is feed rate. Fig. 5.4 shows the main effect plot for SN ratio for surface roughness which shows that as the depth of cut increases with decrease in the surface quality. As the cutting speed increases the surface quality increases. 6. Conclusion The experimental work involves analysis of cutting forces, surface roughness in turning on Inconel 625. Give the following conclusions:  Analysis of variance suggests that depth of cut shows maximum contribution (55.05%) on cutting force.  In thrust force also depth of cut contributes 55.83% which is most influence parameter. As the depth of cut increases thrust force increase.  Analysis of variance for feed force contributing factor is depth of cut 83.39%.  Feed rate and depth of cut is highly affecting parameters on surface roughness. 20.61% and 51.68% contribution respectively. Rise in feed rate will rise the surface roughness value.  Feed rate and depth of cut increases the cutting forces are also increases. In cutting speed, it shows the decreasing trend.

Fig. 5.3. Main effect plot for SN ratios of feed force.

Table 5.5 ANOVA for surface roughness. Parameters

DF

Contribution (%)

F-Value

P-Value

Cutting Speed (m/min) Feed rate (mm/rev) Depth of Cut (mm) Error Total

2 2 2 2 8

8.82 20.61 51.68 18.89 100

3.31 6.37 11.79

0.766 0.031 0.023

R- sq = 81.11% R-sq (adj) = 71.05%.

Acknowledgements The author would like to thank Department of Mechanical Engineering, Walchand College of Engineering, Sangli for providing support. References [1] D.M. D’Addona, S.J. Raykar, Analysis of surface roughness in hard turning using wiper insert geometry, in: 48th CIRP Conference on Manufacturing Systems CIRP CMS, 2015, pp. 841–846. [2] R. Suresh, S. Basavarajappa, G.L. Samuel, Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool, Measurement (2012) 1872– 1884. [3] D. Das, R. Kumar Thakur, A. Kumar Chaubey, A. Kumar Sahoo, Optimization of machining parameters and development of surface roughness models during turning Al-based metal matrix composite, ICMPC (2017) 4431–4437. [4] S. Kosaraju, M.V. Kumar, N. Sateesh, Optimization of machining parameter in turning Inconel 625, ICMPC (2017) 5343–5348. [5] R.K. Bharilya, R. Malgaya, L. Patidar, R.K. Gurjar, A.K. Dr, Jha,, Study of optimised process parameters in turning operation through Force Dynamometer on CNC Machine, in: 4th International Conference on Materials Processing and Characterization, 2015, pp. 2300–2305. [6] G. Kartheek, K. Srinivas, C. Devaraj, Optimization of residual stresses in hard turning of super alloy Inconel 718, ICMPC (2017) 4592–4600. [7] U.A. Dabade, M.R. Jadhav, Experimental study of surface integrity of Al/SiC particulate metal–matrix composites in hot machining, in: 48th CIRP Conference on MANUFACTURING SYSTEMS - CIRP CMS, 2015, pp. 914–919.

Fig. 5.4. Main effect plots for SN ratios of surface roughness.

cutting speed increase the force required for cutting the material is also required less. Table 5.4 shows the contribution in percentage of each parameter. Lesser the p value indicates most influencing parame-

Further reading [8] Phillips J Ross, Taguchi Technique for quality engineering, Mc-Graw-Hill, New York, USA.

Please cite this article as: S. P. Waghmode and U. A. Dabade, Optimization of process parameters during turning of Inconel 625, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.08.138