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Particle swarm optimization technique for determining optimal machining parameters of different work piece materials in turning operation

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Abstract

Empirical models for machining time and surface roughness are described for exploring optimized machining parameters in turning operation. CNC turning machine was employed to conduct experiments on brass, aluminum, copper, and mild steel. Particle swarm optimization (PSO) has been used to find the optimal machining parameters for minimizing machining time subjected to desired surface roughness. Physical constraints for both experiment and theoretical approach are cutting speed, feed, depth of cut, and surface roughness. It is observed that the machining time and surface roughness based on PSO are nearly same as that of the values obtained based on confirmation experiments; hence, it is found that PSO is capable of selecting appropriate machining parameters for turning operation.

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Authors and Affiliations

  1. School of Mechanical Engineering, SASTRA University, Thanjavur, Tamil Nadu, Pin 613 401, India

    S. Bharathi Raja

  2. Department of Mechanical Engineering, M.A.M College of Engineering, Tiruchirappalli, Tamil Nadu, Pin 621 105, India

    N. Baskar

Authors
  1. S. Bharathi Raja
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  2. N. Baskar
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Correspondence to S. Bharathi Raja.

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Bharathi Raja, S., Baskar, N. Particle swarm optimization technique for determining optimal machining parameters of different work piece materials in turning operation. Int J Adv Manuf Technol 54, 445–463 (2011). https://doi.org/10.1007/s00170-010-2958-y

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  • DOI: https://doi.org/10.1007/s00170-010-2958-y

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