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Multi-objective optimization of machining and micro-machining processes using non-dominated sorting teaching–learning-based optimization algorithm

Author

Listed:
  • R. Venkata Rao

    (S. V. National Institute of Technology)

  • Dhiraj P. Rai

    (S. V. National Institute of Technology)

  • J. Balic

    (University of Maribor)

Abstract

Selection of optimum machining parameters is vital to the machining processes in order to ensure the quality of the product, reduce the machining cost, increasing the productivity and conserve resources for sustainability. Hence, in this work a posteriori multi-objective optimization algorithm named as Non-dominated Sorting Teaching–Learning-Based Optimization (NSTLBO) is applied to solve the multi-objective optimization problems of three machining processes namely, turning, wire-electric-discharge machining and laser cutting process and two micro-machining processes namely, focused ion beam micro-milling and micro wire-electric-discharge machining. The NSTLBO algorithm is incorporated with non-dominated sorting approach and crowding distance computation mechanism to maintain a diverse set of solutions in order to provide a Pareto-optimal set of solutions in a single simulation run. The results of the NSTLBO algorithm are compared with the results obtained using GA, NSGA-II, PSO, iterative search method and MOTLBO and are found to be competitive. The Pareto-optimal set of solutions for each optimization problem is obtained and reported. These Pareto-optimal set of solutions will help the decision maker in volatile scenarios and are useful for real production systems.

Suggested Citation

  • R. Venkata Rao & Dhiraj P. Rai & J. Balic, 2018. "Multi-objective optimization of machining and micro-machining processes using non-dominated sorting teaching–learning-based optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1715-1737, December.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:8:d:10.1007_s10845-016-1210-5
    DOI: 10.1007/s10845-016-1210-5
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    Cited by:

    1. Elango Natarajan & Varadaraju Kaviarasan & Wei Hong Lim & Sew Sun Tiang & S. Parasuraman & Sangeetha Elango, 2020. "Non-dominated sorting modified teaching–learning-based optimization for multi-objective machining of polytetrafluoroethylene (PTFE)," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 911-935, April.
    2. Daniele Marini & Jonathan R. Corney, 2021. "Concurrent optimization of process parameters and product design variables for near net shape manufacturing processes," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 611-631, February.

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