DocumentCode :
122139
Title :
Data mining photovoltaic cell manufacturing data
Author :
Evans, Roger ; Dore, Jonathon ; Van Voorthuysen, Erik ; Jingbing Zhu ; Green, Martin A.
Author_Institution :
Australian Centre for Adv. Photovoltaics, UNSW, Sydney, NSW, Australia
fYear :
2014
fDate :
8-13 June 2014
Firstpage :
2699
Lastpage :
2704
Abstract :
So called “data mining” techniques comprise a broad family of statistical investigative and analysis techniques from informal exploratory and graphical methods through to sophisticated multivariate analysis. Data mining of photovoltaic (PV) cell manufacturing data can be used with an understanding of cell performance to isolate the variance in production associated with wafer material quality or other time based changes. This can lead to new insights for SPC and for understanding process variance.
Keywords :
data mining; electronic engineering computing; graph theory; integrated circuit manufacture; production engineering computing; solar cells; statistical analysis; PV cell; SPC; data mining techniques; graphical methods; multivariate analysis; photovoltaic cell manufacturing data; process variance; statistical analysis techniques; time based changes; wafer material quality; Data mining; Manufacturing; Materials; Photovoltaic systems; Production; Time series analysis; Vectors; data mining; manufacturing; photovoltaic cells; process control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Photovoltaic Specialist Conference (PVSC), 2014 IEEE 40th
Conference_Location :
Denver, CO
Type :
conf
DOI :
10.1109/PVSC.2014.6925486
Filename :
6925486
Link To Document :
بازگشت