Simulation-Based Cycle Time Analysis in a Front-End Wafer Fabrication Fab

Lou Yanan

Abstract

Cycle time (CT) directly influences time-to-market and production costs, which are critical factors in an industry characterized by its highly competitive and capital-intensive nature. A shorter CT facilitates yield learning for emerging technologies (e.g., AI chips) while maximizing output for mature products. Conversely, delays can lead to bottlenecks, increase work-in-progress (WIP) inventory costs, and reduce the responsiveness of fabrication fabs to fluctuations in demand.

This study examines the impact of production scheduling policies and equipment reliability on cycle time performance in a memory chip fabrication fab, with a focus on two distinct product types: mature production (type A), which requires stable output to meet customer demand, and new technology node wafers (type B), which require accelerated cycle times to support yield learning. Using FlexSim discrete-event simulation, four operational scenarios were modeled and analyzed: (1) Baseline First-In-First-Out (FIFO) scheduling, (2) Shortest Processing Time (SPT), (3) Priority-Based (PB) dispatching favoring type B wafer, and (4) FIFO with machine failure integration. 

The simulation results reveal significant variations in cycle time performance depending on the scheduling policies. For the type A wafer, PB policy increased average cycle time compared to FIFO and SPT due to deprioritization effects, although output stability was maintained. In contrast, PB scheduling reduced type B cycle time relative to FIFO and SPT, effectively supporting yield learning objectives. Machine failures were found to disproportionately affect cycle times, causing increases for both wafer types, with more impacts on type B due to its extended re-entrant processing requirements. 

To mitigate these impacts, a targeted MTTR Reduction and MTBF prolongation Strategy is proposed. This approach enables fabrication facilities to accelerate the introduction of new nodes while safeguarding the stability of mature production. The findings offer practical recommendations for implementing simulation-driven scheduling approaches in real-world wafer fabrication environments, enabling manufacturers to improve their decision-making processes. Additionally, the model and principles can be universally extended to back-end fabs without compromising generality.