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.