Multi-Objective Optimization in Electric Discharge Machining of Aluminium Composite

Tribology in Industry

N. Radhika¹  P. Shivaram¹  K.T. Vijay Karthik¹ 

[1] Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India;

关键词: Aluminium Composites;    Machining;    Genetic Algorithm;    Multi-objective optimization;    Artificial Neural Networks;   

DOI  :  

来源: DOAJ

【 摘 要 】

This paper involves the optimization of input process parameters in Electric Discharge Machining of Aluminium hybrid Metal Matrix Composite. Aluminium AlSi10Mg alloy reinforced with 9 %wt. alumina and 3 %wt. graphite particles fabricated through liquid metallurgy route was used for machining. Experiments were conducted in an Electric Discharge Machine and the influence of input process parameters such as Peak current, Pulse-on time and Flushing pressure during machining of aluminium composite was studied. The objective was to obtain a minimum surface roughness with minimum tool wear rate and maximum material removal rate. Multi-objective optimization of the input process parameters was performed by employing Artificial Neural Network and Genetic Algorithm hybrid optimization technique. The results obtained provide a pareto-optimal solution set that offers a set of non-dominated solutions that can be used in a practical situation by a decision maker.

【 授权许可】

Unknown