Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process
The advanced manufacturing and machining techniques are adopting a population-based metaheuristic algorithm for production, predicting and decision-making. Using the same approach, this paper deals with the application of bees algorithm and differential evolution to forecast the optimal parametric v...
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Online Access: | https://doi.org/10.1177/0020294019858216 |
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doaj-cccee21505ef4e768d25fb045b033c202020-11-25T03:57:06ZengSAGE PublishingMeasurement + Control0020-29402019-09-015210.1177/0020294019858216Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining processParvesh Antil0Sarbjit Singh1Sunpreet Singh2Chander Prakash3Catalin Iulian Pruncu4College of Agricultural Engineering & Technology, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Hisar, IndiaPunjab Engineering College, Chandigarh, IndiaSchool of Mechanical Engineering, Lovely Professional University, Phagwara, IndiaSchool of Mechanical Engineering, Lovely Professional University, Phagwara, IndiaDepartment of Mechanical Engineering, Imperial College London, London, UKThe advanced manufacturing and machining techniques are adopting a population-based metaheuristic algorithm for production, predicting and decision-making. Using the same approach, this paper deals with the application of bees algorithm and differential evolution to forecast the optimal parametric values aiming to obtain maximum material removal rate during electrochemical discharge machining of silicon carbide particle/glass fiber–reinforced polymer matrix composite. The bees algorithm follows swarm-based approach, while differential evolution works on a population-based approach. The experimental design was prepared on the basis of Taguchi’s methodology using an L 16 orthogonal array. For the experimental analysis, the main variables in the process, that is, electrolyte concentration (g/L), inter-electrode gap (mm), duty factor and voltage (volts), were selected as main input parameters, and material removal rate (mg/min) was adjudged as output quality characteristic. A comparative investigation reveals that the maximum material removal rate was obtained by the parametric value proposed by differential evolution that follows the bees algorithm and Taguchi’s methodology. Furthermore, the results prove that the differential evolution algorithm has better collective assessment capability with a rapid converging rate.https://doi.org/10.1177/0020294019858216 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Parvesh Antil Sarbjit Singh Sunpreet Singh Chander Prakash Catalin Iulian Pruncu |
spellingShingle |
Parvesh Antil Sarbjit Singh Sunpreet Singh Chander Prakash Catalin Iulian Pruncu Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process Measurement + Control |
author_facet |
Parvesh Antil Sarbjit Singh Sunpreet Singh Chander Prakash Catalin Iulian Pruncu |
author_sort |
Parvesh Antil |
title |
Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process |
title_short |
Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process |
title_full |
Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process |
title_fullStr |
Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process |
title_full_unstemmed |
Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process |
title_sort |
metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process |
publisher |
SAGE Publishing |
series |
Measurement + Control |
issn |
0020-2940 |
publishDate |
2019-09-01 |
description |
The advanced manufacturing and machining techniques are adopting a population-based metaheuristic algorithm for production, predicting and decision-making. Using the same approach, this paper deals with the application of bees algorithm and differential evolution to forecast the optimal parametric values aiming to obtain maximum material removal rate during electrochemical discharge machining of silicon carbide particle/glass fiber–reinforced polymer matrix composite. The bees algorithm follows swarm-based approach, while differential evolution works on a population-based approach. The experimental design was prepared on the basis of Taguchi’s methodology using an L 16 orthogonal array. For the experimental analysis, the main variables in the process, that is, electrolyte concentration (g/L), inter-electrode gap (mm), duty factor and voltage (volts), were selected as main input parameters, and material removal rate (mg/min) was adjudged as output quality characteristic. A comparative investigation reveals that the maximum material removal rate was obtained by the parametric value proposed by differential evolution that follows the bees algorithm and Taguchi’s methodology. Furthermore, the results prove that the differential evolution algorithm has better collective assessment capability with a rapid converging rate. |
url |
https://doi.org/10.1177/0020294019858216 |
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