Title :
Automated semiconductor equipment modeling and model parameter estimation using MES data
Author :
Kohn, Robert ; Werner, Stefan
Author_Institution :
Oliver Rose Inst. of Appl. Comput. Sci., Dresden Univ. of Technol., Dresden, Germany
Abstract :
Driven by upcoming simulation and optimization applications with increasing complexity, the demand for more detailed equipment models is growing. The effort to create and to parameterize practicable equipment models by providing capacity limitations and predicting processing times increases as well. Automated modeling strategies based on MES data using data mining techniques increase the efficiency of today´s modeling policies remarkably.
Keywords :
data mining; electronic engineering computing; parameter estimation; semiconductor device manufacture; semiconductor device models; MES data; automated semiconductor equipment modeling; data mining techniques; manufacturing execution systems; model parameter estimation; Analytical models; Buildings; Data mining; Data models; Semiconductor device modeling; Spline; Throughput;
Conference_Titel :
Advanced Semiconductor Manufacturing Conference (ASMC), 2010 IEEE/SEMI
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4244-6517-0
DOI :
10.1109/ASMC.2010.5551413