Performance analysis and optimization of machining parameters using coated tungsten carbide cutting tool developed by novel S3P coating method

Sukhdev gangwar, Subhas Chandra Mondal, Ajay Kumar, Ranjan Kumar Ghadai*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

The motivation of research in modern manufacturing systems demands the least expensive operations to produce the best quality products. To achieve the same objective, the current study analyses and optimizes the Coated tungsten carbide cutting tool’s performance compared to the uncoated tool. For the study the coating over the cutting tool has been done using the novel Scalable Pulse Power Plasma (S3P) physical vapor deposition. For the experiments, cutting velocity (Vc), feed rate (f) and depth of cut (d) have been considered as the process or independent variable, while surface roughness and material removal rate have been taken as the response. During the study, Taguchi’s L18 orthogonal array is used for the design of experiments, and S/N ratios are used to obtain the impact of process variables on the responses; analysis of variance (ANOVA) is used to get the regression equations used as an objective function for optimization. Grasshopper’s optimization algorithm is used for the optimization. The results show that the individual optimization coated tool is suitable for generating smoother surfaces while for higher material removal rate uncoated tool favours. Multi-objective optimization suggested 0.1 mm depth of cut, 0.812 mm/rev feed rate and 70.45 mm/min cutting speed with a coated tool as the optimum parameters for the machining operation, which produces surface roughness of 4.843 μm and 5.47 cm3/min MRR.

Original languageEnglish
Pages (from-to)3909-3922
Number of pages14
JournalInternational Journal on Interactive Design and Manufacturing
Volume18
Issue number6
DOIs
Publication statusPublished - 08-2024

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Industrial and Manufacturing Engineering

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