SBIR Phase II: Real-time Economic Sampling System

SBIR第二阶段：实时经济采样系统

• 批准号: 0956911
• 负责人: Dadi Gudmundsson
• 金额: $ 50万
• 依托单位: Sensor Analytics Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-15 至 2012-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0956911&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Real; time

This Small Business Innovation Research (SBIR) Phase II project will create a first Real-time Economic Sampling (RES) system for quality intensive high-tech manufacturing. Focusing initially on semiconductor manufacturing, the system will allow defect inspection sampling to be optimized and adjusted many times per day across all process tools, steps, and products. This minimizes, among other things, a manufacturer's economic risk of producing bad products by adaptively focusing sampling where it gives the greatest return. The complexity of the underlying interdisciplinary models have hindered the realization of RES. Recent advancements by the applicants showed feasibility that this research will build on. There are three main research categories, 1) Risk & Optimization, 2) Cycle-Time, and 3) Yield Modeling. Categories 1 & 2 build on Phase I feasibility results where fast, yet accurate, approximations of complex factory models were established. Risk & Optimization modeling will introduce near-term risk due to factory floor events into traditional (long-run average) risk models. Cycle-time research will refine the approximations for queues with heterogeneous servers. Yield modeling will introduce novel real-time yield approximations needed for RES. The included implementation tasks will then create the first factory-ready RES system that captures the necessary intricacies of semiconductor manufacturing.The proposed RES system is a "Green Manufacturing" enabler that creates a new market as it will be the first to recoup inefficiencies present in many process control operations. The initial focus is on semiconductor manufacturers who are limited by time-consuming off-line analysis, rigid sampling rules, and risky ad-hoc sampling adjustments. Meanwhile valuable products are being wasted due to out-of-control incidents and/or under-utilized inspection capacity. The proposed system can change this. An RES system belongs to a fast growing segment of the semiconductor industry: process control. Other markets can also be pursued and a societal impact due to reduced waste can become widespread.

该小型企业创新研究（SBIR）第二阶段项目将为质量密集型高科技制造业创建第一个实时经济采样（RES）系统。该系统最初专注于半导体制造，将允许缺陷检测采样在所有工艺工具、步骤和产品中每天进行多次优化和调整。这最小化，除其他事项外，制造商的经济风险，生产不良产品的自适应重点抽样，它给出了最大的回报。潜在的跨学科模型的复杂性阻碍了RES的实现。申请人最近的进展表明了这项研究的可行性。主要有三个研究类别，1）风险优化，2）周期时间和3）收益率建模。类别1和2建立在第一阶段的可行性结果，其中快速，但准确，复杂的工厂模型的近似建立。风险优化建模将由于工厂车间事件而导致的近期风险引入传统（长期平均）风险模型。周期时间的研究将完善的近似与异构服务器的队列。成品率建模将引入RES所需的新的实时成品率近似值。所包含的实施任务将创建第一个工厂就绪的RES系统，该系统捕获半导体制造的必要复杂性。拟议的RES系统是一个“绿色制造”的推动者，它将首先弥补许多过程控制操作中存在的低效率，从而创造一个新的市场。最初的重点是半导体制造商，他们受到耗时的离线分析，严格的采样规则和风险的临时采样调整的限制。与此同时，由于失控事件和/或检查能力利用不足，有价值的产品正在被浪费。拟议的系统可以改变这一点。 RES系统属于半导体行业快速增长的部分：过程控制。 还可以开拓其他市场，减少浪费所产生的社会影响可能会变得广泛。