Title :
Enhancement of simulation-based semiconductor manufacturing forecast quality through hybrid tool down time modeling
Author :
Preuss, Patrick ; Naumann, Andre ; Scholl, Wolfgang ; Boon Ping Gan ; Lendermann, Peter
Author_Institution :
D-SIMLAB Technol. GmbH, Dresden, Germany
Abstract :
Material flow forecast based on Short-Term Simulation has been established as a decision support solution for fine-tuning of Preventive Maintenance (PM) timing at Infineon Dresden. To ensure stable forecast quality for effective PM decision making, the typical tool uptime behavior needs to be portrayed accurately. In this paper, we present a hybrid tool down modeling approach that selectively combines deterministic and random down time modeling based on historical tool uptime behavior. The method allowed to approximate the daily uptime of reality in simulation. A generic framework to model historical down behavior of any distribution type, described by the two parameters Mean Time to Failure (MTTF) and Mean Time to Repair (MTTR) is also discussed.
Keywords :
decision making; failure analysis; forecasting theory; preventive maintenance; quality control; semiconductor device manufacture; Infineon Dresden; decision support solution; hybrid tool down time modeling; material flow forecasting; mean-time-to-failure; mean-time-to-repair; preventive maintenance; quality forecasting; semiconductor manufacturing; short-term simulation; Analytical models; Data models; Gallium nitride; Maintenance engineering; Predictive models; Radiation detectors; Stochastic processes;
Conference_Titel :
Simulation Conference (WSC), 2014 Winter
Conference_Location :
Savanah, GA
Print_ISBN :
978-1-4799-7484-9
DOI :
10.1109/WSC.2014.7020088
