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  4. Equipment deterioration modeling and cause diagnosis in semiconductor manufacturing
 
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Equipment deterioration modeling and cause diagnosis in semiconductor manufacturing

Journal
International Journal of Intelligent Systems
Date Issued
2021
Author(s)
Rostami H
Blue J
Chen A
ARGON CHEN  
JAKEY BLUE  
DOI
10.1002/int.22395
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100888974&doi=10.1002%2fint.22395&partnerID=40&md5=f543656445f88eaec035dea80a98a103
https://scholars.lib.ntu.edu.tw/handle/123456789/577105
Abstract
Condition-based monitoring (CBM) as a new control scheme suggests characterizing the machine condition and triggering the corresponding control actions. CBM includes prognostic and diagnostic modules. In this study, the framework of equipment deterioration modeling and monitoring for batch processes is proposed with two objectives in the semiconductor industry. The first one is to characterize equipment behavior by exploiting the temporal data of batch processes. The second one is to model the deterioration trend with the most related causes. With the best-fitted mother wavelet, wavelet packet decomposition transforms the temporal data into macro and micro level domains to identify two types of deterioration. The determinant of the correlation matrix of the decomposed signals is calculated as the equipment condition, and the factors that account for the deterioration are identified through a stepwise searching algorithm. A case study shows that the proposed methodology can identify influencing factors and model deterioration. ? 2021 Wiley Periodicals LLC
Subjects
Batch data processing; Semiconductor device manufacture; Signal processing; Wavelet decomposition; Condition-based monitoring; Correlation matrix; Deterioration modeling; Equipment conditions; Searching algorithms; Semiconductor industry; Semiconductor manufacturing; Wavelet Packet Decomposition; Deterioration
SDGs

[SDGs]SDG9

Type
journal article

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