Yield improvement analysis with parameter-screening factorials

Journal article

Authors/Editors

TIRANEE ACHALAKUL

Strategic Research Themes

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Publication Details

Author list: Yamwong W., Achalakul T.

Publisher: Elsevier

Publication year: 2012

Journal: Applied Soft Computing (1568-4946)

Volume number: 12

Issue number: 3

Start page: 1021

End page: 1040

Number of pages: 20

ISSN: 1568-4946

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855989359&doi=10.1016%2fj.asoc.2011.11.021&partnerID=40&md5=cd2fe04ad6751fb07a85a620fa4e5464

Languages: English-Great Britain (EN-GB)

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Abstract

This paper presents a technique for the critical parameter analysis of the disk drive manufacturing process. The objective of the work is to improve the manufacturing yield by tuning the parameters that significantly affect the yield. Several techniques were studied including the sensitivity analysis framework, which is currently used at several disk drive plants. From our initial experiments, we found that the sensitivity analysis results were not sufficiently good and the interactions between parameters were not identified. We then designed a new technique based on factorial designs, the parameter-screening factorials algorithm. Our method can work with a large number of inputs within reasonable computing time, and can identify both the parameter and the interaction effects. The results can be obtained more quickly and are better in comparison with the currently used technique. Moreover, by applying the technique to the full list instead of the pre-selected list of the manufacturing parameters, we discovered that the parameters watch list previously identified by the experts should be adjusted to include some extra parameters. After the results were validated by the experts, we designed software that automates the critical parameter analysis process. The software should greatly benefit the daily yield analysis at the disk drive manufacturing plant greatly. ฉ 2011 Elsevier B.V. All rights reserved.

Keywords

Critical parameter identification, Factorial designs, Yield improvement analysis