Predicting of Machining Quality in Electric Discharge Machining using Intelligent Optimization Techniques

Metal matrix composites (MMCs) are the new-generation advanced materials that have excellent mechanical properties, such as high specific strength, strong hardness, and strong resistance to wear and corrosion. All these qualities make MMCs suitable material in the manufacture of automobiles and aircraft. The machining of these materials is still difficult due to the abrasive nature of the reinforced particles and hardness of MMCs. The conventional machining of MMCs results in high tool wear and slow removal of materials, thereby increasing the overall machining cost. The nonconventional machining of these materials, on the contrary, ensures much better performance. This paper reviews various research works on the development of MMCs and the subsequent hybrid composites and evaluates their performances. Further, it discusses the influence of the process parameters of conventional and nonconventional machining on the performance of MMCs. At the end, it identifies the research gaps and future scopes for further investigations in this field.

show abstract

Predicting of Machining Quality in Electric Discharge Machining using Intelligent Optimization Techniques

Abstract: This paper presents the development and application of fuzzy logic, neural network and genetic algorithm in EDM (

Cited by 3 publications

References 11 publications

Analysis of MRR, TWR and Surface Roughness in EDM Using Artificial Neural Network Technique

Analysis of MRR, TWR and Surface Roughness in EDM Using Artificial Neural Network Technique

Fuzzy analysis of surface roughness in electrical discharge machining

A review on the intensification of metal matrix composites and its nonconventional machining

Contact Info

Product

Resources

About