Nickel Superalloy Components Surface Integrity Control through Numerical Optimization

Article Preview

Abstract:

Different parameters are used to evaluate the machined surface quality; roughness, residual stress and white layer are the most common factors that affect the surface integrity. Residual stress, in addition, are one of the main factors that influence the component fatigue life. Superficial residual stresses depend on different factors, such as cutting parameters and tool geometry. This article describes the development of an automated optimization procedure that allows the matching of a residual stress Target Profile by varying process parameters and tool geometry for a typical aeronautic superalloy, such as Waspaloy, for which a reliable numerical model has been developed for comparison to experimental data. The objective of this procedure is to maximize the Material Removal Rate under physical constraints represented by appropriate limits assigned to: Cutting Force, Thrust Force, Tool Rake Temperature and residual stress Target Profile. The developed optimization procedure has shown its effectiveness to match a given residual stress profile in accordance to process responses numerically evaluated.

You might also be interested in these eBooks

Info:

Periodical:

Key Engineering Materials (Volumes 611-612)

Pages:

1396-1403

Citation:

Online since:

May 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Ezugwu EO, Bonney J, Yamane Y (2003), An overview of the machinability of aero-engine alloys. J Mater Process Technol 134: 233–253.

DOI: 10.1016/s0924-0136(02)01042-7

Google Scholar

[2] J. S. Senthilkumaar & P. Selvarani & R. M. Arunachalam, 2011, Intelligent optimization and selection of machining parameters in finish turning and facing of Inconel 718, Int J Adv Manuf Technol (2012) 58: 885–894.

DOI: 10.1007/s00170-011-3455-7

Google Scholar

[3] E.O. Ezugwu, J. Bonney, Y. Yamane, An overview of the machinability of aero engine alloy, Journal of Materials Processing Technology 135 (2003) 233–253.

DOI: 10.1016/s0924-0136(02)01042-7

Google Scholar

[4] Brian Griffith, Manufacturing Surface Technology-Surface Integrity and Functional Performance, Penton Press, London, (2001).

Google Scholar

[5] R.S. Pawadea, Suhas S. Joshia, P.K. Brahmankar Effect of machining parameters and cutting edge geometry on surface integrity of high-speed turned Inconel 718, International Journal of Machine Tools & Manufacture 48 (2008) 15–28.

DOI: 10.1016/j.ijmachtools.2007.08.004

Google Scholar

[6] Thiele JD, Melkote SN, Peascoe RA, Watkins TR (2000) Effect of cutting-edge geometry and workpiece hardness on surface residual stresses in finish hard turning of AISI 52100 steel. ASME J Manuf Sci Eng 122: 642–649.

DOI: 10.1115/1.1286369

Google Scholar

[7] D. Venkatesan, K. Kannan, R. Saravanan, A genetic algorithm-based artificial neural network model for the optimization of machining processes, Neural Comput & Applic (2009) 18: 135–140.

DOI: 10.1007/s00521-007-0166-y

Google Scholar

[8] K. Saravanakumar, M.R. Pratheesh Kumar, Dr.A.K. Shaik Dawood, Optimization of CNC Turning Process Parameters on INCONEL 718 Using Genetic Algorithm, Engineering Science and Technology: An International Journal (ESTIJ), ISSN: 2250-3498, Vol. 2, No. 4, August (2012).

Google Scholar

[9] G. Gary Wang, Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points, Transactions of the ASME, Journal of Mechanical Design, Vol. 125, pp.210-220, June (2003).

DOI: 10.1115/1.1561044

Google Scholar

[10] A. Del Prete, T. Primo, R. Franchi, 2013, Super-Nickel Orthogonal Turning Operations Optimization, 14th CIRP Conference on Modeling of Machining Operations (CIRP CMMO).

DOI: 10.1016/j.procir.2013.06.083

Google Scholar

[11] AdvantEdge FEM 6. 0 User's Manual, Third Wave Systems.

Google Scholar

[12] ISight User's Manual.

Google Scholar