Analysis of Main Optimization Techniques in Predicting Surface Roughness in Metal Cutting Processes

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This paper collects the main methodologies and tools employed for predicting the surface roughness. The goal of this work is to provide compact and adequate information that could be useful in metal cutting industries to select the techniques and optimization tools that best suit to their needs and particular requirements. Each approach, with its advantages and disadvantages, is outlined and the present and future trends are discussed. As result, a quick guide for using practitioners of mentioned industrial sector is provided in form of tables that relate: machining parameters, cutting tool properties, workpiece properties and cutting phenomena with the different techniques and optimization tools usually employed to analyze the different parameters and phenomena involved in the process of surface roughness generation.

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November 2012

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[1] D.C. Montgomery: Design and analysis of experiments (6th ed. Wiley, New York 2005).

Google Scholar

[2] DIN4760. Form Deviations; Concepts; Classification System (Deutches Institut Fuer Normung 1982).

Google Scholar

[3] P.G. Benardos and G.C. Vosniakos: Int. J. Mach. Tool Manu. Vol. 43 (2003), p.833

Google Scholar

[4] P.G. Benardos and G.C. Vosniakos: Robot. Cim-Int. Manuf. Vol. 18 (2002), p.343

Google Scholar

[5] C. Lu: J. Mater. Process. Tech. Vol. 205 (2008), p.439

Google Scholar

[6] K.F. Ehmann and M.S. Hong: CIRP Ann.-Manufact. Techn. Vol. 43 (1994), p.483

Google Scholar

[7] W. Grzesik: Wear Vol. 194 (1996), p.143

Google Scholar

[8] S.C. Lin and M.F. Chang: Int. J. Mach. Tool Manu. Vol. 38 (1998), p.763

Google Scholar

[9] C-CA. Chen, W.C. Liu and N.A. Duffie: Int. J. Mach. Tool Manufact. Vol.38 (1998), p.543

Google Scholar

[10] P. Muñoz-Escalona and Z. Cassier: Wear Vol. 218 (1998), p.103

Google Scholar

[11] K.Y. Lee, M.C. Kang, Y.H. Jeong, et al.: J. Mater. Process. Tech. Vol. 113 (2001), p.410

Google Scholar

[12] D.Y. Jang, Y.G. Choi, H.G. Kim, et al.: Int. J. Mach. Tool Manufact. Vol. 36 (1996), p.453

Google Scholar

[13] C. Beggan, M. Woulfe, P. Young, et al.: Int. J. Adv. Manuf. Tech. Vol. 15 (1999), p.737

Google Scholar

[14] S.A. Coker and Y.C. Shin: Int. J. Mach. Tool Manufact. Vol. 36 (1996), p.411

Google Scholar

[15] I. Mukherjee and P.K. Ray: Comput. Ind. Eng. Vol. 50 (2006), p.15

Google Scholar

[16] O.B. Abouelatta and J. Madl: J. Mater. Process. Tech. Vol. 118 (2001), p.269

Google Scholar

[17] C.X.J. Feng and X. Wang: Int. J. Adv. Manuf. Tech. Vol. 20 (2002), p.348

Google Scholar

[18] A.K. Ghani and I.A. Choudhury: J. Mater. Process. Tech. Vol. 127 (2002), p.17

Google Scholar

[19] K.L. Petri, R.E. Billo and B. Bidanda: J. Manuf. Sci. Vol. 17 (1998), p.52

Google Scholar

[20] F. Cus and U. Zuperl: J. Mater. Process. Tech. Vol. 173 (2006), p.281

Google Scholar

[21] T. Matsumura, H. Sekiguchi and E. Usui: J. Mater. Process. Tech. Vol. 62 (1996), p.440

Google Scholar

[22] S. Varghese and V. Radhakrishnan: J. Mater. Process. Tech. Vol. 44 (1994), p.353

Google Scholar

[23] R. Azouzi and M. Guillot: Int. J. Mach. Tool Manufact. Vol. 37 (1997), p.1201

Google Scholar

[24] Y.H. Tsai, J.C. Chen and S.J. Lou: Int. J. Mach. Tool Manufact. Vol. 39 (1999), p.583

Google Scholar

[25] W.S. Lin, B.Y. Lee and C.L. Wu.: J. Mater. Process. Tech. Vol. 108 (2001), p.286

Google Scholar

[26] S.G. Wang and Y.L. Hsu, in: One-pass milling machining parameter optimization to achieve mirror surface roughness, volume 193 of Proceedings of the Institution of Mechanical Engineers, chapter, 1, Part B: Journal of Engineering Manufacture (2005).

