A reticle thermal expansion calibration method includes exposing a group of wafers and generating a sub-recipe, performing data mining and data parsing to generate a plurality of overlay parameters, extracting a plurality of predetermined parameters from the plurality of overlay parameters, performing a linear regression on each of the predetermined parameters, and generating a coefficient of determination for each of the predetermined parameters.

Disclosed is a method for a metrology measurement on an area of a substrate comprising at least a portion of a target structure. The method comprises receiving a radiation information representing a portion of radiation scattered by the are, and using a filter in a Fourier domain for removing or suppressing at least a portion of the received radiation information that does not relate to radiation that has been scattered by the target structure for obtaining a filtered radiation information for the metrology measurement, wherein characteristics of the filter are based on target information about the target structure.

A method for improving the yield of a lithographic process, the method including: determining a parameter fingerprint of a performance parameter across a substrate, the parameter fingerprint including information relating to uncertainty in the performance parameter; determining a process window fingerprint of the performance parameter across the substrate, the process window being associated with an allowable range of the performance parameter; and determining a probability metric associated with the probability of the performance parameter being outside an allowable range. Optionally a correction to the lithographic process is determined based on the probability metric.

The invention relates to a method for operating a machine for microlithography which has a multiplicity of machine components. According to one aspect, malfunctions of these machine components that occur during the operation of the machine are each describable by a symptom, wherein the method includes the following steps: creating a database in which a cause is in each case assigned to different combinations of these symptoms, automatically recording the symptoms occurring within a predetermined time interval when a problem occurs during the operation of the machine and automatically assigning a cause to the problem on the basis of the recorded symptoms and the database.

A state monitoring method, a state monitoring apparatus and a state monitoring system for a developing device are provided. After image information is obtained through the acquired video information of the developing device, it is determined by an analysis unit whether the image information includes nozzle anomaly information, and alarm information is issued after the nozzle anomaly information is determined. Moreover, similarity between the image information that does not include the nozzle anomaly information and second preset nozzle anomaly information is compared, and the nozzle information is stored in the analysis unit in a case that the similarity between the image information and the second preset nozzle anomaly information is greater than a first threshold.

Methods of determining information about a patterning process. In a method, measurement data from a metrology process applied to each of a plurality of metrology targets on a substrate is obtained. The measurement data for each metrology target includes at least a first contribution and a second contribution. The first contribution is from a parameter of interest of a patterning process used to form the metrology target. The second contribution is from an error in the metrology process. The method further includes using the obtained measurement data from all of the plurality of metrology targets to obtain information about an error in the metrology process, and using the obtained information about the error in the metrology process to extract a value of the parameter of interest for each metrology target.

A method of determining a control setting for a lithographic apparatus. The method includes obtaining a first correction for a current layer on a current substrate based on first metrology data associated with one or more previous substrates, and obtaining a second correction for the current layer on the current substrate. The second correction is based on a residual determined based on second metrology data associated with a previous layer on the current substrate. The method further includes determining the control setting for the lithographic apparatus for patterning the current layer on the current substrate by combining the first correction and the second correction.

Aspects of disclosure provide a method for attaching wiring connections to a component using both design and field measured data of the component to produce accurate wiring connections.

A semiconductor device manufacturing system includes a photolithography apparatus that performs exposure. On a semiconductor substrate including a chip area and a scribe lane area. An etching apparatus etches the exposed semiconductor substrate. An observing apparatus images the etched semiconductor substrate. A controller controls the photolithography apparatus and the etching apparatus. The controller generates a first mask pattern and provides the first mask pattern to the photolithography apparatus. The photolithography apparatus performs exposure on the semiconductor substrate using the first mask pattern. The etching apparatus performs etching on the exposed semiconductor substrate to provide an etched semiconductor substrate. The observing apparatus generates a first semiconductor substrate image by imaging the etched semiconductor substrate corresponding to the scribe lane area. The controller generates a second mask pattern based on the first mask pattern and the first semiconductor substrate image, and provides the second mask pattern to the photolithography apparatus.

A system and methods for Advance Process Control (APC) in semiconductor manufacturing include: for each of a plurality of waiter sites, receiving a pre-process set of scatterometric training data, measured before implementation of a processing step, receiving a corresponding post-process set of scatterometric training data measured after implementation of the process step, and receiving a set of process control knob training data indicative of process control knob settings applied during implementation of the process step; and generating a machine learning model correlating variations in the pre-process sets of scatterometric training data and the corresponding process control knob training data with the corresponding post-process sets of scatterometric training data, to train the machine learning model to recommend changes to process control knob settings to compensate for variations in the pre-process scatterometric data.