Method and system of diagnosing a processing system using adaptive multivariate analysis
First Claim
1. A method of monitoring a processing system for processing a substrate during the course of semiconductor manufacturing, comprising:
- acquiring initial data from said processing system for a plurality of observations from a first set of substrate runs having performed a process in the processing system, said initial data comprising a plurality of data parameters;
constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data from the first set;
acquiring additional data from said processing system after said constructing step from a second set of substrate runs performing said process in the processing system, said additional data comprising an additional observation of said plurality of data parameters;
adjusting said centering coefficients at the time of each observation of the additional data from the second set by utilizing both said initial data and current data obtained from the additional observation from the process performed in the second set to produce updated adaptive centering coefficients for each of said data parameters in said PCA model;
applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged;
determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients;
setting a control limit for said at least one statistical quantity;
comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of semiconductor manufacturing for the second set; and
providing an output assessing the process being performed in the processing system.
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Abstract
A method and system of monitoring a processing system and for processing a substrate during the course of semiconductor manufacturing. As such, data is acquired from the processing system for a plurality of observations, the data including a plurality of data parameters. A principal components analysis (PCA) model is constructed from the data and includes centering coefficients. Additional data is acquired from the processing system, the additional data including an additional observation of the plurality of data parameters. The centering coefficients are adjusted to produce updated adaptive centering coefficients for each of the data parameters in the PCA model. The updated adaptive centering coefficients are applied to each of the data parameters in the PCA model. At least one statistical quantity is determined from the additional data using the PCA model. A control limit is set for the statistical quantity and compared to the statistical quantity.
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Citations
44 Claims
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1. A method of monitoring a processing system for processing a substrate during the course of semiconductor manufacturing, comprising:
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acquiring initial data from said processing system for a plurality of observations from a first set of substrate runs having performed a process in the processing system, said initial data comprising a plurality of data parameters; constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data from the first set; acquiring additional data from said processing system after said constructing step from a second set of substrate runs performing said process in the processing system, said additional data comprising an additional observation of said plurality of data parameters; adjusting said centering coefficients at the time of each observation of the additional data from the second set by utilizing both said initial data and current data obtained from the additional observation from the process performed in the second set to produce updated adaptive centering coefficients for each of said data parameters in said PCA model; applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged; determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients; setting a control limit for said at least one statistical quantity; comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of semiconductor manufacturing for the second set; and providing an output assessing the process being performed in the processing system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. In a process control system including a principal components analysis (PCA) model for monitoring a processing system for processing a substrate during the course of semiconductor manufacturing, the improvement comprising:
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an adaptive centering coefficient for a data parameter obtained during a current observation made after construction of a PCA model from a first set of substrate runs having performed a process in the processing system, said adaptive centering coefficient combining an old value of said adaptive centering coefficient and a current value of said data parameter for said current observation from a second set of substrate runs performing said process in the processing system to produce at each observation of data an updated adaptive centering coefficient, wherein said old value of said adaptive centering coefficient comprises a mean value of data parameters obtained during a plurality of observations preceding said current observation; at least one statistical quantity determined using a combination of said PCA model created from the first set of substrate runs and unchanged and additional data acquired after construction of the PCA model that has been centered by the updated adaptive centering coefficients; said updated adaptive centering coefficient implemented in the PCA model to provide, based on the statistical quantity, an improved process center for the substrate processing in order to update the substrate processing during the course of semiconductor manufacturing for the second set; and said improved process center producing an output assessing the process being performed in the processing system. - View Dependent Claims (20, 21, 22, 23, 24)
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25. A processing system for processing a substrate during the course of semiconductor manufacturing, comprising:
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a process tool; and a process performance monitoring system coupled to said process tool and comprising a plurality of sensors coupled to said process tool and a controller coupled to said plurality of sensors and said process tool, wherein said controller includes, means for acquiring initial data from said plurality of sensors for a plurality of observations from a first set of substrate runs having performed a process in the processing system, said initial data comprising a plurality of data parameters, means for constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data, means for acquiring additional data from said plurality of sensors after construction of the PCA model from a second set of substrate runs performing said process in the processing system, means for adjusting said centering coefficients at the time of each observation of the additional data by utilizing both previous run data from said initial data and current data obtained by the means for acquiring additional data to produce updated adaptive centering coefficients for each of said data parameters, means for applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged, means for determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients, means for setting a control limit for said at least one statistical quantity, means for comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of semiconductor manufacturing for the second set; and means for providing an output assessing the process being performed in the processing system. - View Dependent Claims (26, 27, 28, 29, 30, 31, 32)
