Heat Treatment Process Optimization Using Hunting Search and Ant Sense on Path of Steepest Ascent

Abstract:

The purpose of this study is to determine the optimal design parameters of the heat treatment process (HTP) in the context of the multi-response surface optimization. An aim is to improve quality characteristics in the HTP by simultaneously optimizing hardness, stain yield and roundness via pre-heat and heat chamber heaters, number of vacuum, gas fan speed in quenching chamber and partial gas pressure. Taguchi orthogonal design and desirability function approach are applied to form the path of steepest ascent. Influential parameters from the hunting search and ant colony optimization metaheuristics are integrated to seek the optimum. The results proved that the hybrid approach based on the hunting search optimization mechanism was successfully applied in the study. The confirmation tests based on the predicted optimal results were verified and carried out to show considerable improvement.

• Periodical: Applied Mechanics and Materials (Volumes 217-219)
• Pages: 1475-1478
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.217-219.1475
• Online since: November 2012
• Authors: Korakoch Waiyakan, Pongchanun Luangpaiboon
• Keywords: Ant Colony Optimization (ACO), Desirability Function Approach, Heat Treatment Process, Hunting Search Method, Multi-Response Surfaces, Steepest Ascent Method

References

[1] P.W. Tsai, J.S. Pan, S.M. Chen, B.Y. Liao, Enhanced parallel cat swarm optimization based on the Taguchi method, Expert Systems with Applications 39 (2012), 6309-6319.

DOI: 10.1016/j.eswa.2011.11.117

[2] A.K. Pandey, A.K. Dubey, Taguchi based fuzzy logic optimization of multiple quality characteristics in laser cutting of Duralumin sheet, Optics and Lasers in Engineering 50 (2012), 328-335.

DOI: 10.1016/j.optlaseng.2011.11.005

[3] A. Soveja, E. Cicala, D. Grevey, J.M. Jouvard, Optimization of TA6V alloy surface laser texturing using an experimental design approach, Optics and Lasers in Engineering 46 (2008), 671-678.

DOI: 10.1016/j.optlaseng.2008.04.009

[4] Z.C. Chen, Q. Fu, A practical approach to generating steepest ascent tool-paths for three-axis finish milling of compound NURBS surfaces, Computer-aided Design 39 (2007), 964-974.

DOI: 10.1016/j.cad.2007.06.010

[5] M. Dorigo, C. Blum, Ant colony optimization theory: a survey, Theoretical Computer Science 344 (2005), 243-278.

DOI: 10.1016/j.tcs.2005.05.020

[6] R.Oftadeh, M.J. Mahjoob, M. Shariatpanahi, A novel meta-heuristic optimization algorithm inspired by group hunting of animals: hunting search, Computers and Mathematics with Applications 60 (2010), 2087-2098.

DOI: 10.1016/j.camwa.2010.07.049

[7] P. Luangpaiboon, Variable neighborhood simplex search methods for global optimization models, Journal of Computer Science 8 (2012), 613-620.

DOI: 10.3844/jcssp.2012.613.620