Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey

Abbas, Adnan Jameel and Minhat, Mohamad and Abd Rahman, Md Nizam (2012) Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey. Scottish Journal of Arts, Social Sciences and Scientific Studies , 7 (1). ISSN ISSN 2047-1278

[img] Text (Optimization of Machining Parameters in Turning Operation Using PSO and AIS)
SJASS_Vol.7_No.1.pdf - Published Version
Restricted to Registered users only until 14 February 2020.

Download (1MB) | Request a copy


In recent manufacturing, the optimization of turning processes is one of important problems which aim to increase competitiveness and product quality. However, the choice of optimal machining parameters is difficult and complex. Traditionally, the selections is heavily relies on trial and error methods which is tedious and unreliable. Metaheuristics methods have been proposed over the last decade to overcome these problems. This paper presents a survey for optimizing the parameters of turning operation using Particle Swarm Optimization (PSO) and Artificial Immune System (AIS). This study deals with different machining performance in turning operation like surface roughness, material removal rate , tool wear , tool life, production cost, machining time and cutting temperature. Most papers in the field of turning parameters optimization are based on (PSO) algorithms, but only a few efforts that are using (AIS) algorithms. In addition, there is a gap of several machining operation parameters especially for cutting temperature optimization in turning operation using PSO and AIS.

Item Type: Article
Uncontrolled Keywords: Metaheuristics methods, Particle swarm optimization, Artificial immune system, Turning process optimization, Optimal machining parameters
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TS Manufactures
Divisions: Faculty of Manufacturing Engineering > Department of Manufacturing Process
Depositing User: Dr. Mohamad Minhat
Date Deposited: 19 Feb 2013 00:49
Last Modified: 04 Feb 2022 14:48
URI: http://eprints.utem.edu.my/id/eprint/6667
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item