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Computer vision based robotic polishing using artificial neural networks

Polishing is a highly skilled manufacturing process with a lot of constraints and interaction with environment. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part’s surface. In order to reduce the polishing time and cope with the shortage...

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Main Authors: Md Palil, Md Dan, Bani Hashim, Ahmad Yusairi, Adnan, R.A.B, Zamri, Ruzaidi, Abd Rahman, Khairul Anuar, Rizal, M.S., Prabuwono, Anton Satria
Format: Article
Language:English
Published: Universiti Teknikal Malaysia Melaka 2012
Subjects:
TS Manufactures
Online Access:http://eprints.utem.edu.my/id/eprint/6994/1/06%2861-76%29.pdf
http://eprints.utem.edu.my/id/eprint/6994/
https://jamt.utem.edu.my/jamt/article/view/15/12
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spelling my.utem.eprints.69942023-05-29T13:12:24Z http://eprints.utem.edu.my/id/eprint/6994/ Computer vision based robotic polishing using artificial neural networks Md Palil, Md Dan Bani Hashim, Ahmad Yusairi Adnan, R.A.B Zamri, Ruzaidi Abd Rahman, Khairul Anuar Rizal, M.S. Prabuwono, Anton Satria TS Manufactures Polishing is a highly skilled manufacturing process with a lot of constraints and interaction with environment. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part’s surface. In order to reduce the polishing time and cope with the shortage of skilled workers, robotic polishing technology has been investigated. This paper studies about vision system to measure surface defects that have been characterized to some level of surface roughness. The surface defects data have learned using artificial neural networks to give a decision in order to move the actuator of arm robot. Force and rotation time have chosen as output parameters of artificial neural networks. Results shows that although there is a considerable change in both parameter values acquired from vision data compared to real data, it is still possible to obtain surface defects characterization using vision sensor to a certain limit of accuracy. The overall results of this research would encourage further developments in this area to achieve robust computer vision based surface measurement systems for industrial robotic, especially in polishing process. Universiti Teknikal Malaysia Melaka 2012-01 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/6994/1/06%2861-76%29.pdf Md Palil, Md Dan and Bani Hashim, Ahmad Yusairi and Adnan, R.A.B and Zamri, Ruzaidi and Abd Rahman, Khairul Anuar and Rizal, M.S. and Prabuwono, Anton Satria (2012) Computer vision based robotic polishing using artificial neural networks. Journal of Advanced Manufacturing Technology, 6 (1). pp. 61-76. ISSN 1985-3157 https://jamt.utem.edu.my/jamt/article/view/15/12
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic TS Manufactures
spellingShingle TS Manufactures
Md Palil, Md Dan
Bani Hashim, Ahmad Yusairi
Adnan, R.A.B
Zamri, Ruzaidi
Abd Rahman, Khairul Anuar
Rizal, M.S.
Prabuwono, Anton Satria
Computer vision based robotic polishing using artificial neural networks
description Polishing is a highly skilled manufacturing process with a lot of constraints and interaction with environment. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part’s surface. In order to reduce the polishing time and cope with the shortage of skilled workers, robotic polishing technology has been investigated. This paper studies about vision system to measure surface defects that have been characterized to some level of surface roughness. The surface defects data have learned using artificial neural networks to give a decision in order to move the actuator of arm robot. Force and rotation time have chosen as output parameters of artificial neural networks. Results shows that although there is a considerable change in both parameter values acquired from vision data compared to real data, it is still possible to obtain surface defects characterization using vision sensor to a certain limit of accuracy. The overall results of this research would encourage further developments in this area to achieve robust computer vision based surface measurement systems for industrial robotic, especially in polishing process.
format Article
author Md Palil, Md Dan
Bani Hashim, Ahmad Yusairi
Adnan, R.A.B
Zamri, Ruzaidi
Abd Rahman, Khairul Anuar
Rizal, M.S.
Prabuwono, Anton Satria
author_facet Md Palil, Md Dan
Bani Hashim, Ahmad Yusairi
Adnan, R.A.B
Zamri, Ruzaidi
Abd Rahman, Khairul Anuar
Rizal, M.S.
Prabuwono, Anton Satria
author_sort Md Palil, Md Dan
title Computer vision based robotic polishing using artificial neural networks
title_short Computer vision based robotic polishing using artificial neural networks
title_full Computer vision based robotic polishing using artificial neural networks
title_fullStr Computer vision based robotic polishing using artificial neural networks
title_full_unstemmed Computer vision based robotic polishing using artificial neural networks
title_sort computer vision based robotic polishing using artificial neural networks
publisher Universiti Teknikal Malaysia Melaka
publishDate 2012
url http://eprints.utem.edu.my/id/eprint/6994/1/06%2861-76%29.pdf
http://eprints.utem.edu.my/id/eprint/6994/
https://jamt.utem.edu.my/jamt/article/view/15/12
_version_ 1768012340616232960
score 13.211869

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