Computer vision approach for robotic polishing application using artificial neural networks

Adnan Rachmat Anom Besari, Anton Satria Prabuwono, Ruzaidi Zamri, Md Dan Md Palil

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    Polishing is a highly skilled manufacturing process with a lot of constraint and interaction with environment. Unfortunately, manual polishing process takes time consuming of the total manufacturing time and takes a significant cost. On top of that, undesired working condition exists due to dust and noise and next it is quite difficult to find skilled technicians. Therefore, it is necessary to develop an automation system on the polishing process. One of the automation systems that are often developed by the industry is the use of robots. The goal is to handle the repetitive work that humans are not able to do so. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part's surface. This research combines computer vision and robotics systems to overcome the problems arising in the polishing process. Vision system is used to measure surface defect that divide into several categories. The surface data is learned using artificial neural networks then give the decisions to move the actuator on robot. Parameters that developed in this system are force and time polishing which has a significant effect on the polishing process. Therefore, this system studies the characteristics of surface defects before the given action with different value of force and polishing time, and then compared with surface defects after given the action. Results obtained show that it is possible to obtain surface parameters using vision-based methods with a certain limit of accuracy. However, there are some advantages using this system, including faster polishing time, simpler quality inspection, and more evenly surface roughness result compared with manual polishing. The overall results of this research would encourage further developments to achieve robust computer vision technique for robotic polishing application.

    Original languageEnglish
    Title of host publicationProceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010
    Pages281-286
    Number of pages6
    DOIs
    Publication statusPublished - 2010
    Event2010 8th IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010 - Kuala Lumpur
    Duration: 13 Dec 201014 Dec 2010

    Other

    Other2010 8th IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010
    CityKuala Lumpur
    Period13/12/1014/12/10

    Fingerprint

    Polishing
    neural network
    Computer vision
    Robotics
    Neural networks
    Surface defects
    robot
    automation
    manufacturing
    technician
    working conditions
    Automation
    Surface roughness
    Robots
    time
    industry
    Dust
    costs
    interaction
    Actuators

    Keywords

    • Computer vision
    • Polishing robot
    • Surface defect characerizations
    • Surface roughness and artificial neural networks

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Education

    Cite this

    Besari, A. R. A., Prabuwono, A. S., Zamri, R., & Palil, M. D. M. (2010). Computer vision approach for robotic polishing application using artificial neural networks. In Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010 (pp. 281-286). [5704017] https://doi.org/10.1109/SCORED.2010.5704017

    Computer vision approach for robotic polishing application using artificial neural networks. / Besari, Adnan Rachmat Anom; Prabuwono, Anton Satria; Zamri, Ruzaidi; Palil, Md Dan Md.

    Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010. 2010. p. 281-286 5704017.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Besari, ARA, Prabuwono, AS, Zamri, R & Palil, MDM 2010, Computer vision approach for robotic polishing application using artificial neural networks. in Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010., 5704017, pp. 281-286, 2010 8th IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010, Kuala Lumpur, 13/12/10. https://doi.org/10.1109/SCORED.2010.5704017
    Besari ARA, Prabuwono AS, Zamri R, Palil MDM. Computer vision approach for robotic polishing application using artificial neural networks. In Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010. 2010. p. 281-286. 5704017 https://doi.org/10.1109/SCORED.2010.5704017
    Besari, Adnan Rachmat Anom ; Prabuwono, Anton Satria ; Zamri, Ruzaidi ; Palil, Md Dan Md. / Computer vision approach for robotic polishing application using artificial neural networks. Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010. 2010. pp. 281-286
    @inproceedings{fab1328d60ab4042a5651a8919baf3c5,
    title = "Computer vision approach for robotic polishing application using artificial neural networks",
    abstract = "Polishing is a highly skilled manufacturing process with a lot of constraint and interaction with environment. Unfortunately, manual polishing process takes time consuming of the total manufacturing time and takes a significant cost. On top of that, undesired working condition exists due to dust and noise and next it is quite difficult to find skilled technicians. Therefore, it is necessary to develop an automation system on the polishing process. One of the automation systems that are often developed by the industry is the use of robots. The goal is to handle the repetitive work that humans are not able to do so. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part's surface. This research combines computer vision and robotics systems to overcome the problems arising in the polishing process. Vision system is used to measure surface defect that divide into several categories. The surface data is learned using artificial neural networks then give the decisions to move the actuator on robot. Parameters that developed in this system are force and time polishing which has a significant effect on the polishing process. Therefore, this system studies the characteristics of surface defects before the given action with different value of force and polishing time, and then compared with surface defects after given the action. Results obtained show that it is possible to obtain surface parameters using vision-based methods with a certain limit of accuracy. However, there are some advantages using this system, including faster polishing time, simpler quality inspection, and more evenly surface roughness result compared with manual polishing. The overall results of this research would encourage further developments to achieve robust computer vision technique for robotic polishing application.",
    keywords = "Computer vision, Polishing robot, Surface defect characerizations, Surface roughness and artificial neural networks",
    author = "Besari, {Adnan Rachmat Anom} and Prabuwono, {Anton Satria} and Ruzaidi Zamri and Palil, {Md Dan Md}",
    year = "2010",
    doi = "10.1109/SCORED.2010.5704017",
    language = "English",
    isbn = "9781424486489",
    pages = "281--286",
    booktitle = "Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010",

