In a workpiece production method a plurality of nominally similar workpieces are produced in a production process on one production machine. The order or time of production of some of the workpieces on the production machine is recorded. Some of the workpieces recorded are measured at two or more inspection stations. Dimensions or points of one workpiece are measured at one of the inspection stations, and corresponding dimensions or points of another of the workpieces are measured at another of the inspection stations. The results of the measurements of corresponding dimensions or points made at the two or more inspection stations are analysed together, taking account of the order or time of production of the workpieces. An output signal is produced based on the analysing of the results together. The output signal indicates performance of the production machine or of one or more of the inspection stations.

The invention relates to a method (100) for controlling a film production in which at least one film is produced depending on at least one specific recipe information (R), where the following steps are performed: providing different fingerprints (F), the fingerprints (F) characterizing different method executions (210) for producing a film, providing in each case at least one result information (E) for the respective fingerprint (F), the result information (E) being specific for at least one product property (D) of the produced film, storing the fingerprints (F) and result information (E) as data in a data system (200) so that the data is provided as a basis for evaluation for controlling at least one subsequent method execution (210).

Methods, apparatus, and computer program products for analyzing, monitoring, and/or modeling the manufacture of a type of part by a manufacturing process. Non-destructive evaluation data and/or quality related data collected from manufactured parts of the type of part may be aligned to a simulated model associated with the type of part. Based on the aligned data, the manufacturing process may be monitored to determine whether the manufacturing process is operating properly; aspects of the manufacturing process may be spatially correlated to the aligned data; and/or the manufacturing process may be analyzed.

A mounting state informing apparatus includes a database, an acquisition unit, a first specifying unit, a comparison unit and an output unit. The database stores information upon a mounting position and a direction of each of multiple components belonging to a processing apparatus. The acquisition unit acquires first appearance data, which is obtained by a 3D scanner, indicating a state of an appearance of the processing apparatus. The first specifying unit identifies the multiple components based on the first appearance data and specifies a mounting position and a direction of each of the identified components. The comparison unit compares the specified mounting position and the specified direction of each of the identified components with the information upon the mounting position and the direction stored in the database. The output unit is configured to output a comparison result obtained by the comparison unit.

Methods and systems for detection of an endpoint of a substrate process are provided. A set of machine learning models are trained to provide a metrology measurement value associated with a particular type of metrology measurement for a substrate based on spectral data collected for the substrate. A respective machine learning model is selected to be applied to future spectral data collected during a future substrate process for a future substrate in view of a performance rating associated with the particular type of metrology measurement. Current spectral data is collected during a current process for a current substrate and provided as input to the respective machine learning model. An indication of a respective metrology measurement value corresponding to the current substrate is extracted from one or more outputs of the trained machine learning model. In response to a determination that the respective metrology measurement satisfies a metrology measurement criterion, an instruction including a command to terminate the current process is generated.

According to one embodiment, a processing information management system includes: an abnormality analyzer configured to generate abnormality occurrence data of a target wafer based on processing location information, the processing location information collected based on a first sensor outputting a first sensor signal according to a detected processing state, the first sensor provided in a wafer processing apparatus; and an integration system configured to integrate the abnormality occurrence data into wafer map data corresponding to the target wafer.

In an embodiment, a method of automatically generating an inspection program includes receiving input data related to an object to be inspected. The input data includes geometric dimensioning and tolerancing data for the object. The method also includes, for each of a plurality of surfaces of the object, generating at least one inspection direction and a plurality of inspection points based, at least in part, on the geometric dimensioning and tolerancing data. The method also includes generating transitional motions for an inspection machine to inspect the plurality of surfaces according to the inspection directions and the inspection points. The method also includes storing, at a destination, machine-readable code for inspecting the object according to the at least one inspection direction of each of the plurality of surfaces, the inspection points of each of the plurality of surfaces, and the transitional motions.

A method of preparing a self-aligned via on a semiconductor workpiece includes using an integrated sequence of processing steps executed on a common manufacturing platform hosting a plurality of processing modules including one or more film-forming modules, one or more etching modules, and one or more transfer modules. The integrated sequence of processing steps include receiving the workpiece into the common manufacturing platform, the workpiece having a pattern of metal features in a dielectric layer wherein exposed surfaces of the metal features and exposed surfaces of the dielectric layer together define an upper planar surface; selectively etching the metal features to form a recess pattern by recessing the exposed surfaces of the metal features beneath the exposed surfaces of the dielectric layer using one of the one or more etching modules; and depositing an etch stop layer over the recess pattern using one of the one or more film-forming modules.

Provided is a system and method for visual inspection. The system may be used in a quality assurance station at a manufacturing facility or site. The system may evaluate and determine the quality of manufactured or fabricated articles. The system may include a mechanical subsystem for capturing images of the article. The system may include a sensor such as a camera for capturing data, such as images. The system may include an artificial intelligence system to determine if the article suffers from an impermissible defect.

A wafer defect test apparatus in which a defect prediction performance is improved and a simulation time is shortened is provided. The wafer defect test apparatus comprises a wafer variable generator which receives a first structural measurement data and a first process condition data of a first wafer, and a second structural measurement data and a second process condition data of a second wafer, generates a first process variable and a second process variable based on the first structural measurement data and the first process condition data, and generates a third process variable and a fourth process variable based on the second structural measurement data and the second process condition data, an abnormal wafer index generating circuit which generates a first wafer vector of the first process variable and second process variable, generates a second wafer vector of the third process variable and fourth process variable, calculates a first Euclidean distance between the first wafer vector and the second wafer vector, calculates a first Cosine distance between the first wafer vector and the second wafer vector, and generates a first abnormal wafer index of the first wafer based on a product of the first Euclidean distance and the first Cosine distance, and a prediction model generating circuit which receives a first characteristic variable which is a test result of the first wafer, and generates a wafer defect prediction model through a regression based on the first process variable, the second process variable, the first characteristic variable, and the first abnormal wafer index.