DOI: 10.1243/095440505x8064

Google Scholar

[27] J.P. Davim, V.N. Gaitonde and S.R. Karnik: J. Mater. Process. Tech. Vol. 205 (2008), p.16

Google Scholar

[28] D. Karayel: J. Mater. Process. Tech. Vol. 209 (2009), p.3125

Google Scholar

[29] A.M. Zain, H. Haron and S. Sharif: Expert Syst. Appl. Vol. 37 (2010), p.1755

Google Scholar

[30] I. Asiltürk and M. Çunkaş: Expert Syst. Appl. Vol. 38 (2011), p.5826

Google Scholar

[31] X.P. Li, K. Iynkaran and A.Y.C. Nee: J. Mater. Process. Tech. Vol. 89-90 (1999), p.224

Google Scholar

[32] W. Grzesik and S. Brol: J. Mater. Process. Tech. Vol. 134 (2003) p.265

Google Scholar

[33] M. Correa, C. Bielza and J. Pamies-Teixeira: Expert Syst. Appl. Vol. 36 (2009), p.7270

Google Scholar

[34] H.J. Zimmerman: Int. J. Gen. Syst. Vol. 2 (1976), p.209

Google Scholar

[35] Kwon and G.W. Fisher: J. Manuf. Syst. Vol. 21(6) (2002), p.440

Google Scholar

[36] S.J. Lou and J.C. Chen: Comput. Ind. Eng. Vol.33 (1997), p.401

Google Scholar

[37] J.C. Chen and M. Savage: Int. J. Adv. Manuf. Tech. Vol. 17 (2001), p.670.

Google Scholar

[38] Y.T. Chen and S.R.T. Kumara: Int. J. Prod. Res. Vol. 36 (1998), p.395

Google Scholar

[39] R. Javadpour and G.M. Knapp: Comput. Ind. Eng. Vol. 45 (2003), p.323

Google Scholar

[40] Y. Jiao, S. Lei, Z.J. Pei, et al.: Int. J. Mach. Tool Manufact. Vol. 44 (2004), p.1643

Google Scholar

[41] E.D. Kirby, J.C. Chen and J.Z. Zhang: Expert Syst. Appl. Vol. 30 (2006), p.592

Google Scholar

[42] N.R. Abburi and U.S. Dixit: Robot. Cim-Int. Manuf. Vol. 22 (2006), p.363

Google Scholar

[43] R.Y. Kuo and P.H. Cohen: Fuzzy Set. Syst. Vol. 98 (1998), p.15

Google Scholar

[44] S-Y. Ho, K-C. Lee, S-S. Chen, et al.: Int. J. Mach. Tool Manufact. Vol. 42 (2002), p.1441

Google Scholar

[45] E.D. Kirby and J.C. Chen: Comput. Ind. Eng. Vol. 53 (2007), p.30

Google Scholar

[46] M. Dong and N. Wang: Appl. Math. Model. Vol. 35 (2011), p.1024

Google Scholar

[47] J. Kopac, M. Bahor and M. Sokovic: Int. J. Mach. Tool Manufact. Vol. 42 (2002), p.707

Google Scholar

[48] M. Thomas and Y. Beuchamp: Int. J. Mach. Tool Manu. Vol. 43 (2003), p.1093

Google Scholar

[49] A.H. El-Sinawi and R. Kashani: J. Mater. Process. Tech. Vol. 167 (2005), p.54

Google Scholar

[50] G.A. Hassan and S.M.A. Suliman: Int. J. Prod. Res. Vol. 28 (1990), p.1057

Google Scholar

[51] G. Taguchi: System of experimental design, vol 2 (American Supplier Institute, New York 1987).

Google Scholar

[52] W.H. Yang and Y.S. Tarng: J. Mater. Process. Tech. Vol.84 (1998), p.122

Google Scholar

[53] J.P. Davim: J. Mater. Process. Tech. Vol. 116 (2001), p.305

Google Scholar

[54] A. Manna and B. Bhattacharyya: Int. J. Adv. Manuf. Tech. Vol. 23 (2004), p.658

Google Scholar

[55] Y. Tzeng and M. Jean: Robot. Cim-Int. Manuf. Vol. 21 (2005), p.506

Google Scholar

[56] M. Nalbant, H. Gökkaya and G. Sur: Mater. Design Vol. 28 (2007), p.1379.

Google Scholar

[57] I. Asiltürk and H. Akkuş: Measurment Vol. 44 (2011), p.1697

Google Scholar

[58] A. Gupta, H. Singh and A. Aggarwal: Expert Syst. Appl. Vol. 38 (2011), p.6822

Google Scholar

[59] M. Villeta, E.M. Rubio, J.M. Sáenz de Pipaón, et al., in: Mater. Manuf. Process. Vol. 26 (2011), p.1503.

