Tool Life Modeling in High Speed Turning of AISI 4340 Hardened Steel with Mixed Ceramic Tools by Using Face Central Cubic Design
(*) Corresponding author
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)
Tool life estimation for the cutting tool before the machining process is important due to economic and quality consideration. Thus, developing a model that can predict the tool life with high accuracy is an important issue. This paper deals with developing a new model of tool life for mixed ceramic tools in turning hardened steel AISI 4340 based on experimental tests. The experiments were planned and implemented using Central Composites Design (CCD) of Response Surface Methodology (RSM) with three input factors: cutting speed, feed rate and negative rake angle. The Face Central Cubic Design has been used as a special case of CCD. The analysis of variance (ANOVA) has been conducted to analyze the influence of process parameters and their interaction during machining. The first and second order models have been developed. It was found that the second order model provide higher accuracy prediction than the first order model. It was observed that the cutting speed is the most significant factor that influences the tool life for the two models, followed by the feed rate then the negative rake angle. The predicted values are confirmed by using validation experiments.
Copyright © 2013 Praise Worthy Prize - All rights reserved.
T. Ozel, and A. Nadgir, Predictions of flank wear by using back propagation neural network modeling when cutting hardened H-13 steel with chamfered and honed CBN tools. International Journal of Machine Tools & Manufacture (42) 287–297. PII: S0890-6955(01)00103-1(2002).
M. H. F Al Hazza, Experimental Study of flank wear in High Speed Turning of Stainless Steel AISI 304. Journal of Advanced Science and Engineering Research, 3(2). (2013).
A. G. Mamalis, J. Kundrak & M. Horvath, Wear and tool life of CBN cutting tools. The International Journal of Advanced Manufacturing Technology, 20(7), 475-479. (2002).
W. B. Sai, An investigation of tool wear in high-speed turning of AISI 4340 steel. The International Journal of Advanced Manufacturing Technology, 26(4), 330-334. (2005).
J.G., Lima, A.M., Abrao, M. Faustino, and J.P., Davim, Hard turning: AISI 4340 high strength low alloy steel and AISI D2 cold work tool steel, Journal of Materials Processing Technology, vol. 169, pp. 388–395. (2005),
L Ginta Turnad., A.K.M Nurul Amin., A.N.M Karim., G. Sutjipto Agus, tool life prediction by response surface methodology for end milling titanium alloy ti–6al–4v using uncoated carbide inserts International Conference on Mechanical Engineering 2007 (ICME2007) 29- 31 December 2007, Dhaka, Bangladesh ICME07-AM-11(2007).
E. Y. T. Adesta, & Muataz Hazza F. Al Hazza, (2011). Tool Life in High Speed Turning with Negative Rake Angle. Advanced Materials Research, 264, 1009-1014.
E. Y. T. Adesta, M. Hazza F. Al Hazza, Riza, M., & Agusman, D. (2010). Tool life estimation model based on simulated flank wear during high speed hard turning. European Journal of Scientific Research, 39(2), 265-278.
E. Y. T Adesta, M. Riza, M. H. F., Al Hazza, D. Agusman and Rosehan, Tool Wear and Surface Finish Investigation in High Speed Turning Using Cermet Insert by Applying Negative Rake Angles, European Journal of Scientific Research ISSN 1450-216X Vol.38 No.2, pp.180-188. (2009)
A.G. Jaharah , N. A Mohd , O. Kamal, C H. Che Hassan,Tool Life and Surface Roughness of FCD 700 Ductile Cast Iron when Dry Turning Using Carbide ToolAdvanced Materials Research (Volumes 126 - 128) pp 347-352 Doi.10.4028/www.scientific.net/AMR.126-128.347(2010)
E. Y. T Adesta, M.H.F Al Hazza, A. Delvis, M. Riza, A. M. Ali, (2011). Tool Life in High Speed Turning With Negative Rake Angle. Advanced Materials Research Vols. 264-265 pp 1009-1014. (2011)
Y. Sahin, Comparison of tool life between ceramic and cubic boron nitride (CBN) cutting tools when machining hardened steels. Journal of materials processing technology 2 0 9, 3478–3489. doi:10.1016/j.jmatprotec. (2009).
