Application of newly developed algorithms for improving surface finish in face milling of Ti-6Al-4V

Neelesh Kumar Sahu, Ankur Jaiswal, Mohammad Ali

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


The proposed work describes about application of evolutionary algorithms such as Genetic algorithm (GA), Teaching learning based optimization (TLBO) and newly developed algorithms JAYA algorithms for minimization of irregularities of machined surface. Objective function for machining response is developed using response surface methodology (RSM) after performing systematic face milling operation based on design of experiment. Response model is examined for better prediction using additional milling trials other than the ones used in main design of experiments (DoE). Later on, minimization of irregularity of machined surface was done with response surface based desirability approach. Correlation coefficient (R2) of 98% shows goodness of the model which means 98% of data is explained by the developed model. Results shows that newly developed algorithms TLBO and JAYA are outperforming RSM and GA in terms of minimizing irregularities of machined surface.

Original languageEnglish
Pages (from-to)636-641
Number of pages6
JournalMaterials Today: Proceedings
Publication statusPublished - 2019
Event2nd International Conference on Recent Advances in Materials and Manufacturing Technologies, IMMT 2019 - Dubai, United Arab Emirates
Duration: 20-11-201922-11-2019

All Science Journal Classification (ASJC) codes

  • Materials Science(all)


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