Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: Offline metrology measurements are performed on substrates that have been subjected to lithographic processing. Model parameters are calculated by fitting the measurements to an extended high-order substrate model defined using a combination of basis functions that include an edge basis function related to a substrate edge. A radial edge basis function may be expressed in terms of distance from a substrate edge. The edge basis function may, for example, be an exponential decay function or a rational function. Lithographic processing of a subsequent substrate is controlled using the calculated high-order substrate model parameters, in combination with low-order substrate model parameters obtained by fitting inline measurements to a low order model.

Abstract: Offline metrology measurements are performed on substrates that have been subjected to lithographic processing. Model parameters are calculated by fitting the measurements to an extended high-order substrate model defined using a combination of basis functions that include an edge basis function related to a substrate edge. A radial edge basis function may be expressed in terms of distance from a substrate edge. The edge basis function may, for example, be an exponential decay function or a rational function. Lithographic processing of a subsequent substrate is controlled using the calculated high-order substrate model parameters, in combination with low-order substrate model parameters obtained by fitting inline measurements to a low order model.

Abstract: Offline metrology measurements are performed on substrates that have been subjected to lithographic processing. Model parameters are calculated by fitting the measurements to an extended high-order substrate model defined using a combination of basis functions that include an edge basis function related to a substrate edge. A radial edge basis function may be expressed in terms of distance from a substrate edge. The edge basis function may, for example, be an exponential decay function or a rational function. Lithographic processing of a subsequent substrate is controlled using the calculated high-order substrate model parameters, in combination with low-order substrate model parameters obtained by fitting inline measurements to a low order model.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: Offline metrology measurements are performed on substrates that have been subjected to lithographic processing. Model parameters are calculated by fitting the measurements to an extended high-order substrate model defined using a combination of basis functions that include an edge basis function related to a substrate edge. A radial edge basis function may be expressed in terms of distance from a substrate edge. The edge basis function may, for example, be an exponential decay function or a rational function. Lithographic processing of a subsequent substrate is controlled using the calculated high-order substrate model parameters, in combination with low-order substrate model parameters obtained by fitting inline measurements to a low order model.

Abstract: Metrology measurements are performed on substrates that have been subjected to lithographic processing. Model parameters are calculated by fitting the measurements to an extended high-order substrate model defined using a combination of basis functions that include an edge basis function related to a substrate edge. A radial edge basis function may be expressed in terms of distance from a substrate edge. The edge basis function may, for example, be an exponential decay function or a rational function. Lithographic processing of a subsequent substrate is controlled using the calculated high-order substrate model parameters, in combination with low-order substrate model parameters obtained by fitting inline measurements to a low order model.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in said multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in said multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in said multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

Abstract: Metrology measurements are performed on substrates that have been subjected to lithographic processing. Model parameters are calculated by fitting the measurements to an extended high-order substrate model defined using a combination of basis functions that include an edge basis function related to a substrate edge. A radial edge basis function may be expressed in terms of distance from a substrate edge. The edge basis function may, for example, be an exponential decay function or a rational function. Lithographic processing of a subsequent substrate is controlled using the calculated high-order substrate model parameters, in combination with low-order substrate model parameters obtained by fitting inline measurements to a low order model.

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in said multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.