Google Scholar

[60] M.Y. Noordin, V.C. Venkatesh, S. Sharif, et al.: J. Mater. Process. Tech. Vol. 145 (2004), p.46

Google Scholar

[61] W.M. Carlyle, D.C. Montgomery and G.C. Runger: J. Qual. Technol. Vol. 32 (2000), p.1

Google Scholar

[62] G. Steenackers, F. Presezniak and P. Guillaume: Comput. Ind. Eng. Vol. 57 (2009), p.847

Google Scholar

[63] K. Taramen: Int. J. Prod. Res. Vol. 12 (1974), p.233

Google Scholar

[64] M. Alauddin, M.A. El-Baradie and M.S.J. Hashmi: J. Mater. Process. Tech. Vol. 55 (1995), p.123

Google Scholar

[65] A. Mansour and H. Abdalla: J. Mater. Process. Tech. Vol.124 (2002), p.183

Google Scholar

[66] M.J. Davidson, K. Balasubramanian and G.R.N. Tagore: J. Mater. Process. Tech. Vol. 202 (2008), p.41

Google Scholar

[67] Y. Sahin and A.R. Motorcu: Int. J. Refract. Met. H. Vol. 26 (2008), p.84

Google Scholar

[68] D.I. Lalwani, N.K. Mehta and P.K. Jain: J. Mater. Process. Tech. Vol. 206 (2008), p.167

Google Scholar

[69] P. Sahoo, T. K. Barman and B.C. Routara: Int. J. Manu. Res. Vol. 3 (2008), p.360

Google Scholar

[70] J.S. Dureja, V.K. Gupta, V.S. Sharma, et al. in: Design optimization of cutting conditions and analysis of their effect on tool wear and surface roughness during hard turning of AISI-H11 steel with a coated—mixed ceramic tool, volume 223 of Proceedings of the Institution of Mechanical Engineers, chapter 11, Part B: Journal of Engineering Manufacture (2009).

DOI: 10.1243/09544054jem1498

Google Scholar

[71] K. Bouacha, M.A. Yallese, T. Mabrouki, et al.: Int. J. Refract. Met. H. Vol. 8 (2010), p.349

Google Scholar

[72] S. Neşeli, S. Yalidz and E. Türkeş: Measurement Vol. 44 (2011), p.580

Google Scholar

[73] K. Fuh and C.F. Wu: Int. J. Mach. Tool Manufact. Vol. 35 (1995), p.1187

Google Scholar

[74] C. Ezilarasan, V.S. Senthil, A.Velayudham, et al.: Trans. Nonferrous Met. Soc. China Vol. 21 (2011), p. (1986)

Google Scholar

[75] F. Glover: Interfaces Vol. 20 (1990), p.74

Google Scholar

[76] J.H. Holland: Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence (MIT Press, Massachusetts 1992).

DOI: 10.7551/mitpress/1090.001.0001

Google Scholar

[77] F. Cus and J. Balic: Robot. Cim-Int. Manuf. Vol. 19 (2003), p.113

Google Scholar

[78] W.T. Chien and C.Y. Chou: J. Mater. Process. Tech. Vol. 118 (2001), p.442

Google Scholar

[79] P.V.S. Suresh, P. Venkateswara Rao and S.G. Deshmukh: Int. J. Mach. Tool Manufact. Vol. 42 (2002), p.675

Google Scholar

[80] A.J. Vallejo and R. Morales-Menendez R in: Cost-effective supervisory control system in peripheral milling using HSM, Annual Reviews in Control, doi:10.1016/j.arcontrol.2009.05.008 (2009)

DOI: 10.1016/j.arcontrol.2009.05.008

Google Scholar

[81] A.K. Nandi and D.K. Pratihar: J. Mater. Process. Tech. Vol. 155-156 (2004), p.1150

Google Scholar

[82] I.N. Tansel, B. Ozcelik, W.Y. Bao, et al.: Int. J. Mach. Tool Manufact. Vol. 46 (2006), p.26

Google Scholar

[83] W-H.Ho, J-T. Tsai, B-T. Lin, et al.: Expert Syst. Appl. Vol. 36 (2009), p.3216

Google Scholar

[84] A.M. Zain, H. Haron and S. Sharif: Expert Syst. Appl. Vol. 37 (2010), p.4650

Google Scholar

[85] I.N. Tansel, S. Gülmez, M. Demetgul, et al.: Expert Syst. Appl. Vol. 38 (2011), p.4780

Google Scholar

[86] K. Kirkpatrick, C.D. Gelett and M.P. Vecchi: Sciences Vol. 220 (1983), p.671

Google Scholar

[87] Z. Khan, B. Prasad and T. Singh: Comput. Oper. Res. Vol. 24(7) (1997), p.647

Google Scholar

[88] R. Saravanan, P. Ashokan and M. Sachithanandam: Int. J. Adv. Manuf. Tech. Vol. 17 (2001), p.471

Google Scholar

[89] M.C. Chen and D.M. Tsai: Int. J. Prod. Res. Vol. 34 (1996), p.2803

Google Scholar

[90] M.C. Chen and C.T. Su: Internacional J. Prod. Res. Vol. 36 (1998), p.2115

Google Scholar

[91] M. Hagiwara, S. Chen and I.S. Jawahir: J. Mater. Process. Tech. Vol. 209 (2009), p.332

Google Scholar

[92] F. Kolahan and M. Liang: Comput. Ind. Eng. Vol.31 (1996) p.371

Google Scholar

[93] I. Mukherjee and P.K. Ray: Appl. Soft Comput. Vol. 8: (2008), p.402

Google Scholar