Parameter Optimization of Machining Processes Using a New Optimization Algorithm

REFERENCES

• Mukherjee , I. ; Ray , P.K. A review of optimization techniques in metal cutting processes . Computer and Industrial Engineering 2006 , 50 , 15 – 34 .
   Web of Science ®Google Scholar
• Rao , R.V. Advanced Modeling and Optimization of Manufacturing Processes. International Research and Development . Springer-Verlag : London , 2011 .
   Google Scholar
• Chandrasekaran , M. ; Muralidhar , M. ; Krishna , C.M. ; Dixit , U.S. Application of soft computing techniques in machining performance prediction and optimization: A literature review . International Journal of Advanced Manufacturing Technology 2010 , 46 ( 5–8 ), 445 – 464 .
   Web of Science ®Google Scholar
• Rao , R.V. ; Savsani , V.J. ; Vakharia , D.P. Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems . Computer-Aided Design 2011 , 43 , 303 – 315 .
   Web of Science ®Google Scholar
• Onwubolu , G.C. ; Clerc , M. Optimal path for automated drilling operations by a new heuristic approach using particle swarm optimization . International Journal of Production Research 2004 , 42 ( 3 ), 473 – 491 .
   Web of Science ®Google Scholar
• Nakhjavani , O.B. ; Ghoreishi , M. Multicriteria optimization of laser percussion drilling process using artificial neural network model combined with genetic algorithm . Materials and Manufacturing Processes 2006 , 21 , 11 – 18 .
   Web of Science ®Google Scholar
• Arul , S. ; Samuel , R.D. ; Vijayaraghavan , L. ; Malhotra , S.K. ; Krishnamurthy , R. Modeling and optimization of process parameters for defect toleranced drilling of GFRP composites . Materials and Manufacturing Processes 2006 , 21 ( 4 ), 357 – 365 .
   Web of Science ®Google Scholar
• Gaitonde , V.N. ; Karnik , S.R. ; Davim , J.P. Prediction and minimization of delamination in drilling of Medium-Density Fiberboard (MDF) using response surface methodology and Taguchi design. Materials and Manufacturing Processes 2008, 23 (4), 377–384.
   Web of Science ®Google Scholar
• Zhu , G.Y. ; Zhang , W.B. Drilling path optimization by the particle swarm optimization algorithm with global convergence characteristics . International Journal of Production Research 2008 , 46 , 2299 – 2311 .
   Web of Science ®Google Scholar
• Zhang , J.Z. ; Chen , J.C. Surface roughness optimization in a drilling operation using the taguchi design method . Materials and Manufacturing Processes 2009 , 24 ( 4 ), 459 – 467 .
   Web of Science ®Google Scholar
• Singh , J. ; Gill , S.S. Fuzzy modeling and simulation of ultrasonic drilling of porcelain ceramic with hollow stainless steel tools . Materials and Manufacturing Processes 2009 , 24 , 468 – 475 .
   Web of Science ®Google Scholar
• Kilickap , E. ; Huseyinoglu , M. Selection of optimum drilling parameters on burr height using response surface methodology and genetic algorithm in drilling of AISI 304 stainless steel . Materials and Manufacturing Processes 2010 , 25 ( 10 ), 1068 – 1076 .
   Web of Science ®Google Scholar
• Kilickap , E. ; Huseyinoglu , M. ; Yardimeden , A. Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm . International Journal of Advanced Manufacturing Technology 2011 , 52 , 79 – 88 .
   Web of Science ®Google Scholar
• Palanikumar , K. Modeling and analysis of delamination factor and surface roughness in drilling GFRP composites . Materials and Manufacturing Processes 2010 , 25 ( 10 ), 1059 – 1067 .
   Web of Science ®Google Scholar
• Latha , B. ; Senthilkumar , V.S. Modeling and analysis of surface roughness parameters in drilling GFRP composites using fuzzy logic . Materials and Manufacturing Processes 2010 , 25 ( 8 ), 817 – 827 .
   Web of Science ®Google Scholar
• Pawar , P.J. ; Rao , R.V. ; Davim , J.P. Multiobjective optimization of grinding process parameters using particle swarm optimization algorithm . Materials and Manufacturing Processes 2010 , 25 ( 6 ), 424 – 431 .
   Web of Science ®Google Scholar
• Gopal , A.V. ; Rao , P.V. The optimization of the grinding of silicon carbide with diamond wheels using genetic algorithms . International Journal of Advanced Manufacturing Technology 2003 , 22 ( 7–8 ), 475 – 480 .
   Web of Science ®Google Scholar
• Alagumurthi , N. ; Palaniradja , K. ; Soundararajan , V. Optimization of grinding process through design of experiment (DOE)-A comparative study . Materials and Manufacturing Processes 2006 , 21 , 19 – 21 .
   Web of Science ®Google Scholar
• Zahara , E. ; Hu , C. Solving constrained optimization problems with hybrid particle swarm optimization . Engineering Optimization 2008 , 40 ( 11 ), 1031 – 1049 .
   Web of Science ®Google Scholar
• Mani , A. ; Patvardhan , C. Solving ceramic grinding optimization problem by adaptive quantum evolutionary algorithm. IEEE International Conference on Intelligent Systems, Modelling and Simulation 2010 , DOI doi: 10.1109/ISMS.2010.19, 43–48 .
   Google Scholar
• Cus , F. ; Balic , J. Optimization of cutting process by GA approach . Robotics and Computer Integrated Manufacturing 2003 , 19 , 113 – 121 .
