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Title: Predictive modelling of surface roughness for double vibropolishing in trough system
Authors: Alcaraz, Joselito Yam Tomacder
Mankar, A.V.
Ahluwalia, Kunal
Mediratta, Rijul
Majumdar, Kausik Kumar
Yeo, Swee Hock
Keywords: Numerical Modelling
Vibratory Finishing
DRNTU::Engineering::Mechanical engineering
Issue Date: 2018
Source: Alcaraz, J. Y. T., Mankar, A. V., Ahluwalia, K., Mediratta, R., Majumdar, K. M., & Yeo, S. H. (2018). Predictive Modelling of Surface Roughness for Double Vibropolishing in Trough System. Procedia CIRP, 77, 489-492. doi:10.1016/j.procir.2018.08.258
Series/Report no.: Procedia CIRP
Abstract: Vibratory finishing is a ubiquitous surface finishing process administered to components of various functionalities. Alongside the development of more complex finishing techniques such as drag finishing and abrasive flow machining, significant progress on numerical simulation has also been achieved, e.g. computational fluid dynamics, discrete element method. Yet, search into predictive roughness modelling has been insipid. In this study, multi-variable regression and artificial neural network modelling was done using experimental data obtained from subjecting rectangular test coupons to double vibropolishing in a vibratory trough. Two regression models, i.e. exponential and power, and several Multi-Layer Perceptron (MLP) architectures were trained using experimental data, and were subsequently evaluated for generalization ability. Model selection was done by comparing the mean-absolute percentage error and r-squared values from both training and testing datasets.
ISSN: 2212-8271
DOI: 10.1016/j.procir.2018.08.258
Rights: © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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