Optimization of process parameters in magnetic field assisted powder mixed EDM of aluminium 6061 alloy
| Autor: | Arun Kumar Rouniyar, Pragya Shandilya |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Materials science Mechanical Engineering Metallurgy Alloy chemistry.chemical_element 02 engineering and technology engineering.material 021001 nanoscience & nanotechnology Magnetic field 020901 industrial engineering & automation Electrical discharge machining Fine powder chemistry Aluminium Scientific method Electric field Genetic algorithm engineering 0210 nano-technology |
| Zdroj: | Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 235:2998-3014 |
| ISSN: | 2041-2983 0954-4062 |
| DOI: | 10.1177/0954406220959108 |
| Popis: | Magnetic field assisted powder mixed electrical discharge machining (MFAPM-EDM) is a variant of EDM process where magnetic field coupled with electric field is used with addition of fine powder in dielectric to improve the surface quality, machining rate and stability of the process. Aluminium 6061 alloy as workpiece was selected due to growing use in aviation, automotive, naval industries. In this present work, parametric study and optimization was carried out on MFAPM-EDM machined Aluminium 6061 alloy. In this study, process parameters such as discharge current (IP), spark duration (PON), pause duration (POFF), concentration of powder (CP) and magnetic field (MF) were considered to analyze the effect on material erosion rate (MER) and electrode wear rate (EWR). Box Behnken design approach based on response surface methodology (RSM) was utilized for performing the experiments. Quadratic model to predict the MER and EWR were developed using response surface methodology. Discharge current has most significant effect of 50.176% and 36.36% on MER and EWR, respectively among all others process parameters. Teacher-learning-based optimization (TLBO) was employed for determining the optimal process parameters for maximum MER and minimal EWR. The results obtained with TLBO was compared with well-known optimization methods such as genetic algorithm (GA) and desirability function of RSM. Minimum EWR (0.1021 mm3/min) and maximum MER (30.4687 mm3/min) obtained using TLBO algorithm for optimized process parameters was found to better as compared to GA and desirability function. |
| Databáze: | OpenAIRE |
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