   Web of Science ®Google Scholar
• Chen , M.C. ; Tsai , D.M. A simulated annealing approach for optimization of multi-pass turning operations . International Journal of Production Research 1996 , 34 ( 10 ), 2803 – 2825 .
   Web of Science ®Google Scholar
• Lin , C.L. Use of the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics . Materials and Manufacturing Processes 2004 , 19 ( 2 ), 209 – 220 .
   Web of Science ®Google Scholar
• Zhang , J.Y. ; Liang , S.Y. Process optimization of finish turning of hardened steels . Materials and Manufacturing Processes 2007 , 22 , 107 – 113 .
   Web of Science ®Google Scholar
• Wang , Y.C. A note on ‘optimization of multi-pass turning operations using ant colony system’ . International Journal of Machine Tools and Manufacture 2007 , 47 ( 12–13 ), 2057 – 2059 .
   Web of Science ®Google Scholar
• Singh , D. ; Rao , P.V. Optimization of tool geometry and cutting parameters for hard turning . Materials and Manufacturing Processes 2007 , 22 , 15 – 21 .
   Web of Science ®Google Scholar
• Ramesh , S. ; Karunamoorthy , L. ; Palanikumar , K. Fuzzy modeling and analysis of machining parameters in machining titanium alloy . Materials and Manufacturing Processes 2008 , 23 ( 4 ), 439 – 447 .
   Web of Science ®Google Scholar
• Ranganathan , S. ; Senthilvelan , T. ; Sriram , G. Evaluation of machining parameters of hot turning of stainless steel (Type 316) by applying ANN and RSM . Materials and Manufacturing Processes 2010 , 25 ( 10 ), 1131 – 1141 .
   Web of Science ®Google Scholar
• Kotaiah , K.R. ; Srinivas , J. ; Babu , K.J. ; Srinivas , K. Prediction of optimal cutting states during inward turning: An experimental approach . Materials and Manufacturing Processes 2010 , 25 ( 6 ), 432 – 441 .
   Web of Science ®Google Scholar
• Deb , K. Multi-Objective Optimization Using Evolutionary Algorithms . John Wiley : Chichester , 2001 .
   Google Scholar
• Coello , C.A.C. ; Becerra , R.L. Evolutionary multiobjective optimization in materials science and engineering . Materials and Manufacturing Processes 2009 , 24 , 119 – 129 .
   Web of Science ®Google Scholar
• Coello , C.A.C. ; Lamont , G.B. ; Van Veldhuizen , D.A. Evolutionary Algorithms for Solving Multi-Objective Problems . Springer-Verlag : New York , 2007 .
   Google Scholar
• Rajak , P. ; Tewary , U. ; Das , S. ; Bhattacharya , B. ; Chakraborti , N. Phases in Zn-coated Fe analyzed through an evolutionary meta-model and multi-objective Genetic Algorithms . Computational Materials Science 2011 , 50 , 2502 – 2516 .
   Web of Science ®Google Scholar
• Mondal , D.N. ; Sarangi , K. ; Pettersson , F. ; Sen , P.K. ; Saxen , H. ; Chakraborti , N. Cu―Zn separation by supported liquid membrane analyzed through multi-objective Genetic Algorithms . Hydrometallurgy 2011 , 107 , 112 – 123 .
   Web of Science ®Google Scholar
• Biswas , A. ; Chakraborti , N. ; Sen , P.K. Multiobjective optimization of manganese recovery from sea nodules using Genetic Algorithms . Materials and Manufacturing Processes 2009 , 24 , 22 – 30 .
   Web of Science ®Google Scholar
• Biswas , A. ; Maitre , O. ; Mondal , D.N. ; Das , S.K. ; Sen , P.K. ; Collet , P. ; Chakraborti , N. Data-driven multiobjective analysis of manganese leaching from low grade sources using genetic algorithms, genetic programming, and other allied strategies . Materials and Manufacturing Processes 2011 , 26 , 415 – 430 .
   Web of Science ®Google Scholar
• Bhargava , S. ; Dulikravich , G.S. ; Murty , G.S. ; Agarwal , A. ; Colaco , M.J. Stress corrosion cracking resistant aluminum alloys: Optimizing concentrations of alloying elements and tempering . Materials and Manufacturing Processes 2011 , 26 , 363 – 374 .
   Web of Science ®Google Scholar
• Gujarathi , A.M. ; Babu , B.V. Multiobjective optimization of industrial processes using elitist multiobjective differential evolution (Elitist-MODE). Materials and Manufacturing Processes 2011, 26, 455–463.
   Web of Science ®Google Scholar
• Mitra , T. ; Helle , M. ; Petterson , F. ; Saxen , H. Multiobjective optimization of top gas recycling conditions in the blast furnace by genetic algorithms . Materials and Manufacturing Processes 2011 , 26 , 475 – 480 .
   Web of Science ®Google Scholar
• Sindhya , K. ; Miettinen , K. New perspective to continuous casting of steel with a hybrid evolutionary multiobjective algorithm . Materials and Manufacturing Processes 2011 , 26 , 481 – 492 .
   Web of Science ®Google Scholar
• Nandi , A.K. ; Datta , S. ; Deb , K. Investigating the role of nonmetallic fillers in particle-reinforced mold composites using EAs . Materials and Manufacturing Processes 2011 , 26 , 541 – 549 .
   Web of Science ®Google Scholar
• Rao , R.V. Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods . Springer-Verlag : London , 2007 .
   Google Scholar