| Author | Mongklon Lerttaveevit |
| Subject(s) | Magnetic recorders and recording--Heads
|
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechatronics, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Abstract | The propose of this Thesis was to study surface roughness of magnetic recording head defects in order to improve accuracy of defect classification by using 2D image, which was done by human. The study was processed by using surface profiles of slider head defects from AFM analysis. Information of profile, e.g., color, number of pixel, and defective location were studied to determine criteria of each defect for classification. The evaluation required simulation software that was developed for studied parameters called that auto defect classification or ADC. The performance was compared to two manual methods, optical microscope inspection and inspection on monitor screen. The classification of both manual methods depends on human’s skill The results of the study showed that accuracy of classification by optical microscope is the 82%, on monitor screen inspection is 91%, and ADC is 100%. From the comparison of three methods, classification that is based on using information of surface roughness has the best performance. It can improve accuracy in classification and it is an independent method from using human skill. |
| Year | 2015 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Microelectronics (ME) |
| Chairperson(s) | Mongkol Ekpanyapong; |
| Examination Committee(s) | Dailey, Matthew N.;Tirawat Tarawatcharasart ;Danai Lohwithee; |
| Scholarship Donor(s) | NECTEC;AIT Fellowship;Western Digital (Thailand) Co., Ltd.; |