Abstract: Described herein is a method for determining process drifts or outlier wafers over time in semiconductor manufacturing. The method involves obtaining a key performance indicator (KPI) variation (e.g., LCDU) characterizing a performance of a semiconductor process over time, and data associated with a set of factors associated with the semiconductor process. A model of the KPI and the data is used to determine contributions of a first set of factors toward the KPI variation, the first set of factors breaching a statistical threshold. The contributions from the first set of factors toward the KPI variation is removed from the model to obtain a residual KPI variation. Based on the residual KPI variation, a residual value breaching a residual threshold is determined. The residual value indicates process drifts in the semiconductor process over time or an outlier substrate corresponding to the residual value at a certain time.

Abstract: A method of topography determination, the method including: obtaining a first focus value derived from a computational lithography model modeling patterning of an unpatterned substrate or derived from measurements of a patterned layer on an unpatterned substrate; obtaining a second focus value derived from measurement of a substrate having a topography; and determining a value of the topography from the first and second focus values.

Abstract: A method of hot spot ranking for a patterning process. The method includes obtaining (i) a set of hot spots of a patterning process, (ii) measured values of one or more parameters of the patterning process corresponding to the set of hot spots, and (ii) simulated values of the one or more parameters of the patterning process corresponding to the set of hot spots; determining a measurement feedback based on the measured values and the simulated values of the one or more parameters of the patterning process; and determining, via simulation of a process model of the patterning process, a ranking of a hot spot within the set of hot spots based on the measurement feedback.

Abstract: A defect prediction method for a device manufacturing process involving processing one or more patterns onto a substrate, the method including: determining values of one or more processing parameters under which the one or more patterns are processed; and determining or predicting, using the values of the one or more processing parameters, an existence, a probability of existence, a characteristic, and/or a combination selected from the foregoing, of a defect resulting from production of the one or more patterns with the device manufacturing process.

Abstract: A method of topography determination, the method including: obtaining a first focus value derived from a computational lithography model modeling patterning of an unpatterned substrate or derived from measurements of a patterned layer on an unpatterned substrate; obtaining a second focus value derived from measurement of a substrate having a topography; and determining a value of the topography from the first and second focus values.

Abstract: A defect prediction method for a device manufacturing process involving processing one or more patterns onto a substrate, the method including; determining values of one or more processing parameters under which the one or more patterns are processed; and determining or predicting, using the values of the one or more processing parameters, an existence, a probability of existence, a characteristic, and/or a combination selected from the foregoing, of a defect resulting from production of the one or more patterns with the device manufacturing process.

Abstract: A method of topography determination, the method including: obtaining a first focus value derived from a computational lithography model modeling patterning of an unpatterned substrate or derived from measurements of a patterned layer on an unpatterned substrate; obtaining a second focus value derived from measurement of a substrate having a topography; and determining a value of the topography from the first and second focus values.

Abstract: A method of defect validation for a device manufacturing process, the method including: obtaining a first image of a pattern processed into an area on a substrate using the device manufacturing process under a first condition; obtaining a metrology image from the area; aligning the metrology image and the first image; and determining from the first image and the metrology image whether the area contains a defect, based on one or more classification criteria.

Abstract: A defect prediction method for a device manufacturing process involving processing one or more patterns onto a substrate, the method including; determining values of one or more processing parameters under which the one or more patterns are processed; and determining or predicting, using the values of the one or more processing parameters, an existence, a probability of existence, a characteristic, and/or a combination selected from the foregoing, of a defect resulting from production of the one or more patterns with the device manufacturing process.

Abstract: A method of topography determination, the method including: obtaining a first focus value derived from a computational lithography model modeling patterning of an unpatterned substrate or derived from measurements of a patterned layer on an unpatterned substrate; obtaining a second focus value derived from measurement of a substrate having a topography; and determining a value of the topography from the first and second focus values.

Abstract: A defect prediction method for a device manufacturing process involving processing one or more patterns onto a substrate, the method including: determining values of one or more processing parameters under which the one or more patterns are processed; and determining or predicting, using the values of the one or more processing parameters, an existence, a probability of existence, a characteristic, and/or a combination selected from the foregoing, of a defect resulting from production of the one or more patterns with the device manufacturing process.

Abstract: A method of defect validation for a device manufacturing process, the method including: obtaining a first image of a pattern processed into an area on a substrate using the device manufacturing process under a first condition; obtaining a metrology image from the area; aligning the metrology image and the first image; and determining from the first image and the metrology image whether the area contains a defect, based on one or more classification criteria.

Abstract: A defect prediction method for a device manufacturing process involving processing one or more patterns onto a substrate, the method including: determining values of one or more processing parameters under which the one or more patterns are processed; and determining or predicting, using the values of the one or more processing parameters, an existence, a probability of existence, a characteristic, and/or a combination selected from the foregoing, of a defect resulting from production of the one or more patterns with the device manufacturing process.