Abstract
In this study, silicon carbide mixed electrical discharge machining (SCMEDM) process has been developed and later on modelled also using an artificial neural network (ANN) based technique as well as response surface methodology (RSM). Experiments were conducted with Al LM-25/SiC metal matrix composites as per Box Behnken design (BBD). Discharge current, pulse-on-time, servo-voltage, powder concentration, tool material and varying reinforcement levels were considered as machining input parameters. Material removal rate, tool wear rate and surface roughness were taken to be the response parameters. Analysis of variance (ANOVA) method was used to investigate the significant effect of parameters on the response measures. The experimental data was trained using a back-propagation ANN technique. Research shows that the influence of current, pulse length and tool material on the machining characteristics of Al LM-25 MMCs is significant. Surrogated models were also developed for proposed process using RSM. However, the accuracy of ANN models was found to be better than that of RSM models.
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Data Availability
The data and material are available within the manuscript.
Code Availability
Not applicable.
The authors declare that all procedures followed were in accordance with the ethical standards.
Abbreviations
- ANN:
-
Artificial neural network
- RBFNN:
-
Radial Basics Function Neural Network
- NSGA:
-
Non sorting genetic algorithm
- SCMEDM:
-
Silicon carbide mixed electro discharge machining
- WEDM:
-
Wire electro discharge machining
- FEM:
-
Finite element method
- DEM:
-
Dimensional exponential model
- TWR:
-
Tool wear rate
- SF:
-
Surface finish
- CR:
-
Crater radius
- ρ w :
-
Density of work piece material
- Kw :
-
Work piece thermal conductivity
- Vg:
-
Voltage GapTON Pulse-on-time
- TOFF :
-
Pulse-off-time
- Ra:
-
Surface Roughness
- R2 :
-
Coefficient of determination
- BPNN:
-
Back propagation neural network
- ANOVA:
-
Analysis of variance
- PCA:
-
Principal Component Analysis
- MMC:
-
Metal matrix composites
- SEM:
-
Scanning electron microscopy
- MRR:
-
Metal removal rate
- SR:
-
Surface roughness
- OC:
-
Over cut
- SEM:
-
Scanning electron microscope
- IP :
-
Input Current
- αw :
-
Thermal expansion coefficient
- Cp:
-
Concentration of powder
- WT:
-
White layer thickness
- PMEDM:
-
Powder mixed electro discharge machining
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Samples preparation, data collection and analysis were performed by the authors SST and SKP. The first draft of the manuscript was written by SST. SS and KKS contributed during editing and revision work of the paper. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Thakur, S.S., Pradhan, S.K., Sehgal, S. et al. Experimental investigations on silicon carbide mixed electric discharge machining. Silicon 15, 583–601 (2023). https://doi.org/10.1007/s12633-022-02022-w
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DOI: https://doi.org/10.1007/s12633-022-02022-w