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33. A processing performance monitoring system to monitor a processing system for processing a substrate during the course of semiconductor manufacturing, comprising:
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a plurality of sensors coupled to said processing system; and a controller coupled to said plurality of sensors and said processing system, wherein said controller includes, means for acquiring initial data from said plurality of sensors for a plurality of observations from a first set of substrate runs having performed a process in the processing system, said initial data comprising a plurality of data parameters, means for constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data, means for acquiring additional data from said plurality of sensors acquired after construction of the PCA model from a second set of substrate runs performing said process in the processing system, means for adjusting said centering coefficients at the time of each observation of the additional data by utilizing both previous run data from said initial data and current data obtained by the means for acquiring additional data to produce updated centering coefficients for each of said data parameters, means for applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged, means for determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients, means for setting a control limit for said at least one statistical quantity, means for comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of semiconductor manufacturing for the second set; and means for providing an output assessing the process being performed in the processing system. - View Dependent Claims (34, 35, 36, 37, 38, 39, 40)
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41. A method of monitoring a first processing system for processing a substrate during the course of semiconductor manufacturing, comprising:
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acquiring initial data from a processing system for a plurality of observations from a first set of substrate runs having performed a process in the processing system, said initial data comprising a plurality of data parameters; constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data; acquiring additional data from said first processing system after constructing the PCA model from a second set of substrate runs performing said process in the processing system, said additional data comprises an additional observation of said plurality of data parameters; adjusting said centering coefficients at the time of each observation of the additional data by utilizing both previous run data from said initial data and current data obtained from the additional observations to produce updated adaptive coefficients for each of said data parameters in said PCA model; applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged; determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients; setting a control limit for said at least one statistical quantity; comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of semiconductor manufacturing for the second set; and providing an output assessing the process being performed in the processing system. - View Dependent Claims (42)
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43. A computer readable medium containing program instructions for execution on a computer system, which when executed by the computer system, cause the computer system to perform substrate processing comprising:
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acquiring initial data from a processing system for a plurality of observations from a first set of substrate runs having performed a process in a processing system, said initial data comprising a plurality of data parameters; constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data; acquiring additional data from said processing system after constructing the PCA model from a second set of substrate runs performing said process in the processing system, said additional data comprising an additional observation of said plurality of data parameters; adjusting said centering coefficients by utilizing both previous run data from said initial data and current data obtained from the additional observation to produce updated adaptive centering coefficients for each of said data parameters in said PCA model; applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged; determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients; setting a control limit for said at least one statistical quantity; comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of semiconductor manufacturing for the second set; and providing an output assessing the process being performed in the processing system.
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44. A computer readable medium containing program instructions for execution on a computer system, which when executed by the computer system, cause the computer system to perform substrate processing comprising:
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acquiring initial data from a second processing system for a plurality of observations from a first set of substrate runs having performed a process in a processing system, said initial data comprising a plurality of data parameters; constructing a principal components analysis (PCA) model from said data parameters of the first set, said PCA model including centering coefficients for the initial data; acquiring additional data from a first processing system after constructing the PCA model from a second set of substrate runs performing said process in the processing system, said additional data comprises an additional observation of said plurality of data parameters; adjusting said centering coefficients by utilizing both previous run data from said initial data and current data obtained from the additional observation to produce updated adaptive centering coefficients for each of said data parameters in said PCA model; applying said updated adaptive centering coefficients to each of said data parameters in said PCA model created from the first set of substrate runs and unchanged; determining at least one statistical quantity using a combination of said PCA model and the additional data that has been centered by the updated adaptive centering coefficients; setting a control limit for said at least one statistical quantity; comparing said at least one statistical quantity to said control limit in order to determine if the substrate processing remains within control during the course of manufacturing for the second set; and providing an output assessing the process being performed in the processing system.
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Specification