ABSTRACT

In accordance with the operational characteristics of semiconductor wafer fabrication (FAB), multiple-dynamic-scheduling-rule (MDSR) selection mechanisms must be developed for dynamic scheduling in FAB. The main disadvantage of the classic MDSR selection approach is that it does not immediately reflect changes in production requirements in a dynamic FAB environment. A dynamic scheduling knowledge base (KB) is generally not static; therefore, if a major change occurs in the production system, a mechanism for modifying the KB must be established. Accordingly, we develop a dynamic scheduling scheme that uses a Q-learning-based MDSR selection mechanism to support shop floor control in FAB. This selection mechanism involves two phases: initial generation of an MDSR KB and revision of the MDSR KB. On the basis of various performance criteria, the proposed scheme exhibited superior system performance to a classic MDSR selection approach and an approach that applies fixed scheduling decisions.

摘要

根据半导体晶圆制造（FAB）的操作特点，必须开发多动态调度规则（MDSR）选择机制以实现FAB的动态调度。经典 MDSR 选择方法的主要缺点是它不能立即反映动态 FAB 环境中生产需求的变化。动态调度知识库 (KB) 通常不是静态的；因此，如果生产系统发生重大变化，则必须建立修改KB的机制。因此，我们开发了一种动态调度方案，该方案使用基于 Q 学习的 MDSR 选择机制来支持 FAB 中的车间控制。该选择机制涉及两个阶段：MDSR KB 的初始生成和 MDSR KB 的修订。根据各种性能标准，