Abstract: Methods and systems for accurate arc detection in semiconductor manufacturing tools are disclosed. Such methods and systems provide real-time arc detection and near real-time notification for corrective actions during a semiconductor manufacturing process. Such methods and systems utilize data with high sample rate and wavelet analysis to provide for more accurate arc detection, which leads to more effective and cost efficient semiconductor manufacturing operations.

Abstract: A method is provided for determining one or more causes for variability in data. The method includes selecting a first range of a multivariate model output data on a user interface and employing a computing system, operatively coupled to the user interface, to determine one or more process data causing a variability of the multivariate model output data in the first range when compared to a second range of the multivariate model output data. At least some of the process data includes data derived from a physical measurement of a process variable.

Abstract: Methods and systems for accurate arc detection in semiconductor manufacturing tools are disclosed. Such methods and systems provide real-time arc detection and near real-time notification for corrective actions during a semiconductor manufacturing process. Such methods and systems utilize data with high sample rate and wavelet analysis to provide for more accurate arc detection, which leads to more effective and cost efficient semiconductor manufacturing operations.

Abstract: Methods and systems for accurate arc detection in semiconductor manufacturing tools are disclosed. Such methods and systems provide real-time arc detection and near real-time notification for corrective actions during a semiconductor manufacturing process. Such methods and systems utilize data with high sample rate and wavelet analysis to provide for more accurate arc detection, which leads to more effective and cost efficient semiconductor manufacturing operations.

Abstract: A semiconductor substrate processing system having acoustic monitoring is disclosed. The system includes a process chamber adapted to perform a process on a substrate, a process fluid source, a fluid conduit coupling the fluid source to the process chamber, and a flow control valve located along the fluid conduit and adapted to be operable to control a flow of a process fluid between the process fluid source and the process chamber. The system includes one or more acoustic sensors operable to sense acoustic noise coupled to at least one of the process fluid source, the fluid conduit, and the flow control valve, and an acoustic processor adapted to receive at least one signal from the one or more acoustic sensors. Acoustic monitoring methods are provided, as are other aspects.

Abstract: A method is provided for determining one or more causes for variability in data. The method includes selecting a first range of a multivariate model output data on a user interface and employing a computing system, operatively coupled to the user interface, to determine one or more process data causing a variability of the multivariate model output data in the first range when compared to a second range of the multivariate model output data. At least some of the process data includes data derived from a physical measurement of a process variable.

Abstract: A TSV (through silicon via) reveal process using CMP (chemical mechanical polishing) may be acoustically monitored and controlled to detect TSV breakage and automatically respond thereto. Acoustic emissions received by one or more acoustic sensors positioned proximate a substrate holder and/or a polishing pad of a CMP system may be analyzed to detect TSV breakage during a CMP process. In response to detecting TSV breakage, one or more remedial actions may automatically occur. In some embodiments, a polishing pad platen may have one or more acoustic sensors integrated therein that extend into a polishing pad mounted on the polishing pad platen. Methods of monitoring and controlling a TSV reveal process are also provided, as are other aspects.

Abstract: A semiconductor substrate processing system having acoustic monitoring is disclosed. The system includes a process chamber adapted to perform a process on a substrate, a process fluid source, a fluid conduit coupling the fluid source to the process chamber, and a flow control valve located along the fluid conduit and adapted to be operable to control a flow of a process fluid between the process fluid source and the process chamber. The system includes one or more acoustic sensors operable to sense acoustic noise coupled to at least one of the process fluid source, the fluid conduit, and the flow control valve, and an acoustic processor adapted to receive at least one signal from the one or more acoustic sensors. Acoustic monitoring methods are provided, as are other aspects.

Abstract: Methods and systems for accurate arc detection in semiconductor manufacturing tools are disclosed. Such methods and systems provide real-time arc detection and near real-time notification for corrective actions during a semiconductor manufacturing process. Such methods and systems utilize data with high sample rate and wavelet analysis to provide for more accurate arc detection, which leads to more effective and cost efficient semiconductor manufacturing operations.