Application of Particle Swarm Optimization for Achieving Desired Surface Roughness in Tungsten-Copper Alloy Machining

Author:

Gaitonde V. N.1,Karnik S. R.1,Davim J. Paulo2

Affiliation:

1. B. V. B. College of Engineering and Technology, Hubli, Karnataka, India

2. University of Aveiro, Campus Santiago, Aveiro, Portugal

Abstract

The tungsten-copper electrodes are used in the manufacture of die steel and tungsten carbide workpieces due to high thermal and electrical conductivity of copper, spark erosion resistance, low thermal expansion coefficient, better arc-resistance, non-welding, and high melting temperature of tungsten. Since a tungsten-copper electrode is more expensive than traditional electrodes; there is a need to study the machinability aspects, especially the surface roughness of turned components, which has a greater influence on product quality. This chapter deals with the application of response surface methodology (RSM) for the development surface roughness model for turning of tungsten-copper alloy. The experiments were planned as per full factorial design (FFD) with cutting speed, feed rate, and depth of cut as the process parameters. The proposed surface roughness model was employed with particle swarm optimization (PSO) to optimize the parameters. PSO program gives the minimum values of surface roughness and the corresponding optimal machining parameters.

Publisher

IGI Global

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An analysis to enhance the machining performance of micro-EDM for drilling of blind micro-hole using ANN;The International Journal of Advanced Manufacturing Technology;2023-10-17

2. Multiresponse optimization in wire electric discharge machining (WEDM) of HCHCr steel by integrating response surface methodology (RSM) with differential evolution (DE);Computational Methods and Production Engineering;2017

3. A review of empirical modeling techniques to optimize machining parameters for hard turning applications;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2014-12-05

4. Multi-Objective Optimization of Abrasive Waterjet Machining Process Parameters Using Particle Swarm Technique;International Journal of Materials Forming and Machining Processes;2014-07

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