    }

    TY - GEN

    T1 - Computer vision approach for robotic polishing application using artificial neural networks

    AU - Besari, Adnan Rachmat Anom

    AU - Prabuwono, Anton Satria

    AU - Zamri, Ruzaidi

    AU - Palil, Md Dan Md

    PY - 2010

    Y1 - 2010

    N2 - Polishing is a highly skilled manufacturing process with a lot of constraint and interaction with environment. Unfortunately, manual polishing process takes time consuming of the total manufacturing time and takes a significant cost. On top of that, undesired working condition exists due to dust and noise and next it is quite difficult to find skilled technicians. Therefore, it is necessary to develop an automation system on the polishing process. One of the automation systems that are often developed by the industry is the use of robots. The goal is to handle the repetitive work that humans are not able to do so. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part's surface. This research combines computer vision and robotics systems to overcome the problems arising in the polishing process. Vision system is used to measure surface defect that divide into several categories. The surface data is learned using artificial neural networks then give the decisions to move the actuator on robot. Parameters that developed in this system are force and time polishing which has a significant effect on the polishing process. Therefore, this system studies the characteristics of surface defects before the given action with different value of force and polishing time, and then compared with surface defects after given the action. Results obtained show that it is possible to obtain surface parameters using vision-based methods with a certain limit of accuracy. However, there are some advantages using this system, including faster polishing time, simpler quality inspection, and more evenly surface roughness result compared with manual polishing. The overall results of this research would encourage further developments to achieve robust computer vision technique for robotic polishing application.

    AB - Polishing is a highly skilled manufacturing process with a lot of constraint and interaction with environment. Unfortunately, manual polishing process takes time consuming of the total manufacturing time and takes a significant cost. On top of that, undesired working condition exists due to dust and noise and next it is quite difficult to find skilled technicians. Therefore, it is necessary to develop an automation system on the polishing process. One of the automation systems that are often developed by the industry is the use of robots. The goal is to handle the repetitive work that humans are not able to do so. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout part's surface. This research combines computer vision and robotics systems to overcome the problems arising in the polishing process. Vision system is used to measure surface defect that divide into several categories. The surface data is learned using artificial neural networks then give the decisions to move the actuator on robot. Parameters that developed in this system are force and time polishing which has a significant effect on the polishing process. Therefore, this system studies the characteristics of surface defects before the given action with different value of force and polishing time, and then compared with surface defects after given the action. Results obtained show that it is possible to obtain surface parameters using vision-based methods with a certain limit of accuracy. However, there are some advantages using this system, including faster polishing time, simpler quality inspection, and more evenly surface roughness result compared with manual polishing. The overall results of this research would encourage further developments to achieve robust computer vision technique for robotic polishing application.

    KW - Computer vision

    KW - Polishing robot

    KW - Surface defect characerizations

    KW - Surface roughness and artificial neural networks

    UR - http://www.scopus.com/inward/record.url?scp=79951997908&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=79951997908&partnerID=8YFLogxK

    U2 - 10.1109/SCORED.2010.5704017

    DO - 10.1109/SCORED.2010.5704017

    M3 - Conference contribution

    SN - 9781424486489

    SP - 281

    EP - 286

    BT - Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010

    ER -