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Volume 47, No 2, 2025, Pages 228-249


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Multi-Objective Optimization in Hard Turning of AISI 4140 Steel Using Taguchi-Based GRA and DEAR with Ceramic Tool

Authors:

Mohand Ouidir Sahbi , Sadeddine Abdelhamid , Mohamed Athmane Yallese , Salim Belhadi ,
Abdelatif Belmarie

DOI: 10.24874/ti.1842.12.24.03

Received: 26 December 2024
Revised: 3 February 2025
Accepted: 24 March 2025
Published: 15 June 2025

Abstract:

In machining, achieving a low surface roughness (Ra), minimal tool wear (VB), and a high material removal rate (MRR) is essential for successful hard turning. This study investigates the optimal cutting conditions for hard turning of AISI 4140 steel using a Taguchi L9 experimental design. Four factors were varied: cutting speed (Vc), feed rate (f), depth of cut (Doc), and cutting tool material (mixed ceramic CC650, TiN-coated mixed ceramic CC6050, and composite ceramic CC670). The experimental results were carefully measured after each test, and ANOVA was performed to analyze the influence of input parameters on the output variables. A multi-objective optimization was applied using Grey Relational Analysis (GRA) and Data Envelopment Analysis Ranking (DEAR) based on Taguchi analysis to simultaneously minimize Ra and VB while maximizing MRR. The results revealed that the optimal regimes produce Ra and VB values below their minimum levels. The DEAR method achieves a higher MRR compared to GRA. The CC6050 insert demonstrated superior performance in terms of Ra and VB. The optimal conditions identified by GRA and DEAR maintained f = 0.08 mm/rev, Doc = 0.3 mm, and the CC6050 insert, with a variation in cutting speed (Vc). ANOVA results for surface roughness (Ra) revealed that the feed rate (f) had the most significant influence, contributing 82.35% to Ra. Vc had the most significant influence on VB, contributing 37.03%. Among the tested inserts, CC6050 exhibited the lowest wear (VB = 0.09 mm), followed by CC670 (VB = 0.18 mm).

Keywords:

Hard machining, AISI 4140, Ceramics, Tool-wear, Surface roughness, MCDM Optimization



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