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Mathematical modeling of surface roughness in polystyrene foam machining.

Authors :
Gote, Gopal
Kamble, Pushkar
Hodgir, Rajendra
Mittal, Yash
Karunakaran, K. P.
Source :
International Journal of Advanced Manufacturing Technology; Jun2022, Vol. 120 Issue 11/12, p7461-7475, 15p
Publication Year :
2022

Abstract

In the present era, polystyrene foam is widely used in foundries for pattern making. Industries extensively use the steam molding routes for polystyrene foam pattern making. However, the molding method cannot produce complex geometries. Industries are using the machining route for pattern making to overcome these limitations. There is limited research carried out on expanded polystyrene foam machining. Patterns need smooth surfaces with minimum surface roughness to make good quality castings. Therefore, there is a need to predict the surface roughness and its affecting parameters for polystyrene foam machining. The present article discusses a new theory for foam machining. The preliminary experiments identified two cutting mechanisms, mechanism I (through bead cutting) and mechanism II (bead removal). A novel mathematical model for the surface roughness has been developed and experimentally validated. A close correlation between the predicted and experimental values of average surface roughness (R<subscript>a</subscript>) is observed with an average error of 19.70%. The correlation analysis shows a 93.07% correlation between the predicted and experimental values. The proposed mathematical model has been segregated into two parts because of through bead cutting and bead removal. Observation shows, the model part due to bead removal contributes significantly more (approximately 90% for all experiments) to the surface roughness. Therefore, surface roughness can be improved by minimizing or avoiding bead removal. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
120
Issue :
11/12
Database :
Complementary Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
157023823
Full Text :
https://doi.org/10.1007/s00170-022-09229-6