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Hierarchical Equipment Health Index Framework

Journal
IEEE Transactions on Semiconductor Manufacturing
Journal Volume
32
Journal Issue
3
Pages
267-276
Date Issued
2019
Author(s)
CHIA-YEN LEE  
Dong, Z.-H.
DOI
10.1109/TSM.2019.2925362
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068173806&doi=10.1109%2fTSM.2019.2925362&partnerID=40&md5=9264443f2d46317a9925f376a0b0edeb
https://scholars.lib.ntu.edu.tw/handle/123456789/526180
Abstract
In the semiconductor manufacturing industry the development of single index assessing the equipment health condition is urgent, and thus the dashboard can be used for monitoring thousands of equipment. This paper proposes a novel equipment health index (EHI) framework and a Hotelling T-squared index (HTI) to monitor equipment and support preventive maintenance in real time in the semiconductor manufacturing industry. The EHI framework consists of data preprocessing, statistical process control, analytic hierarchy process, and a comprehensive single index representing the health condition of equipment. It considers different types of the univariate control charts for each status variable identification (SVID), and aggregates the scores corresponding to the control charts throughout the hierarchical structure. The HTI considers the correlation among the selected SVIDs and builds a multivariate index by using Hotelling T-squared statistic. An empirical study of Taiwan's leading semiconductor assembly manufacturer finds that both the EHI and the HTI supported monitoring thousands of pieces of equipment in real time. In practice, firms can rapidly troubleshoot the root causes of failures by the decomposition of EHI.
SDGs

[SDGs]SDG9

Type
journal article

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