東海大學 工業工程與經營資訊學系

東海工工88雙強論壇「半導體製程」產學對話 

演講者：
范書愷 教授
國立台北科技大學 工業工程與管理系 教授
科技部工業工程與管理學門召集人(2020-2022)
Editor-in-Chief, Engineering Optimization (SCI, Top 13% in Scopus, Taylor & Francis)
Board Member & Vice President, Asia-Pacific Industrial Engineering & Management Systems Society

朱憲國 事業群總經理
力晶積成電子製造股份有限公司

演講日期: 109年10月30日(五)

演講地點:東海大學工學院E108教室(地圖請見附件)

主辦單位: 東海大學工業工程與經營資訊學系
共同主辦單位:  科技部工業工程與管理學門
 
 
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范書愷教授演講大綱：
The semiconductor industry has become fully automated during the manufacturing process and abundant process parameters are collected on-line by sensors for fault detection and classification purposes. Analyzing process parameters and identifying a smaller set of key parameters that have crucial influence on wafer quality will bring great benefits in stabilizing the manufacturing process and enhancing productive yield. Typically, this type of the parameter set is called the “raw trace data”. This paper considers image processing techniques as a novel approach for analyzing and visualizing the raw trace data. First, the one-dimensional time series data of a wafer batch was transformed into a two-dimensional image. Fisher’s criterion ratios of the labeled good and defective wafer image maps are computed to identify the key parameters. The key parameters identified by the proposed image processing technique are consistent with the technical experience of the process engineers. Furthermore, the texture analysis technique with 2D Fourier transform is utilized to analyze the images of the key parameters to detect defective wafers. The proposed key parameter identification and wafer classification method proves to be a viable solution under the paradigm of advanced process control practice for semiconductor manufacturing.

• 東海大學工業工程與經營資訊系E108教室 講者簡歷