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    • 1. 发明申请
    • AUTONOMOUS BIOLOGICALLY BASED LEARNING TOOL
    • 自主生物学的学习工具
    • WO2009114387A1
    • 2009-09-17
    • PCT/US2009/036169
    • 2009-03-05
    • TOKYO ELECTRON LIMITEDKAUSHAL, SanjeevPATEL, Sukesh JanubhaiSUGISHIMA, Kenji
    • KAUSHAL, SanjeevPATEL, Sukesh JanubhaiSUGISHIMA, Kenji
    • G06F17/00
    • G06N5/04G05B13/0265G06N5/02G06N99/005
    • Autonomous biologically based learning tool systems and methods that the tool systems employ for learning and analysis are provided. An autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes, and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats data, and (c) an autonomous learning system based on biological principles of learning, such system comprises a memory platform and a processing platform that are defined recursively and communicate through a network. Autonomous tool systems can be deployed recursively to assemble increasingly complex autonomous tools. Knowledge generated and accumulated in the autonomous learning system(s) associated with individual or assembled complex autonomous tools can be cast into semantic networks that can be employed for learning and driving tool goals based on context.
    • 提供了自动生物学的学习工具系统和工具系统用于学习和分析的方法。 一种自主的基于生物学的学习工具系统包括(a)执行一组特定任务或过程的一个或多个工具系统,并生成与表征各种过程和相关工具性能的资产相关的资产和数据; (b)接收和格式化数据的交互管理器,以及(c)基于生物学习原理的自主学习系统,该系统包括递归定义并通过网络进行通信的存储器平台和处理平台。 自动工具系统可以递归部署,以组合日益复杂的自主工具。 在与个人或组装的复杂自主工具相关的自主学习系统中生成和积累的知识可以被投入到可以用于基于上下文学习和驱动工具目标的语义网络中。
    • 10. 发明申请
    • SEMICONDUCTOR PROCESSING SYSTEM WITH WIRELESS SENSOR NETWORK MONITORING SYSTEM INCORPORATED THEREWITH
    • 具有无线传感器网络监控系统的半导体处理系统
    • WO2007112180A3
    • 2008-01-10
    • PCT/US2007063462
    • 2007-03-07
    • TOKYO ELECTRON LTDTOKYO ELECTRON AMERICA INCKAUSHAL SANJEEVSUGISHIMA KENJIRAO DONTHINENI RAMESH KUMAR
    • KAUSHAL SANJEEVSUGISHIMA KENJIRAO DONTHINENI RAMESH KUMAR
    • H01L21/00
    • H01L21/67253H01L21/67242H01L21/67248H01L21/67288H01L2924/0002H01L2924/00
    • A method and system for non-invasive sensing and monitoring of a processing system (100, 200) employed in semiconductor manufacturing. The method allows for detecting and diagnosing drift and failures in the processing system (100, 200) and taking the appropriate correcting measures. The method includes positioning at least one non-invasive sensor (247a-d, 248a-b, 249a-b, 250a-c, 906) on an outer surface of a system component of the processing system (200), where the at least one invasive sensor forms a wireless sensor network (902), acquiring a sensor signal from the at least one non-invasive sensor (247a-d, 248a-b, 249a-b, 250a-c, 906), where the sensor signal tracks a gradual or abrupt change in a processing state of the system component during flow of a process gas in contact with the system component, and extracting the sensor signal from the wireless sensor network (902) to store and process the sensor signal. In one embodiment, the non-invasive sensor (247a-d, 248a-b, 249a-b, 250a-c, 906) can be an accelerometer sensor and the wireless sensor network (902) can be motes-based.
    • 一种用于半导体制造中使用的处理系统(100,200)的非侵入式感测和监测的方法和系统。 该方法允许检测和诊断处理系统(100,200)中的漂移和故障并采取适当的校正措施。 该方法包括将至少一个非侵入式传感器(247a-d,248a-b,249a-b,250a-c,906)定位在处理系统(200)的系统部件的外表面上,其中至少 一个入侵传感器形成无线传感器网络(902),从至少一个非侵入式传感器(247a-d,248a-b,249a-b,250a-c,906)获取传感器信号,其中传感器信号跟踪 在与系统部件接触的处理气体的流动期间系统部件的处理状态的逐渐或突然的变化,以及从无线传感器网络(902)提取传感器信号以存储和处理传感器信号。 在一个实施例中,非侵入式传感器(247a-d,248a-b,249a-b,250a-c,906)可以是加速度计传感器,并且无线传感器网络(902)可以是基于空白的。