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A Markov Chain Framework for Cycle Time Approximation of Toolsets

机译:工具集周期时间近似的马尔可夫链框架

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摘要

Cycle time is a key performance measure in semiconductor manufacturing. Currently, discrete event simulation and queueing theory are the most common approaches to estimating the cycle time of a fabrication facility. However, the performance of both approaches has been unsatisfactory due to many factors, including the inability to perform in an environment where informal and unwritten operational rules exist. Such rules create dependence between the arrival and service processes of a toolset, and, hence, render the classical queueing models inaccurate. We propose a Markov chain framework that attempts to approximate the cycle time of a toolset in the presence of informal operational rules, and we compare our approach with classical queueing models through a series of numerical examples.
机译:循环时间是半导体制造中关键的性能指标。当前,离散事件模拟和排队理论是估计制造设备周期时间的最常用方法。但是,由于许多因素,包括无法在存在非正式和不成文的操作规则的环境中执行操作,两种方法的执行效果均不令人满意。这样的规则在工具集的到达和服务过程之间建立了依赖关系,因此使经典排队模型不准确。我们提出了一个马尔可夫链框架,该框架试图在存在非正式操作规则的情况下近似工具集的循环时间,并通过一系列数值示例将我们的方法与经典排队模型进行比较。

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