Optimization of material removal rate of Ti-6Al-4V using Rao-1 algorithm

被引：3

作者：

Agarwal, Neeraj ^{[1
]}

Irshad, Md ^{[1
]}

Singh, Mahendra Raj ^{[2
]}

Singh, Gurjeet ^{[1
]}

机构：

[1] IES Coll Technol, Dept Mech Engn, Bhopal 462044, MP, India

[2] Shri Ram Inst Technol, Dept Mech Engn, Jabalpur 482002, MP, India

来源：

MATERIALS TODAY-PROCEEDINGS | 2022年 / 62卷 / P12期

关键词：

Electrical discharge machining; MRR; Advanced optimization; Rao-1; algorithm; RSM; DISCHARGE MACHINING CHARACTERISTICS; PROCESS PARAMETERS; SURFACE-ROUGHNESS; EDM PARAMETERS; SPEED; MODEL;

D O I：

10.1016/j.matpr.2022.04.760

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Titanium alloy Ti6Al4V has attractive properties for engineering applications. Electric discharge machining is nowadays widely adapted for titanium alloy machining to produce proper geometric profiles and surface integrity. EDM has a high machining cost and has a lower material removal rate (MRR). It is always desirable to improve the machining efficiency. This research involves, enhancing the MRR of Titanium alloy during EDM. The influence of four EDM input parameters on MRR is investigated in this research. Current, pulse on time, voltage and duty factor is selected as EDM control parameters. Response surface methodology (RSM) is utilized to create a design of experiment (DOE) plan. Thirty experiments were conducted as per the DOE. The experimental results are used to develop a predictable quadratic regression model for MRR using RSM. This MRR regression model is optimized using an advanced optimization technique, the Rao-1 algorithm. This is a new algorithm and easier to implement. The study reveals current and voltage are identified as the most influential factors in the MRR. Copyright (C) 2022 Elsevier Ltd. All rights reserved.

引用

页码：6722 / 6726

页数：5

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