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Author: search.filters.author.Kiatwanidvilai, SomyotSubject: search.filters.subject.Hard Disk Drive

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    Head Gimbal Assembly circuit with vision technique and Fuzzy C-Means Clustering
    (2015-12-23)
    Praserttaweelap, Rawinun
    ;
    Kiatwanidvilai, Somyot
    In Hard Disk Drive (HDD) Industry, the automation system is the one key for manufacturing process. Head Gimbal Assembly (HGA) is a part of HDD which have the reader and writer circuit. The HGA circuit is very important for read/write process. This research proposes the new vision technique and clustering by Fuzzy C-Means algorithm for HGA circuit inspection in 3 groups. HGA circuits in 3 groups are good, bridging, and missing group. The bridging and missing groups are the defect group. Blob analysis is the one of vision technique that it can measure the properties of image. The measurement properties from blob analysis are used in clustering technique. Fuzzy C-Means Clustering is the clustering technique which is grouped the measurement data into the cluster group based on the natural grouping of data. From the experiment results of this research, the clustering performance from Fuzzy C-Means Clustering is 99.11% accuracy based on the measurement properties in blob analysis with 225 samples.
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    Vision inspection with k-means clustering on head gimbal assembly defect
    (2015-01-01)
    Praserttaweelap, Rawinun
    ;
    Kiatwanidvilai, Somyot
    Head Gimbal Assembly (HGA) is an important feature of read and write process in a Hard Disk Drive (HDD). Currently, HGA circuit inspections are done using human operators under microscope; the vision processing for inspection in automated systems is required. This research work proposes an algorithm for detection the HGA circuit defect by using the blob detection, and then analysis the properties of blob tool. By the measurement properties of the blob tool, the K-Means Clustering can specify the data in each group in 95.45% accuracy with 110 samples.