Bulletin of Engineering Science, Technology and Industry
Vol. 4 No. 3 (2026): September

OPTIMIZATION OF FACE MILLING PARAMETERS IN GREEN MACHINING USING THE TAGUCHI METHOD

Junid Amrullah (Universitas Sriwijaya)
Muhammmad Yanis (Universitas Sriwijaya)



Article Info

Publish Date
11 Aug 2026

Abstract

Green machining has become an important manufacturing approach for reducing environmental impacts while maintaining machining performance. Minimum Quantity Lubrication (MQL) using biodegradable coconut oil offers an effective alternative to conventional flood cooling by minimizing cutting fluid consumption while ensuring adequate lubrication. This study optimizes face milling parameters of S45C medium-carbon steel under coconut oil-based MQL using the Taguchi method. Experiments were conducted on a conventional milling machine with a 10 mm four-flute carbide end mill. Cutting speed (16.33, 22.45, and 31.09 m/min), feed per tooth (0.042, 0.061, and 0.090 mm/tooth), and axial depth of cut (0.5, 0.8, and 1.2 mm) were arranged using a Taguchi L27 orthogonal array. Surface roughness (Ra) was analyzed using the Smaller-the-Better Signal-to-Noise ratio and Analysis of Variance (ANOVA). The optimum parameters were cutting speed = 31.09 m/min, feed per tooth = 0.042 mm/tooth, and axial depth of cut = 0.5 mm, yielding the highest S/N ratio despite not producing the lowest experimental Ra, indicating the most robust condition. ANOVA showed feed per tooth as the most influential factor (39.42%), followed by cutting speed (11.39%) and axial depth of cut (4.87%). These findings confirm that coconut oil-based MQL enhances surface quality and supports sustainable machining.

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Journal Info

Abbrev

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Publisher

Subject

Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering

Description

Bulletin of Engineering Science, Technology and Industry | ISSN: 3025-5821 is a peer-reviewed journal that publishes popular articles in the fields of Engineering, Technology and Industrial Science. This journal is published 4 times a year, namely in March, June, September and December. We invite ...