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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Main Authors: Masood, Ibrahim, Abdul Rahman, Norasulaini, Abdul Halim, Siti Nur Hasrat
Format: Article
Language:English
Published: ARPN Journal 2016
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Online Access:http://eprints.uthm.edu.my/3827/1/AJ%202016%20%288%29.pdf
http://eprints.uthm.edu.my/3827/
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spelling my.uthm.eprints.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
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic QA75 Electronic computers. Computer science
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
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.
format Article
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
title 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_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_sort identification of unnatural variation in manufacturing of hard disc drive component
publisher ARPN Journal
publishDate 2016
url http://eprints.uthm.edu.my/3827/1/AJ%202016%20%288%29.pdf
http://eprints.uthm.edu.my/3827/
_version_ 1738581172794949632
score 13.214268