Identification of unnatural variation in manufacturing of hard disc drive component
Hard disc drive (HDD) is known as a main device in a computer. In order to produce a high quality HDD, the source of unnatural variation need to be identified and controlled during manufacturing operation. In this research, simulation and modeling approach was utilized for analyzing the statistical...
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| Format: | Article |
| Language: | English |
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ARPN Journal
2016
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| Online Access: | http://eprints.uthm.edu.my/3827/ http://eprints.uthm.edu.my/3827/1/AJ%202016%20%288%29.pdf |
| _version_ | 1848888124251308032 |
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| author | Masood, Ibrahim Abdul Rahman, Norasulaini Abdul Halim, Siti Nur Hasrat |
| author_facet | Masood, Ibrahim Abdul Rahman, Norasulaini Abdul Halim, Siti Nur Hasrat |
| author_sort | Masood, Ibrahim |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Hard disc drive (HDD) is known as a main device in a computer. In order to produce a high quality HDD, the source of unnatural variation need to be identified and controlled during manufacturing operation. In this research, simulation and modeling approach was utilized for analyzing the statistical process control (SPC) chart patterns of unnatural variation associated to its root cause error. Initially, the computer aided design (CAD) software was used to model a HDD component and to analyze the source of unnatural variation in manufacturing operation. Then, the artificial data streams for SPC were generated mathematically using MATLAB programming. The process started with normal (in-control) condition and can be followed by sudden shifts when there is a disruption of unnatural variation such as loading error, offsetting in cutting tool, and inconsistency in pneumatic pressure. The design parameters of artificial data streams can be manipulated in terms of window size (WS, length of data streams), magnitude of shifts (Sigma, size of unnatural variation), initial point of shifts (IS), and cross correlation (p) for bivariate data. The results indicated that the generation of artificial data streams can be adapted effectively to various condition of unnatural variation. Generally, this research has provided useful methodology for a quality practitioner in identifying the source of unnatural variation based on the SPC chart patterns. |
| first_indexed | 2025-11-15T20:05:17Z |
| format | Article |
| id | uthm-3827 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:05:17Z |
| publishDate | 2016 |
| publisher | ARPN Journal |
| recordtype | eprints |
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| spelling | uthm-38272021-11-22T04:03:17Z http://eprints.uthm.edu.my/3827/ Identification of unnatural variation in manufacturing of hard disc drive component Masood, Ibrahim Abdul Rahman, Norasulaini Abdul Halim, Siti Nur Hasrat QA75 Electronic computers. Computer science Hard disc drive (HDD) is known as a main device in a computer. In order to produce a high quality HDD, the source of unnatural variation need to be identified and controlled during manufacturing operation. In this research, simulation and modeling approach was utilized for analyzing the statistical process control (SPC) chart patterns of unnatural variation associated to its root cause error. Initially, the computer aided design (CAD) software was used to model a HDD component and to analyze the source of unnatural variation in manufacturing operation. Then, the artificial data streams for SPC were generated mathematically using MATLAB programming. The process started with normal (in-control) condition and can be followed by sudden shifts when there is a disruption of unnatural variation such as loading error, offsetting in cutting tool, and inconsistency in pneumatic pressure. The design parameters of artificial data streams can be manipulated in terms of window size (WS, length of data streams), magnitude of shifts (Sigma, size of unnatural variation), initial point of shifts (IS), and cross correlation (p) for bivariate data. The results indicated that the generation of artificial data streams can be adapted effectively to various condition of unnatural variation. Generally, this research has provided useful methodology for a quality practitioner in identifying the source of unnatural variation based on the SPC chart patterns. ARPN Journal 2016 Article PeerReviewed text en http://eprints.uthm.edu.my/3827/1/AJ%202016%20%288%29.pdf Masood, Ibrahim and Abdul Rahman, Norasulaini and Abdul Halim, Siti Nur Hasrat (2016) Identification of unnatural variation in manufacturing of hard disc drive component. ARPN Journal of Engineering and Applied Sciences, 11 (10). pp. 6434-6438. ISSN 1819-6608 |
| spellingShingle | QA75 Electronic computers. Computer science Masood, Ibrahim Abdul Rahman, Norasulaini Abdul Halim, Siti Nur Hasrat Identification of unnatural variation in manufacturing of hard disc drive component |
| title | Identification of unnatural variation in manufacturing of hard disc drive component |
| title_full | Identification of unnatural variation in manufacturing of hard disc drive component |
| title_fullStr | Identification of unnatural variation in manufacturing of hard disc drive component |
| title_full_unstemmed | Identification of unnatural variation in manufacturing of hard disc drive component |
| title_short | Identification of unnatural variation in manufacturing of hard disc drive component |
| title_sort | identification of unnatural variation in manufacturing of hard disc drive component |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.uthm.edu.my/3827/ http://eprints.uthm.edu.my/3827/1/AJ%202016%20%288%29.pdf |