Multi Output Optimization of CNC High Speed Hard Turning of AISI 52100 Bearing Steel using Taguchi Method and Fuzzy Logic Unit

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-15 Number-3
Year of Publication : 2014
Authors : Rony Mohan , Josephkunju Paul C , Benny Paul


Rony Mohan , Josephkunju Paul C , Benny Paul. "Multi Output Optimization of CNC High Speed Hard Turning of AISI 52100 Bearing Steel using Taguchi Method and Fuzzy Logic Unit", International Journal of Engineering Trends and Technology (IJETT), V15(3),118-123 Sep 2014. ISSN:2231-5381. published by seventh sense research group


In this paper the application of Taguchi method with logical fuzzy reasoning for multi output optimization of high speed CNC turning of AISI 52100 steel alloy using tungsten carbide tool insert of three different radii. The machining parameters (cutting speed, feed rate, depth of cut and nose radius) are optimized with considerations of the multiple performance measures (surface roughness, material removal rate, machining time, tool wear). Taguchi’s concepts of orthogonal arrays, signal to noise (S/N) ratio, ANOVA have been fuzzified to optimize the high speed CNC turning process parameters through a single comprehensive output measure (COM).


[1] A. Attanasio, D. Umbrello, (2012) “Tool wear effects on white and dark layer formation in hardturning of AISI 52100 steel”.
[2] Anil Gupta, Hari Singh, Aman Aggarwal, (2011) Taguchi-fuzzy multi output optimization (MOO) in high speed CNC turning of AISI P-20 tool steel.
[3] Anderson P. Paiva, Joao Roberto Ferreira (2007) “A multivariate hybrid approach applied to AISI 52100 hardened steel turning optimization”
[4] Dale W. Schwach, Y.B. Guo (2006) “A fundamental study on the impact of surface integrity by hard turning on rolling contact fatigue”.
[5] Dr. C. J. Rao, Dr. D. Nageswara Rao (2013) Influence of cutting parameters on cutting force and surface finish in turning operation.
[6] Ezugwu(2005)“Key improvements in the machining of difficult-to-cut aerospace superalloys”
[7] Fredrik Svahn, ÅsaKassman-Rudolphi, Erik Wallén, (2003) The in?uence of surface roughness on friction and wearof machine element coatings.
[8] HamdiAouici, Mohamed AthmaneYallese, (2012) Analysis of surface roughness and cutting force components in hardturning with CBN tool: Prediction model and cutting conditionsoptimization.
[9] Ilhan Asiltürk, (2011) “Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method”
[10] Luiz Gustavo D. Lopes, (2013) “A multivariate surface roughness modeling and optimization under conditions of uncertainty”.
[11] Meng Liu, Jun-ichiro Takagi (2004)Effect of tool nose radius and tool wear on residual stress distribution in hard turning of bearing steel.
[12] M. Bicek,, F. Dumont, C. Courbon,(2012)Cryogenic machiningas an alternative turning process ofnormalizedand hardened AISI 52100 bearing steel.
[13] M.Y. Noordin, V.C. Venkatesh (2004) “Application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel”.
[14] Nabil Jouini, Philippe Revel proceedia(2013) “Characterization of surfaces obtained by precision hard turning ofAISI 52100 in relation to RCF life”.
[15] Pradeep L. Menezes, Kishore “Influence of surface texture and roughness parameters on friction and transfer layer formation during sliding of aluminium pin on steel plate”.
[16] P.G. Benardos, G.-C. Vosniakos (2003) “Predicting surface roughness in machining: a review”
[17] Ramon QuizaSardinas(2006).“Multi-objective optimization of cutting parameters for drilling laminate composite materials by using genetic algorithms”.
[18] Ramon QuizaSardinas(2005),Genetic algorithm-based multi objective optimization of cutting parameters in turning process.
[19] Suha Karim Shihaba,(2014) “A review of turning of hard steels used in bearing and automotive applications”
[20] T.G. Brito, A.P. Paiva, J.R. Ferreira (2014)“A normal boundary intersection approach to multiresponse robust optimization of the surface roughness in end milling process withcombined arrays.”
[21] Yavuz Sun, Hayrettin Ahlatci, (2011) “ Mechanical and wear behaviors of Al–12Si–XMg composites reinforced with in situ Mg2Si particles”.

CNC hard turning, fuzzy logic, AISI 52100, Taguchi, ANOVA.