Evaluation System and Correlation Analysis for Determining the Performance of a Semiconductor Manufacturing System

Qingyun Yu; Li Li; Hui Zhao; Ying Liu; Kuo-Yi Lin

doi:10.23919/CSMS.2021.0015

Complex System Modeling and Simulation (Sep 2021)

Evaluation System and Correlation Analysis for Determining the Performance of a Semiconductor Manufacturing System

Qingyun Yu,
Li Li,
Hui Zhao,
Ying Liu,
Kuo-Yi Lin

Affiliations

Qingyun Yu: Department of Control Science and Engineering, College of Electronics and Information Engineering, Shanghai Institute of Intelligent Science and Technology, and also with Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 201804, China
Li Li: Department of Control Science and Engineering, College of Electronics and Information Engineering, Shanghai Institute of Intelligent Science and Technology, and also with Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 201804, China
Hui Zhao: Department of Control Science and Engineering, College of Electronics and Information Engineering, Shanghai Institute of Intelligent Science and Technology, and also with Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 201804, China
Ying Liu: Department of Mechanical Engineering, School of Engineering, Cardiff University, The Parade, CF24 3AA, UK
Kuo-Yi Lin: Department of Control Science and Engineering, College of Electronics and Information Engineering, Shanghai Institute of Intelligent Science and Technology, and also with Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 201804, China

DOI: https://doi.org/10.23919/CSMS.2021.0015
Journal volume & issue: Vol. 1, no. 3
pp. 218 – 231

Abstract

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Numerous performance indicators exist for semiconductor manufacturing systems. Several studies have been conducted regarding the performance optimization of semiconductor manufacturing systems. However, because of the complex manufacturing processes, potential complementary or inhibitory correlations may exist among performance indicators, which are difficult to demonstrate specifically. To analyze the correlation between the performance indicators, this study proposes a performance evaluation system based on the mathematical significance of each performance indicator to design statistical schemes. Several samples can be obtained by conducting simulation experiments through the performance evaluation system. The Pearson correlation coefficient method and canonical correlation analysis are used on the received samples to analyze linear correlations between the performance indicators. Through the investigation, we found that linear and other complex correlations exist between the performance indicators. This finding can contribute to our future studies regarding performance optimization for the scheduling problems of semiconductor manufacturing.

Published in Complex System Modeling and Simulation

ISSN: 2096-9929 (Print); 2097-3705 (Online)
Publisher: Tsinghua University Press
Country of publisher: China
LCC subjects: Science: Mathematics: Instruments and machines: Electronic computers. Computer science; Technology: Engineering (General). Civil engineering (General): Systems engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9420428

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