Surface roughness, material removal rate, and their multi-objective optimization in the dry turning of Mg-4Zn/Si3N4 nanocomposites by PCD tool

N Anand; K Jayaprakash Reddy; D Bijulal; K Vijayan; P Prasanth

doi:10.14513/actatechjaur.00792

Authors

N Anand Department of Mechanical Engineering, College of Engineering Trivandrum, Engineering College P.O, Sreekaryam, Thiruvananthapuram, Kerala, 695016, India // APJ Abdul Kalam Technological University, Thiruvananthapuram, CET Campus, Thiruvananthapuram Kerala, 695016, India https://orcid.org/0009-0004-3356-9946
K Jayaprakash Reddy ISRO Inertial Systems Unit, Vattiyoorkavu PO, Thiruvananthapuram, Kerala, 695013, India https://orcid.org/0000-0001-6540-141X
D Bijulal APJ Abdul Kalam Technological University, Thiruvananthapuram, CET Campus, Thiruvananthapuram Kerala, 695016, India // Department of Mechanical Engineering, Government Engineering College Barton Hill, Kunnukuzhi, Thiruvananthapuram, Kerala, 695035, India https://orcid.org/0000-0003-2712-3097
K Vijayan ISRO Inertial Systems Unit, Vattiyoorkavu PO, Thiruvananthapuram, Kerala, 695013, India https://orcid.org/0009-0001-2037-2720
P Prasanth ISRO Inertial Systems Unit, Vattiyoorkavu PO, Thiruvananthapuram, Kerala, 695013, India https://orcid.org/0009-0004-0940-595X

DOI:

https://doi.org/10.14513/actatechjaur.00792

Keywords:

Mg-4Zn, Si3N4, Nanocomposite, Machining, Optimization

Abstract

To manufacture useful products with good surface quality from the sustainable Mg-4Zn/Si₃N₄ nanocomposites strengthened by Si₃N₄ nanoparticles, machining after stir casting is needed, and it has to be done economically. The Si₃N₄ nanoparticles could influence the machining behavior due to their abrasive properties and their ability to strengthen the alloy matrix. Multi-objective optimization of material removal rate (MRR) (a good indicator of economic production) and surface roughness (R_a) (a good indicator of quality of surface) are necessary to identify the optimal settings. This research reports the dry turning studies of vacuum stir cast Mg-4Zn/Si₃N₄ nanocomposites with a polycrystalline diamond turning tool. Response surface methodology (RSM)-based Box-Behnken design was used. The reinforcement (nanometre-sized silicon nitride) weight percentage, cutting speed, feed rate, and depth of cut were the input factors. Regression models for prediction of material removal rate (MRR) and surface roughness (R_a) were obtained and validated. Multi-objective optimization of MRR and R_a using Design-Expert software identified a reinforcement of 0.44 wt.% and a cutting speed of 110 m/min, a feed rate of 0.09 mm/rev, and a depth of cut of 0.16 mm as the optimal settings. The effects of the input process parameters on the MRR and R_a are also studied.

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