Browse > Article
http://dx.doi.org/10.5859/KAIS.2017.26.2.105

A Study on analysis framework development for yield improvement in discrete manufacturing  

Song, Chi-Wook (SK 주식회사 C&C SF사업 1팀)
Roh, Geum-Jong (삼성디스플레이 OLED 제조혁신팀)
Park, Dong-Jin (공주대학교)
Publication Information
The Journal of Information Systems / v.26, no.2, 2017 , pp. 105-121 More about this Journal
Abstract
Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.
Keywords
Discrete Manufacturing; Yield Improvements; Data Mining;
Citations & Related Records
연도 인용수 순위
  • Reference
1 신정훈, 황승준, "DEA와 로지스틱 회귀분석을 이용한 자동차부품기업의 효율성 분석 및 재무전략", 한국경영과학 학회지, 41(1), 2016, pp. 127-143.
2 안경찬, 문창배, 김병만, 이종열, 장득현, 김지윤, 성혜정 "연관규칙 마이닝 알고리즘을 이용한 POS 데이터 분석 시스템", 대한 산업공학회 춘계 공동 학술 대회 논문집, 2012, pp. 2542-2547.
3 정혜진, 구본철, "데이터 마이닝을 이용한 로버스트 설계 모형의 최적화", 산업 경영 시스템 학회지, 30(2), 2007, pp. 99-105.
4 Brian E. Goodlin, Duane S. Boning, and Herbert H. Sawin, "Simultaneous Fault Detection and Classification for Semiconductor Manufacturing Tools." Journal of the Electrochemical Society, Vol.150, No.12, 2003, pp.778-784.   DOI
5 Bernard Kamsu-Foguem, Fabien Rigal, Félix Mauget "Mining association rules for the quality improvement of the production process", Expert Systems with Applications, 40(4), 2013, pp. 1034-1045.   DOI
6 Lee, J, Bagheri, B and Kao, H, A Cyber-Physical Systems architecture for Industry 4.0 based manufacturing systems. Manufacturing Letters 3 (2015), pp18-2.   DOI
7 Duane S. Boning , Jerry Stefani, Stephanie W. Butler., "Statistical Methods for Semiconductor Manufacturing", Encyclopedia of Electrical Engineering, 1999, pp. 1-22.
8 G. A. Cherry, S. J. Qin, "Multiblock Principal Component Analysis Based on a Combined Index for Semiconductor Fault Detection and Diagnosis", IEEE Transactions on Semiconductor Manufacturing, Vol.19, No.2, 2006, pp.159-172.   DOI
9 L. Monostori, B. Kadar, T. Bauernhansl, S. Kondoh, S. Kumara, G. Reihart, O. Sauer, G. Schuh, W. Shin, K. Ueda, "Cyber-physical system in manufacturing," CIRP Annals, Manufacturing Technology 65, 2016, pp.621-641.   DOI
10 Ming-Da Ma. David Shan-Hill Wong, Shi- Shang Jang, Sheng-Tsaing Tseng, "Fault detection based on statistical multivariate analysis and microarray visualization," Industrial Informatics, IEEE Transactions on, Vol.6, No.1, 2010, pp.18-24.   DOI
11 이필립, 박영미, 최양연 "조선 생산 실행 시스템 업무 분석을 위한 연관성 규칙 방법 적용", 한국 CAD/CAM 학회 하계 학술대회 논문집, 2013, pp. 117-122.
12 Rakesh Agrawal, Tomasz Imielinski & Arun Swami, "Mining association rules between sets of items in large database", ACM SIGMOD Conference, 1993, pp. 207-216.
13 Yu, Peng. Lee. Jong-Nam, Lee, Jang-Hee "A Quality management using Data mining Techniques for Small and Medium Manufacturing Companies", 대한 경영학회지, 25(9), 2012, pp. 3579-3599.
14 Susana Ferreiro, Basilio Sierra, Itziar Irigoien, Eneko Gorritxategi, "Data Mining for quality control : Burr detection in the drilling process", Computer & Industrial Engineering, 60(4), 2011, pp. 801-810.   DOI
15 Wei-Chou Chen, Shian-Shyoung Tseng. Ching-Yao Wang, "A novel manufacturing defect detection method using association rule mining techniques", Expert System with Application 29, 2005, pp.807-815.   DOI