Metaheuristic approach in machinability evaluation of silicon carbide particle/glass fiber–reinforced polymer matrix composites during electrochemical discharge machining process
Author(s)
Antil, P
Singh, S
Singh, S
Prakash, C
Pruncu, CI
Type
Journal Article
Abstract
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 L16 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.
Date Issued
2019-09-01
Date Acceptance
2019-05-02
Citation
Measurement and Control (United Kingdom), 2019, 52 (7-8), pp.1167-1176
ISSN
0020-2940
Publisher
SAGE
Start Page
1167
End Page
1176
Journal / Book Title
Measurement and Control (United Kingdom)
Volume
52
Issue
7-8
Replaces
10044/1/71816
Copyright Statement
© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 License
(http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without
further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/
open-access-at-sage).
(http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without
further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/
open-access-at-sage).
Identifier
https://journals.sagepub.com/doi/10.1177/0020294019858216
Subjects
Science & Technology
Technology
Automation & Control Systems
Instruments & Instrumentation
Bees algorithm
differential evolution
electrochemical discharge machining
Taguchi's methodology
DIFFERENTIAL EVOLUTION
BEES ALGORITHM
PROCESS PARAMETERS
NEURAL-NETWORK
OPTIMIZATION
DESIGN
WEAR
ECDM
Industrial Engineering & Automation
Publication Status
Published
Date Publish Online
2019-06-24