Tool wear rate (TWR) and material removal rate (MRR) are two most important factors for improving productivity while machining any component using CNC milling machine in CIM (computer integrated manufacturing) environment. This investigation for multi-walled CNT (MWCNT) composite with Al6061 aims at optimization of the process parameters for minimization of TWR and maximization of MRR for improving productivity. In this study, aluminum alloy 6061 was reinforced with 0.5 wt. % MWCNTs using bottom pouring stir casting under specified conditions. Effect of process parameters, viz. (i) cutting speed (2500, 3500, and 4500 rpm), (ii) feed rate (150, 200, and 250 mm/min), and (iii) depth of cut (0.2, 0.3, and 0.4 mm) was studied on TWR and MRR. Process parameters were optimized using Taguchi design of experimentation using L9 array and nonlinear regression method. For a selected CNC machine in a CIM environment, it is observed that cutting speed affects TWR and MRR significantly compared to other parameters (depth of cut and feed rate). Experiments with optimum process parameters were performed for validation of results.

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Optimization of Machining Parameters of Al6061 Nanocomposites Reinforced with MWCNTs on CNC Machines

  • Madhusudan Baghel,
  • C. M. Krishna,
  • Anurag Namdev,
  • Surendra Kumar Patel,
  • Siddharth Yadav

摘要

Tool wear rate (TWR) and material removal rate (MRR) are two most important factors for improving productivity while machining any component using CNC milling machine in CIM (computer integrated manufacturing) environment. This investigation for multi-walled CNT (MWCNT) composite with Al6061 aims at optimization of the process parameters for minimization of TWR and maximization of MRR for improving productivity. In this study, aluminum alloy 6061 was reinforced with 0.5 wt. % MWCNTs using bottom pouring stir casting under specified conditions. Effect of process parameters, viz. (i) cutting speed (2500, 3500, and 4500 rpm), (ii) feed rate (150, 200, and 250 mm/min), and (iii) depth of cut (0.2, 0.3, and 0.4 mm) was studied on TWR and MRR. Process parameters were optimized using Taguchi design of experimentation using L9 array and nonlinear regression method. For a selected CNC machine in a CIM environment, it is observed that cutting speed affects TWR and MRR significantly compared to other parameters (depth of cut and feed rate). Experiments with optimum process parameters were performed for validation of results.