Title: Optimising the parameters in AWJT process using a modified multi-objective DE algorithm

Authors: I.R. Gawai; D.I. Lalwani

Addresses: Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Ichchhanath Circle, Athawa Lines, Surat, Gujarat, 395007, India ' Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Ichchhanath Circle, Athawa Lines, Surat, Gujarat, 395007, India

Abstract: This paper presents a novel multi-objective optimisation algorithm for predicting the optimal control parameters of a radial abrasive water jet turning (AWJT) method. The objective is to maximise the material removal rate (MRR) and minimise the surface roughness (R_a) of the turned surface. The control parameters include water pressure, jet feed speed, abrasive flow rate, surface speed, and nozzle tilted angle. The proposed algorithm, called multi-objective amended differential evolution algorithm (MADEA), is a rank-based differential evolution (DE) algorithm that uses non-dominated sorting and crowding distance to select and update the solutions. The performance of MADEA is compared with six state-of-the-art multi-objective evolutionary algorithms on a set of benchmark test problems and the AWJT problem. The results show that MADEA can find better Pareto optimal solutions than the other algorithms.

Keywords: multi-objective optimisation; ADEA; AWJT; turning; efficient non-dominated sorting; ENS; evolutionary algorithms.

DOI: 10.1504/IJMMM.2025.145076

International Journal of Machining and Machinability of Materials, 2025 Vol.27 No.1, pp.19 - 39

Received: 26 Aug 2023
Accepted: 29 Dec 2023
Published online: 18 Mar 2025 *

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