Abstract:
A virtual metrology system and a method therefor are provided herein. In the system, a set of process data is gathered and clustered according to a plurality of predetermined patterns. The clustered set of process data is calculated according to the corresponding pattern, so as to obtain a comparison result. If the obtained result meets a desired output, a corresponding step is performed based on the result. In one case, the corresponding step is a normal sampling step if the clustered set of process data meets the corresponding pattern. If the clustered set of process data does not meet the corresponding pattern, an alarm is generated thereby, and the corresponding equipment may be shut down. In another case, the corresponding step is a maintenance, repair, and overhaul step if the clustered set of process data meets the corresponding pattern.
Abstract:
A method of a fault detection and classification (FDC) may be used to determine outlier tools from a plurality of tools. The method includes generating a plurality of parameter charts, generating a plurality of group charts according to the plurality of parameter charts, generating a score table according to the plurality of group charts, determining outlier tools according to the score table, and performing tool correction on the outlier tools.
Abstract:
A method of monitoring a processing system for processing a substrate is provided. The method includes the following steps: acquiring data from the processing system for a plurality of parameters, the data including a plurality of data values; grouping the parameters into a plurality of sub-groups, each of the sub-groups including a plurality of correlated parameters; constructing a principle components analysis (PCA) model from the data values for the correlated parameters in a first one of the sub-groups, including normalizing the data values in the first one of the sub-groups with a first weighting factor and a second weighting factor, wherein the first weighting factor is different from the second weighting factor; and determining a statistical quantity using the PCA model.
Abstract:
A method of virtual metrology is disclosed. Process data and measurement values corresponding to a workpiece are collected. The process data and the measurement values are used to establish a conjecture model. A theoretical model corresponding to the workpiece and the conjecture model is used to establish another conjecture model. The another conjecture model is used to establish a virtual metrology value. The virtual metrology value is used to predict properties of a subsequently manufactured workpiece.
Abstract:
A virtual metrology system at least includes a process apparatus including a set of process data, the process apparatus producing a workpiece according to the set of process data. A virtual metrology server is configured to gather the set of process data, cluster the set of process data to obtain data clusters, and compare the data clusters with patterns. If the data clusters meet the patterns corresponding to the data clusters, performing a corresponding maintenance, repair, and overhaul step on the process apparatus.
Abstract:
A virtual metrology system at least includes a process apparatus including a set of process data, the process apparatus producing a workpiece according to the set of process data. A virtual metrology server is configured to gather the set of process data, cluster the set of process data to obtain data clusters, and compare the data clusters with patterns. If the data clusters meet the patterns corresponding to the data clusters, performing a corresponding maintenance, repair, and overhaul step on the process apparatus.
Abstract:
A virtual metrology system and a method therefor are provided herein. In the system, a set of process data is gathered and clustered according to a plurality of predetermined patterns. The clustered set of process data is calculated according to the corresponding pattern, so as to obtain a comparison result. If the obtained result meets a desired output, a corresponding step is performed based on the result. In one case, the corresponding step is a normal sampling step if the clustered set of process data meets the corresponding pattern. If the clustered set of process data does not meet the corresponding pattern, an alarm is generated thereby, and the corresponding equipment may be shut down. In another case, the corresponding step is a maintenance, repair, and overhaul step if the clustered set of process data meets the corresponding pattern.
Abstract:
A method of monitoring a processing system for processing a substrate is provided. The method includes the following steps: acquiring data from the processing system for a plurality of parameters, the data including a plurality of data values; grouping the parameters into a plurality of sub-groups, each of the sub-groups including a plurality of correlated parameters; constructing a principle components analysis (PCA) model from the data values for the correlated parameters in a first one of the sub-groups, including normalizing the data values in the first one of the sub-groups with a first weighting factor and a second weighting factor, wherein the first weighting factor is different from the second weighting factor; and determining a statistical quantity using the PCA model.