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ARPN Journal of Engineering and Applied Sciences

Optimization of machining parameters in hard turning of AISI 4340 using Hybrid Taguchi and Grey Relational Analysis technique

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Author Armansyah Ginting, Muhammad Arifin and Sudar Sono Sarjana
e-ISSN 1819-6608
On Pages 1418-1423
Volume No. 20
Issue No. 17
Issue Date December 15, 2025
DOI https://doi.org/10.59018/0925161
Keywords machining optimization, minimum quantity lubrication, flank wear, surface roughness.


Abstract

The optimization of machining parameters in hard turning of AISI 4340 steel is crucial for enhancing manufacturing efficiency and product quality. This study integrates the Taguchi method and Grey Relational Analysis (GRA) to identify optimal machining conditions under Minimum Quantity Lubrication (MQL) and dry cutting environments. A CNC lathe was utilized to perform experiments, varying cutting speed, feed rate, depth of cut, and cutting conditions. Flank wear (VB) and surface roughness (Ra) were measured as response variables. The optimal parameters determined were a cutting speed of 90 m/min, a feed rate of 0.10 mm/rev, a depth of cut of 0.25 mm, and an MQL condition. Confirmation tests validated the results, showing a significant reduction in VB and a slight improvement in Ra. This hybrid approach demonstrates the effectiveness of combining Taguchi and GRA methods for machining parameter optimization, providing a robust framework for improving tool life and surface finish in hard turning applications.

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