scholarly journals Simulation-Based Analysis on Operational Control of Batch Processors in Wafer Fabrication

2020 ◽  
Vol 10 (17) ◽  
pp. 5936
Author(s):  
Pyung-Hoi Koo ◽  
Rubén Ruiz

In semiconductor wafer fabrication (wafer fab), wafers go through hundreds of process steps on a variety of processing machines for electrical circuit building operations. One of the special features in the wafer fabs is that there exist batch processors (BPs) where several wafer lots are processed at the same time as a batch. The batch processors have a significant influence on system performance because the repetitive batching and de-batching activities in a reentrant product flow system lead to non-smooth product flows with high variability. Existing research on the BP control problems has mostly focused on the local performance, such as waiting time at the BP stations. This paper attempts to examine how much BP control policies affect the system-wide behavior of the wafer fabs. A simulation model is constructed with which experiments are performed to analyze the performance of BP control rules under various production environments. Some meaningful insights on BP control decisions are identified through simulation results.

2011 ◽  
Vol 48-49 ◽  
pp. 123-126 ◽  
Author(s):  
Li Li ◽  
Fei Qiao

An effective rescheduling method takes an important role on improving the operational performance of a semiconductor wafer fabrication facility (fabs). In this paper, we propose a rescheduling method based on swarm intelligence. Firstly, we build a swarm intelligence based rescheduling model (SIRM) including an ant queen agent, multiple job ant agents and machine ant agents. Secondly, we design a rescheduling algorithm (CMRA) composed of three sub-algorithms: sub-algorithm-1 is used by an ant queen agent to transfer an existing static optimized scheduling plan into additional pheromones of job ant agents; sub-algorithm-2 and sub-algorithm-3 are used to convert scheduling related real-time information to dynamic pheromones of job ant agents and machine ant agents, respectively. Finally, a simplified semiconductor wafer fab model is used to verify and validate CMRA. The simulation results demonstrate that CMRA is superior to the original scheduling method to generate a static optimized scheduling plan with better performance on move, step and on-time operational due date rate under uncertain production environments.


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