N. Mandal B. Doloi and B. Mondal, Development of flank wear prediction model of Zirconia Toughened Alumina (ZTA) cutting tool using response surface methodology International Journal of Refractory Metals and Hard Materials Volume 29, Issue 2, March 2011, Pages 273-280 doi:10.1016/j.ijrmhm.2010.12.001.
M. H. F. Al Hazza and E. Y. T. Adesta, Flank Wear Modeling In High Speed Hard Turning By Using Artificial Neural Network And Regression Analysis. Advanced Materials Research Vols. 264-265, pp 1097-1101. (2011).
U., Natarajan V. M. Periasamy and Saravanan, Application of particle swarm optimisation in artificial neural network for the prediction of tool life The International Journal of Advanced Manufacturing Technology Volume 31, Numbers 9-10, 871-876, DOI: 10.1007/s00170-005-0252-1(2007)
D., Dinakaran, S, Sampathkumar and N, Sivashanmugam. An experimental investigation on monitoring of crater wear in turning using ultrasonic technique International Journal of Machine Tools & Manufacture 49 (2009) 1234–1237. doi:10.1016/j.ijmachtools.2009.08.001. (2009).
Srinivasan, S., Sathyanarayan, R., Srivatsan, L., Vijaya Ramnath, B., Optimization of tool life using linear regression analysis, (2012) International Review of Mechanical Engineering (IREME), 6 (3), pp. 405-410.
Ranganathan, S., Senthilvelan, T., Prediction of machining parameters of surface roughness of GFRP composite by applying ANN and RSM, (2012) International Review of Mechanical Engineering (IREME), 6 (5), pp. 1068-1073.
F. Mahfoudi, L. Boulanouar, G List Experimental study of the influence of the static stiffness of lathes on the tool wear behaviour. J Eng Appl Sci 2:516–523(2007)
Thirumalai, R., Selvarani, P., Senthilkumaar, J.S., Machinability investigations of flank wear in carbide cutting tool, (2012) International Review of Mechanical Engineering (IREME), 6 (4), pp. 837-845.
ISO 3685, Tool life testing with single-point turning tools, International Standard organization, 2nd edition. Geneva, Switzerland. (1993).
T., Moriwak, S., Tangjitsitcharoen, and T., Shibasaka, Development of sequential optimization method for CNC turning based on in –process tool wear monitoring. JSME international journal, series C, Vol 48 no. 4. (2005).
In-Jun Jeong and K. J Kim, An interactive desirability function method to multi response optimization. European Journal of Operational Research. 195 412–426. (2009).
I. Mukherjee, and P. K Ray. A review of optimization techniques in metal cutting processes. Computers and Industrial Engineering (50) pp 15-34. (2006).
N. Tosun and L. Ozler A study of tool life in hot machining using artificial neural networks and regression analysis method. Journal of Materials Processing Technology. 124 99–104. (2002).
V.N., Gaitonde, S. R., Karnik L. Figueira, & J. P., Davim, Performance comparison of conventional and wiper ceramic inserts in hard turning through artificial neural network modeling. International Journal Advanced Manufacturing Technology. DOI 10.1007/s00170-010-2714-3. (2010).
K., Hashmi, M. A., El Baradie, & M. Ryan, Fuzzy logic based intelligent selection of machining parameters. Computers & industrial engineering, 35(3), 571-574. (1998).
D. G., Montgomery, Design and Analysis of Experiments, 5th Edition, John Wiley and Sons, Inc. (2001).
M. J. Anderson, and P. J.,Whitcomb, RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments. Productivity Inc.Portland. 2005.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2023 Praise Worthy Prize