Application of MCDM Method for the Selection of Optimum Process Parameters in Turning Process

被引：14

作者：

Singaravel, B. ^{[1
]}

Shankar, D. Prabhu ^{[1
]}

Prasanna, Lakshmi ^{[1
]}

机构：

[1] Vignan Inst Tehnol & Sci, Mech Engn Dept, Hyderabad 508284, Telangana, India

来源：

MATERIALS TODAY-PROCEEDINGS | 2018年 / 5卷 / 05期

关键词：

Turning; AISI; 4340; steel; process parameters and ARAS; MACHINING PARAMETERS; CUTTING CONDITIONS; SURFACE INTEGRITY; INCONEL; 718; OPTIMIZATION;

D O I：

10.1016/j.matpr.2018.02.341

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Turning process is one of the fundamental machining operations and its parameters optimization leads to better machining performance. This study applies Additive Ratio Assessment (ARAS) method to determine the optimum process parameters and suitable coated tool in turning operation of AISI 4340 steel. The process parameters considered are cutting speed, feed rate, depth of cut and coated tools. The objective is to minimize surface roughness, micro hardness and maximize Material Removal Rate (MRR) simultaneously. The result revealed that this proposed method is appropriate for solving multi criteria optimization of process parameters. (C) 2017 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).

引用

页码：13464 / 13471

页数：8

共 50 条

[31] Influence of Cutting Parameters on Surface Roughness for Wet and Dry Turning Process
Yusuf, Muhammad
Anuar, Khairol
Ismail, Napsiah
Sulaiman, Shamsuddin
COMPOSITE SCIENCE AND TECHNOLOGY, PTS 1 AND 2, 2011, 471-472 : 233 - 238
[32] Application of Taguchi and Response Surface Methodology (RSM) in Steel Turning Process to Improve Surface Roughness and Material Removal Rate
Prasath, Manikanda K.
Pradheep, T.
Suresh, S.
MATERIALS TODAY-PROCEEDINGS, 2018, 5 (11) : 24622 - 24631
[33] A knowledge-driven method of adaptively optimizing process parameters for energy efficient turning
Xiao, Qinge
Li, Congbo
Tang, Ying
Li, Lingling
Li, Li
ENERGY, 2019, 166 : 142 - 156
[34] Machinability study on stainless steel and optimum setting of cutting parameters in turning process using Taguchi design of experiments
Marimuthu, P. (pmarimuthu69@gmail.com), 1600, Inderscience Publishers (43): : 122 - 133
[35] Development and experimental investigation of duplex turning process
Yadav, Ravindra Nath
ADVANCES IN MANUFACTURING, 2017, 5 (02) : 149 - 157
[36] Evaluating Process Parameters of Multi-Pass Turning Process Using Hybrid Genetic Simulated Swarm Algorithm
Gayatri, R.
Baskar, N.
JOURNAL OF ADVANCED MANUFACTURING SYSTEMS, 2015, 14 (04) : 215 - 233
[37] Performance evaluation of process parameters using MCDM methods for Titanium Alloy (Ti6al4v) in turning operation
Ingle, Sushil, V
Raut, Dadarao N.
AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING, 2024, 22 (05) : 958 - 972
[38] Optimal Selection Of Machining Parameters In CNC Turning Process Of EN-31 Using Intelligent Hybrid Decision Making Tools
Gowd, G. Harinath
Goud, M. Venugopal
Theja, K. Divya
Reddy, M. Gunasekhar
12TH GLOBAL CONGRESS ON MANUFACTURING AND MANAGEMENT (GCMM - 2014), 2014, 97 : 125 - 133
[39] Optimization of process parameters during turning of Inconel 625
Waghmode, Shankar P.
Dabade, Uday A.
MATERIALS TODAY-PROCEEDINGS, 2019, 19 : 823 - 826
[40] The application of high-speed camera for analysis of chip creation process during the steel turning
Struzikiewicz, Grzegorz
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS 2016, 2016, 10031

← 1 2 3 4 5 →