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Neurofuzzy c-Means Network-Based SCARA Robot for Head Gimbal Assembly (HGA) Circuit Inspection
Joint Authors
Kiatwanidvilai, Somyot
Praserttaweelap, Rawinun
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Decision and control of SCARA robot in HGA (head gimbal assembly) inspection line is a very challenge issue in hard disk drive (HDD) manufacturing.
The HGA circuit called slider FOS is a part of HDD which is used for reading and writing data inside the disk with a very small dimension, i.e., 45 × 64 µm.
Accuracy plays an important role in this inspection, and classification of defects is very crucial to assign the action of the SCARA robot.
The robot can move the inspected parts into the corresponding boxes, which are divided into 5 groups and those are “Good,” “Bridging,” “Missing,” “Burn,” and “No connection.” A general image processing technique, blob analysis, in conjunction with neurofuzzy c-means (NFC) clustering with branch and bound (BNB) technique to find the best structure in all possible candidates was proposed to increase the performance of the entire robotics system.
The results from two clustering techniques which are K-means, Kohonen network, and neurofuzzy c-means were investigated to show the effectiveness of the proposed algorithm.
Training results from the 30x microscope inspection with 300 samples show that the best accuracy for clustering is 99.67% achieved from the NFC clustering with the following features: area, moment of inertia, and perimeter, and the testing results show 92.21% accuracy for the conventional Kohonen network.
The results exhibit the improvement on the clustering when the neural network was applied.
This application is one of the progresses in neurorobotics in industrial applications.
This system has been implemented successfully in the HDD production line at Seagate Technology (Thailand) Co.
Ltd.
American Psychological Association (APA)
Kiatwanidvilai, Somyot& Praserttaweelap, Rawinun. 2018. Neurofuzzy c-Means Network-Based SCARA Robot for Head Gimbal Assembly (HGA) Circuit Inspection. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1130754
Modern Language Association (MLA)
Kiatwanidvilai, Somyot& Praserttaweelap, Rawinun. Neurofuzzy c-Means Network-Based SCARA Robot for Head Gimbal Assembly (HGA) Circuit Inspection. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1130754
American Medical Association (AMA)
Kiatwanidvilai, Somyot& Praserttaweelap, Rawinun. Neurofuzzy c-Means Network-Based SCARA Robot for Head Gimbal Assembly (HGA) Circuit Inspection. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1130754
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130754