Predictive modelling of surface roughness for double vibropolishing in trough system
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,...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Language: | English |
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2018
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| Online Access: | https://hdl.handle.net/10356/89945 http://hdl.handle.net/10220/47158 |
| _version_ | 1811686601538928640 |
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| author | Alcaraz, Joselito Yam Tomacder Mankar, A.V. Ahluwalia, Kunal Mediratta, Rijul Majumdar, Kausik Kumar Yeo, Swee Hock |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Alcaraz, Joselito Yam Tomacder Mankar, A.V. Ahluwalia, Kunal Mediratta, Rijul Majumdar, Kausik Kumar Yeo, Swee Hock |
| author_sort | Alcaraz, Joselito Yam Tomacder |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T05:03:01Z |
| format | Journal Article |
| id | ntu-10356/89945 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:03:01Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/899452023-03-04T17:17:10Z Predictive modelling of surface roughness for double vibropolishing in trough system Alcaraz, Joselito Yam Tomacder Mankar, A.V. Ahluwalia, Kunal Mediratta, Rijul Majumdar, Kausik Kumar Yeo, Swee Hock School of Mechanical and Aerospace Engineering Rolls-Royce@NTU Corporate Lab Numerical Modelling Vibratory Finishing DRNTU::Engineering::Mechanical engineering 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. NRF (Natl Research Foundation, S’pore) Published version 2018-12-21T03:55:21Z 2019-12-06T17:37:10Z 2018-12-21T03:55:21Z 2019-12-06T17:37:10Z 2018 Journal Article 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 2212-8271 https://hdl.handle.net/10356/89945 http://hdl.handle.net/10220/47158 10.1016/j.procir.2018.08.258 en Procedia CIRP © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/). 4 p. application/pdf |
| spellingShingle | Numerical Modelling Vibratory Finishing DRNTU::Engineering::Mechanical engineering Alcaraz, Joselito Yam Tomacder Mankar, A.V. Ahluwalia, Kunal Mediratta, Rijul Majumdar, Kausik Kumar Yeo, Swee Hock Predictive modelling of surface roughness for double vibropolishing in trough system |
| title | Predictive modelling of surface roughness for double vibropolishing in trough system |
| title_full | Predictive modelling of surface roughness for double vibropolishing in trough system |
| title_fullStr | Predictive modelling of surface roughness for double vibropolishing in trough system |
| title_full_unstemmed | Predictive modelling of surface roughness for double vibropolishing in trough system |
| title_short | Predictive modelling of surface roughness for double vibropolishing in trough system |
| title_sort | predictive modelling of surface roughness for double vibropolishing in trough system |
| topic | Numerical Modelling Vibratory Finishing DRNTU::Engineering::Mechanical engineering |
| url | https://hdl.handle.net/10356/89945 http://hdl.handle.net/10220/47158 |
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