Machining Parameters Optimization of AA6061 Using Response Surface Methodology and Particle Swarm Optimization

Rashmi Lmalghan, Karthik Rao, S. ArunKumar, Shrikantha S. Rao, Mervin A. Herbert

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)


The influence of cutting parameters on the responses in face milling has been examined. Spindle speed, feed rate and depth of cut have been considered as the influential factors. In accordance with the design of experiments (DOE) a series of experiments have been carried out. The paper exemplifies on the optimizing the process parameters in milling through the application of Response surface methodology (RSM), RSM-based Particle Swarm Optimization (PSO) technique and Desirability approach. These aforesaid techniques have been applied to experimentally establish data of AA6061 aluminium material to study the effect of process parameters on the responses such as cutting force, surface roughness and power consumption. By adopting the multiple regression techniques, the interaction between the process parameters are acquired. The optimal parameters have been found by adopting the multi-response optimization techniques, i.e. desirability approach and PSO. The performance capability of PSO and desirability approach is investigated and found that the values obtained from PSO are comparable with the values of desirability approach.

Original languageEnglish
Pages (from-to)695-704
Number of pages10
JournalInternational Journal of Precision Engineering and Manufacturing
Issue number5
Publication statusPublished - 01-05-2018

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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