Multi Objective Optimization in Machining Operations

  • Orlando Durán
  • Roberto Barrientos
  • Luiz Airton Consalter
Part of the Advances in Soft Computing book series (AINSC, volume 41)

Abstract

Process Planning activities are significantly based on experience and technical skill. In spite of the great efforts made for planning automation, this activity continues being made in manual form. Process Planning activities are significantly based on experience and technical skills. The advent of the CAM systems (Computer Aided Manufacturing) has partially close the gap left between the Automated Design and Manufacture. Meanwhile, a great dose of manual work still exists and investigation in this area is still necessary. This paper presents the application of a multi objective genetic algorithm for the definition of the optimal cutting parameters. The objective functions consider the production rate and production cost in turning operations. The obtained Pareto front is compared to high efficiency cutting range. This paper also describes one application of the developed mechanism using an example.

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References

  1. 1.
    Tolouei-Rad, M., Bidhendi, I.M.: On the optimization of machining parameters for milling operations. Int. J. Mach. Tools Manuf. 37(1), 1–16 (1997)CrossRefGoogle Scholar
  2. 2.
    Wang, J., et al.: Optimization of cutting conditions for single pass turning operations using a deterministic approach. International Journal of Machine Tools and Manufacture 42, 1023–1033 (2002)CrossRefGoogle Scholar
  3. 3.
    Armarego, E.J.A., Smith, A.J.R., Wang, J.: Constrained optimization strategies and CAM software for single-pass peripheral milling. Int. J. Prod. Res. 31(9), 2139–2160 (1993)CrossRefGoogle Scholar
  4. 4.
    Taylor, F.W.: On the art of cutting metals. ASME Journal of Engineering for Industry 28, 310–350 (1906)Google Scholar
  5. 5.
    Hitomi, K.: Analyses of production models, Part 1: The optimal decision of production speeds. AIIE Transactions 8(1), 96–105 (1976)MathSciNetGoogle Scholar
  6. 6.
    Taha, H.: A policy for determining the optimal cycle length for a cutting tool. Journal of Industrial Engineering 17(3), 157–162 (1966)Google Scholar
  7. 7.
    Wang, Z.G., et al.: Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing. International Journal of Machine Tools & Manufacture 45, 1726–1734 (2005)CrossRefGoogle Scholar
  8. 8.
    Quiza Sardinas, R., Rivas, M., Brindis, E.A.: Genetic algorithm-based multi-objective optimization of cutting parameters in turning processes. Engineering Applications of Artificial Intelligence 19(2), 127–133 (2006)CrossRefGoogle Scholar
  9. 9.
    Konak, D., Coit, W., Smith, A.E.: Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety 91(9), 992–1007 (2006)CrossRefGoogle Scholar
  10. 10.
    Jones, D.F., Mirrazavi, S.K., Tamiz, M.: Multi-objective metaheuristics: An overview of the current state-of-the-art. European Journal of Operational Research 137(1), 1–9 (2002)MATHCrossRefGoogle Scholar
  11. 11.
    Al-Aomar, R., Al-Okaily, A.: A GA-based parameter design for single machine turning process with high-volume production. Computers & Industrial Engineering 50, 317–337 (2006)CrossRefGoogle Scholar
  12. 12.
    Kicinger, R., Arciszewski, T., De Jong, K.: Evolutionary computation and structural design: A survey of the state-of-the-art. Computers and Structures 83, 1943–1978 (2005)CrossRefGoogle Scholar
  13. 13.
    Coello Coello, C.A., Van Veldhuizen, D.A., Lamont, G.: Evolutionary algorithms for solving multi-objective problems. Kluwer Academic, New York (2002)MATHGoogle Scholar
  14. 14.
    Deb, K., et al.: Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. In: Deb, K., et al. (eds.) Parallel Problem Solving from Nature-PPSN VI. LNCS, vol. 1917, Springer, Heidelberg (2000)Google Scholar
  15. 15.
    Consalter, L.: Arquivo de dados tecnológicos de usinagem para a determinação automática das condições automática das condições de corte em tornos com comando numérico. Msc Thesis, Universidade Federal de Santa Catarina, Florianópolis, Brasil (1985)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Orlando Durán
    • 1
  • Roberto Barrientos
    • 1
  • Luiz Airton Consalter
    • 2
  1. 1.Pontificia Universidad Católica de Valparaíso, Av.Los Carrera, 01567, QuilpuéChile
  2. 2.FEAR, Universidade de Passo Fundo, CP, Passo Fundo (RS)Brasil

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