Title: Optimisation of surface roughness and tool wear in high-speed milling machining of INCONEL 718 using uncoated tools

Authors: A.K.M. Nurul Amin; Sinthea Khatun; Tasfia Saba; Mashiat Iqbal; Md Jalal Uddin Rumi

Addresses: Department of Industrial and Production Engineering, Military Institute of Science and Technology, Mirpur, Dhaka, Bangladesh ' Department of Industrial and Production Engineering, Military Institute of Science and Technology, Mirpur, Dhaka, Bangladesh ' Department of Industrial and Production Engineering, Military Institute of Science and Technology, Mirpur, Dhaka, Bangladesh ' Department of Industrial and Production Engineering, Military Institute of Science and Technology, Mirpur, Dhaka, Bangladesh ' Department of Mechanical Engineering, Iowa State University, Ames, Iowa, USA; Mechanical Engineering, Iowa State University, USA

Abstract: The current study investigates the application of high-speed milling techniques on INCONEL 718 using uncoated tools. The study employed nano-MQL (NMQL), incorporating a combination of palm oil and Al₂O₃ at different concentrations. The effects of various control parameters, including cutting speed, feed rate, and nano-powder concentration, on surface roughness and tool wear were examined. The investigation focused on evaluating different combinations of process parameters using the design of experiments (DoE) with a central composite design (CCD) tool. The goal was to identify the most effective parameter combinations for optimal results. Mathematical models for surface roughness (Ra, Rt), tool nose wear, and flank wear were developed using ANOVA. Genetic algorithm (GA) was employed to implement an alternative optimisation approach based on the results of response surface methodology (RSM) analysis. The graphs generated through DoE were used to analyse the individual impact of parameters on responses. Surface characteristics were assessed using scanning electron microscopy (SEM).

Keywords: surface roughness; tool nose wear; tool flank wear; response surface methodology; RSM; central composite design; CCD; genetic algorithm; GA; scanning electron microscopy; SEM; carbide tools; nano-MQL; Al₂O₃ nano-powder.

DOI: 10.1504/IJMMM.2025.150056

International Journal of Machining and Machinability of Materials, 2025 Vol.27 No.4, pp.392 - 430

Received: 10 Jun 2024
Accepted: 01 Sep 2024
Published online: 28 Nov 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article