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All Journal Journal of Engineering and Technological Sciences
Tun Danish Tun Mohamed Kamarul
Resonac Pte Ltd, 2 Pioneer Cres, Singapore 628553
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering

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Influence of Machining Parameters on Surface Roughness in Trochoidal Milling of Ti-6Al-4V via Response Surface Methodology Nur Aina Farhanah Aziz; Norfauzi Tamin; Kahirol Mohd Salleh; Hairizal Osman; Tun Danish Tun Mohamed Kamarul
Journal of Engineering and Technological Sciences Vol. 58 No. 5 (2026): Vol. 58 No. 5(2026): October
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2026.58.5.3

Abstract

Machining of Ti-6Al-4V titanium alloy poses significant challenges, mainly due to its low thermal conductivity and tendency to form a built-up edge (BUE), which can lead to high surface roughness (Ra) and rapid tool wear. In this context, the trochoidal milling strategy emerges as a promising solution, as it can reduce thermal and mechanical loads by using a spiral-shaped tool path with intermittent contact between the tool and Ti-6Al-4V. Therefore, this research aims to evaluate the effectiveness and optimise the machining parameters, specifically, cutting speed (vc) and feed rate (vf), when using the trochoidal strategy for machining Ti-6Al-4V, with the primary objective of minimising Ra. The methodology used is Response Surface Methodology (RSM) with a Central Composite Design (CCD) to model the nonlinear relationships among vc, vf, and Ra. The experiment was conducted using a 3-axis CNC machining centre with carbide cutting tools. Based on the optimisation results, the optimal parameter combination to minimise Ra is 155 m/min for vc and 124 mm/min for vf. Experimental validation tests of the predicted optimal parameters yielded an Ra value of 0.118 μm, with an error of 2.47% relative to the RSM-predicted value, confirming the model’s applicability. In conclusion, this research confirms that targeted parameter optimisation using RSM is highly effective in improving the surface quality of Ti-6Al-4V, further proving the potential of the trochoidal strategy as an efficient method for critical applications in the aerospace and biomedical sectors where surface integrity is a prerequisite.
Co-Authors Hairizal Osman Kahirol Mohd Salleh Norfauzi Tamin Nur Aina Farhanah Aziz