Abstract:
A method and system for measuring overlay in a semiconductor manufacturing process comprise capturing an image of a feature in an article at a predetermined manufacturing stage, deriving a quantity of an image parameter from the image and converting the quantity into an overlay measurement. The conversion is by reference to an image parameter quantity derived from a reference image of a feature at the same predetermined manufacturing stage with known overlay (“OVL”). There is also disclosed a method of determining a device inspection recipe for use by an inspection tool comprising identifying device patterns as candidate device care areas that may be sensitive to OVL, deriving an OVL response for each identified pattern, correlating the OVL response with measured OVL, and selecting some or all of the device patterns as device care areas based on the correlation.
Abstract:
A method and system for measuring overlay in a semiconductor manufacturing process comprise capturing an image of a feature in an article at a predetermined manufacturing stage, deriving a quantity of an image parameter from the image and converting the quantity into an overlay measurement. The conversion is by reference to an image parameter quantity derived from a reference image of a feature at the same predetermined manufacturing stage with known overlay (“OVL”). There is also disclosed a method of determining a device inspection recipe for use by an inspection tool comprising identifying device patterns as candidate device care areas that may be sensitive to OVL, deriving an OVL response for each identified pattern, correlating the OVL response with measured OVL, and selecting some or all of the device patterns as device care areas based on the correlation.
Abstract:
Methods and systems for determining characteristic(s) of patterns of interest (POIs) are provided. One system is configured to acquire output of an inspection system generated at the POI instances without detecting defects at the POI instances. The output is then used to generate a selection of the POI instances. The system then acquires output from an output acquisition subsystem for the selected POI instances. The system also determines characteristic(s) of the POI using the output acquired from the output acquisition subsystem.
Abstract:
A weak pattern identification method includes acquiring inspection data from a set of patterns on a wafer, identifying failing pattern types on the wafer, and grouping like pattern types of the failing pattern types into a set of pattern groups. The weak pattern identification method also includes acquiring image data from multiple varied instances of a first pattern type grouped in a first group, wherein the multiple varied instances of the first pattern type are formed under different conditions. The weak pattern identification method also includes comparing images obtained from common structures of the instances of the first pattern type to identify local differences within a portion of the first pattern type. Further, the weak pattern identification method includes identifying metrology sites within the portion of the first pattern type proximate to a location of the local differences within the portion of the first pattern type.
Abstract:
A system, method, and computer program product are provided for systematic and stochastic characterization of pattern defects identified from a fabricated component. In use, a plurality of pattern defects detected from a fabricated component are identified. Additionally, attributes of each of the pattern defects are analyzed, based on predefined criteria. Further, a first set of pattern defects of the plurality of pattern defects are determined, from the analysis, to be systematic pattern defects, and a second set of pattern defects of the plurality of pattern defects are determined, from the analysis, to be stochastic pattern defects. Moreover, a first action is performed for the determined systematic pattern defects and a second action is performed for the determined stochastic pattern defects.
Abstract:
Methods and systems for providing weak pattern (or hotspot) detection and quantification are disclosed. A weak pattern detection and quantification system may include a wafer inspection tool configured to inspect a wafer and detect defects present on the wafer. The system may also include at least one processor in communication with the wafer inspection tool. The at least one processor may be configured to: perform pattern grouping on the detected defects based on design of the wafer; identify regions of interest based on the pattern grouping; identify weak patterns contained in the regions of interest identified, the weak patterns being patterns deviating from the design by an amount greater than a threshold; validate the weak patterns identified; and report the validated weak patterns or facilitate revision of the design of the wafer based on the validated weak patterns.
Abstract:
Universal target based inspection drive metrology includes designing a plurality of universal metrology targets measurable with an inspection tool and measurable with a metrology tool, identifying a plurality of inspectable features within at least one die of a wafer using design data, disposing the plurality of universal targets within the at least one die of the wafer, each universal target being disposed at least proximate to one of the identified inspectable features, inspecting a region containing one or more of the universal targets with an inspection tool, identifying one or more anomalistic universal targets in the inspected region with an inspection tool and, responsive to the identification of one or more anomalistic universal targets in the inspected region, performing one or more metrology processes on the one or more anomalistic universal metrology targets with the metrology tool.
Abstract:
Methods and systems for binning defects on a wafer are provided. One method includes identifying areas in a design for a layer of a device being fabricated on a wafer that are not critical to yield of fabrication of the device and generating an altered design for the layer by eliminating features in the identified areas from the design for the layer. The method also includes binning defects detected on the layer into groups using the altered design such that features in the altered design proximate positions of the defects in each of the groups are at least similar.
Abstract:
A method and system for measuring overlay in a semiconductor manufacturing process comprise capturing an image of a feature in an article at a predetermined manufacturing stage, deriving a quantity of an image parameter from the image and converting the quantity into an overlay measurement. The conversion is by reference to an image parameter quantity derived from a reference image of a feature at the same predetermined manufacturing stage with known overlay (“OVL”). There is also disclosed a method of determining a device inspection recipe for use by an inspection tool comprising identifying device patterns as candidate device care areas that may be sensitive to OVL, deriving an OVL response for each identified pattern, correlating the OVL response with measured OVL, and selecting some or all of the device patterns as device care areas based on the correlation.
Abstract:
Defects can be identified using a hybrid design layout that includes a printable layer and a non-printed layer. The hybrid design layout can be generated by incorporating at least a portion of the non-printable layer layout with the printable layer layout. Defects can be identified using optical or scanning electron beam images.