Importance Sampling of Re-entrant Queueing Systems

可重入排队系统的重要性采样

• 批准号: 9622084
• 负责人: Bryan Deuermeyer
• 金额: $ 21.19万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-15 至 2001-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9622084&HistoricalAwards=false
• 关键词: Importance; Sampling; Re; entrant; Queueing

9622084 Deuermeyer This research focuses on the development of new simulation theory and methods to improve the performance and effectiveness of discrete simulation as it applies to semiconductor manufacturing. Planners and designers are becoming more interested in using cycle time to plan equipment purchases and scheduling policies; discrete-event simulation is the only analysis tool currently available to support design activities. Specific improvements in simulation methodology are needed for 1) faster execution speed, 2) methods to obtain cycle-time estimators, and 3)special variance-reduction technology that accounts for the increase in variability in cycle time caused by preventive maintenance and rare failure events. Generalized Semi-Markov Processes (GSMP) will be used as the modeling framework. This research will provide new capabilities in generating sample paths of GSMPs, developing importance sampling schemes for GSMPs, developing methods for computing crossing probabilities of cycle time and developing software to demonstrate the theoretical methods. These should contribute significantly toward solutions to the demanding problems in analysis and design of the extremely complex processes associated with semiconductor wafer fabs from the point of view of product cycle time and throughput rates, and facility and machine capacity.

9622084 Deuermeyer 这项研究的重点是开发新的仿真理论和方法，以提高离散仿真在半导体制造中的性能和有效性。 规划人员和设计人员对利用周期时间来规划设备采购和调度政策越来越感兴趣；离散事件仿真是目前唯一可用于支持设计活动的分析工具。 需要对仿真方法进行具体改进，以实现 1) 更快的执行速度，2) 获取周期时间估计器的方法，以及 3) 特殊的方差减少技术，该技术可以解决由预防性维护和罕见故障事件引起的周期时间变异性的增加。 广义半马尔可夫过程（GSMP）将用作建模框架。 这项研究将提供生成 GSMP 样本路径、开发 GSMP 重要性采样方案、开发计算周期时间交叉概率的方法以及开发软件来演示理论方法的新功能。 从产品周期时间和生产率以及设施和机器容量的角度来看，这些应该对解决与半导体晶圆厂相关的极其复杂的工艺的分析和设计中的苛刻问题做出重大贡献。