Name
Title | ||
|---|---|---|
Enhancement of simulation-based semiconductor manufacturing forecast quality through hybrid tool down time modeling |
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/WSC.2014.7020088 | Winter Simulation Conference |
Keywords | Field | DocType |
infineon dresden,forecasting theory,decision making,quality control,mean-time-to-repair,decision support solution,failure analysis,semiconductor device manufacture,quality forecasting,short-term simulation,preventive maintenance,mean-time-to-failure,semiconductor manufacturing,hybrid tool down time modeling,material flow forecasting | Mean time between failures,Computer science,Simulation,Decision support system,Semiconductor device fabrication,Mean time to repair,Material flow,Downtime,Reliability engineering,Preventive maintenance | Conference |
ISSN | ISBN | Citations |
0891-7736 | 978-1-4673-9741-4 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Preuss | 1 | 12 | 4.16 |
| André Naumann | 2 | 0 | 1.69 |
| Wolfgang Scholl | 3 | 62 | 8.06 |
| Boon-Ping Gan | 4 | 68 | 9.08 |
| Peter Lendermann | 5 | 219 | 25.96 |