Future Prospects of Turning Processes Optimization Using Metaheuristics Methods

被引:0
|
作者
Abbas, Adnan Jameel [1 ]
Minhat, Mohamad [1 ]
Rahman, Md. Nizam Bin Abdul [1 ]
Akbar, Habibullah [2 ]
机构
[1] Univ Teknikal Malaysia Melaka, Fac Mfg Engn, Dept Mfg Design, Durian Tunggal, Melaka, Malaysia
[2] Univ Teknikal Malaysia Melaka, Fac Informat & Commun Technol, Dept Ind Comp, Durian Tunggal, Melaka, Malaysia
来源
2012 2ND INTERNATIONAL CONFERENCE ON UNCERTAINTY REASONING AND KNOWLEDGE ENGINEERING (URKE) | 2012年
关键词
Turning process; metaheuristics; genetic algorithm; particle swarm optimization; hybrid algorithm; GENETIC ALGORITHM; PARAMETERS;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In today's industries, optimization of turning processes is one of vital problems which aim to increase competitiveness and product quality. In fact, the decision of optimal machining parameters is arbitrary and complex. Traditionally, the selections is heavily relies on trial and error methods which is tedious and unreliable. To overcome these problems, metaheuristics methods has been proposed over the last decade. The results on several parameters such as cutting speed, depth of cut and feed rate indicate more effective and efficient way in comparison to traditional methods. This paper presents current development and future prospects due to metaheuristics techniques for optimizing the parameters of turning processes.
引用
收藏
页码:162 / 165
页数:4
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