Analysis of tool vibration and surface roughness with tool wear progression in hard turning: An experimental and statistical approach

Authors

  • Nitin Ambhore Sinhgad College of Engineering, SP Pune University, Pune 41041, M.S., India
  • Dinesh Kamble Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, SP Pune University, Pune, 411048, M.S., India
  • Satish Chinchanikar Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, SP Pune University, Pune, 411048, M.S., India

DOI:

https://doi.org/10.15282/jmes.14.1.2020.21.0506

Keywords:

Hard turning, coated carbide, surface roughness, tool wear, vibration, ANOVA

Abstract

The machined surface quality and dimensional accuracy obtained during hard turning is prominently gets affected due to tool wear and cutting tool vibrations. With this view, the results of tool wear progression on surface quality and acceleration amplitude is presented while machining AISI 52100 hard steel. Central Composite Rotatable Design (CCRD) is employed to develop experimental plan. The results reported that vibration signals sensed in a tangential direction (Vz) are most sensitive and found higher than the vibrations in the feed direction (Vx) and depth of cut direction (Vy). The acceleration signals in all three directions are observed to increase with the advancement of tool wear and good surface finish is observed as tool wear progresses up-to 0.136mm. The vibration amplitude is discovered high in the range 3 kHz – 10 kHz within selected cutting parameter range (cutting speed 60-180mm/min, feed 0.1-0.5mm/rev, depth of cut 0.1-0.5mm). The investigation is extended for the development of multiple regression models with regression coefficients value 0.9. These models found statically significant and give dependable estimates between a tool vibrations and cutting parameters.

References

Shihab SK, Khan ZA, Mohammad A, Siddiquee AN. A review of turning of hard steels used in bearing and automotive applications. Production & Manufacturing Research: An Open Access Journal. 2014;2(1):24-49.

Chinchanikar S, Choudhury SK. Machining of hardened steel-Experimental investigations, performance modeling and cooling techniques: A review. International Journal of Machine Tools & Manufacture. 2015;89:95–109.

Kasim NA, Nuawi MZ, Ghani JA, Rizal M, Ahmad MAF and Che Haron CH, Cutting tool wear progression index via signal element variance. Journal of Mechanical Engineering and Sciences, 2019;13(1), 4596-4612.

Huang Y, Liang SY. Modeling of Cutting Forces under Hard Turning Conditions Considering Tool Wear Effect. Transactions of the ASME. 2015;262/127:262-270.

Shokrani A, Dhokia V, Newman ST. Environmentally conscious machining of difficult-to-machine materials with regard to cutting fluids. International Journal of Machine Tools & Manufacture. 2012;57;83–101.

Chinchanikar S, Choudhury SK. Wear behaviors of single-layer and multi-layer coated carbide inserts in high speed machining of hardened AISI 4340 steel. Journal of Mechanical Science and Technology. 2013;27(5):1451-1459

Zainol A and Yazid MZA, The effect of portable MQL applicator onto carbide insert during turning Inconel 718. Journal of Mechanical Engineering and Sciences, 2018;12(2), 3605-3613.

Mia M, Dhar NR. Prediction and optimization by using SVR, RSM and GA in hard turning of tempered AISI 1060 steel under effective cooling condition. Neural Computing and Applications. 2017; 1–22.

Patil NK, Gopalakrishna K, Sangmesh B, Sudhakar K, Vijaykumar GC, Performance studies on cryogenic treated carbide cutting tool for turning of AISI304 steel. Journal of Mechanical Engineering and Sciences, 2018;12(3), 3927 - 3941.

Suresh R, Basavarajappa S, Samuel GL. Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool. Measurement. 2012;45:1872–1884.

Zahia H, Belbah A, Yallese MA, Mabrouki T, Rigal JF. On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations. Measurement. 2013;46:1671–1681.

Upadhyay V, Jain PK, Mehta NK. In-process prediction of surface roughness in turning of Ti–6Al–4V alloy using cutting parameters and vibration signals. Measurement. 2013;46:154–160.

Asilturk I, Akkus H. Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method. Measurement. 2011;44:1697–1704.

Bouzid L, Yallese MA, Chaoui K, Mabrouki T, Boulanouar L. Mathematical modeling for turning on AISI 420 stainless steel using surface response methodology. Journal of Engineering Manufacture. 2015;229(1):45–61.

Bhuiyan MSH, Choudhury IA. Investigation of Tool Wear and Surface Finish by Analyzing Vibration Signals in Turning Assab-705 Steel. Machining Science and Technology. 2015;19(2):236-261.

Neslusan M, Micieta B, Micietova A, Cillikova M, Mrkvica I. Detection of tool breakage during hard turning through acoustic emission at low removal rates. Measurement. 2015;70:1–13.

Ambhore N, Kamble D, Chinchanikar S, Wayal V. Tool condition monitoring system: A review. Materials Today: Proceedings. 2015;2:3419-3428.

Teti R, Jemielniak K, O’Donnell G, Dornfeld D. Advanced monitoring of machining operations. CIRP Annals - Manufacturing Technology. 2010;79:717-739.

Gonzalez-Laguna A, Barreiro J, Fernandez-Abia A, Alegre E. Gonzalez- Castro V. Design of a TCM system based on vibration signal for metal turning processes. Procedia Engineering. 2015;132:405 – 412.

Kilundu B, Dehombreux P, Chiementin X. Tool wear monitoring by machine learning techniques and singular spectrum analysis. Mechanical Systems and Signal Processing. 2011;25:400–415.

Grynal D, Srinivasa PP, Puneet NP, Ning F. Surface roughness evaluation using cutting vibrations in high speed turning of Ti-6Al-4V -an experimental approach. International Journal of Machining and Machinability of Materials. 2016;18(3):288-312.

Prasad BS, Babu MP. Correlation between vibration amplitude and tool wear in turning: Numerical and experimental analysis. Engineering Science and Technology an International Journal. 2017;20:197–211.

Ozel T, Hsu T, Zeren E. Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel. International Journal Advanced Manufacturing Technology. 2005;25:262–269.

Montgomery DC, Design and Analysis of experiments, 6th ed. John Wiley and Sons India Pvt. Ltd.;2014.

Boy M, Yasar N, Ciftci I. Experimental investigation and modelling of surface roughness and resultant cutting force in hard turning of AISI H13 steel. IOP Conference Series: Materials Science and Engineering. 2016;161:1-10.

Che-Haron CH, Jawaid A. The effect of machining on surface integrity of titanium alloy Ti-6Al-4V. Journal of Materials Processing Technology. 2005;166(2):188–192.

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Published

2020-03-23

How to Cite

[1]
N. Ambhore, D. Kamble, and S. Chinchanikar, “Analysis of tool vibration and surface roughness with tool wear progression in hard turning: An experimental and statistical approach”, J. Mech. Eng. Sci., vol. 14, no. 1, pp. 6461–6472, Mar. 2020.

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