Optimally Scheduling Dual-Arm Multi-Cluster Tools to Process Two Wafer Types
Qinghua Zhu, GengHong Wang, Yan Hou, Naiqi Wu, Yan Qiao
Abstract
To satisfy the requirements of high-mix integrated-circuit chip production, multiple wafer types are grouped into a lot to be fabricated concurrently in a multi-cluster tool system. However, the existing studies do not solve the scheduling problem of multi-cluster tools with multiple wafer types being processed and wafer residency time constraints being imposed. This study aims to find a feasible steady-state schedule for a process-dominant multi-cluster tool that processes two wafer types concurrently. A novel robot cycle, called one-wafer-per-type cycle, and a two-swap robot sequence are defined, under which the minimal cycle time can be achieved. Further, the schedulability for individual cluster tools with two wafer types is proved upon closed-form derivations. The schedulability conditions of a one-wafer-per-type schedule for the system are proposed. With such conditions, an efficient algorithm is established to obtain a schedule in a two-swap sequence. Several instances show the application and effectiveness of the proposed method.
BibTeX
@inproceedings{ral2022_optimallyschedul,
title = {Optimally Scheduling Dual-Arm Multi-Cluster Tools to Process Two Wafer Types},
author = {Qinghua Zhu and GengHong Wang and Yan Hou and Naiqi Wu and Yan Qiao},
booktitle = {RA-L 2022},
year = {2022}
}