Issue |
Manufacturing Rev.
Volume 10, 2023
|
|
---|---|---|
Article Number | 9 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/mfreview/2023007 | |
Published online | 29 May 2023 |
Research article
Analysis and optimization of mass percentage of zycoprint polymer and abrasives in achieving stability of suspension mixture in abrasive water jet machining
Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India
* e-mail: vijay.gs@manipal.edu
** e-mail: cr.kamath@manipal.edu
Received:
2
November
2022
Accepted:
26
March
2023
The suspension parameters are vital in the suspension-type abrasive water jet (AWJ) machining of several engineering materials, more so in difficult-to-cut materials, because it significantly influences the suspension stability and sedimentation behaviour of the suspension mixture and abrasive particle acceleration into the AWJs. The suspension stability and abrasive particle acceleration of the suspension-type AWJs are improved by using polymer additives. Hence, it is necessary to study the effect of suspension parameters (abrasive and polymer concentrations) on suspension stability. In this direction, the novel work reported in the paper analyses the stability of suspension by varying the mass percentage of abrasives (garnet and aluminum oxide (Al2O3)) (ωa) and mass percentage of the zycoprint polymer (ωp) in water by considering the Taguchi L9 Orthogonal array (OA). The linear regression (LR) models for the percentage of suspension volume with garnet (VsG) and the percentage of suspension volume with Al2O3 (VsA), are developed. The JAYA algorithm is used to find the optimal combination of the suspension parameters, and its results are in close agreement with the findings from the LR results. The optimum setting of the suspension parameters for both, VsG and VsA, is 3% of ωa and 0.80% of ωp.
Key words: Suspension / abrasives / water / jet / machining / garnets / aluminium / oxide / zycoprint / linear / regression / JAYA
© P. Maurya et al., Published by EDP Sciences 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.