Abstract: A method for the tracking and identification of components of lithography systems, for example of projection exposure apparatuses for semiconductor lithography is provided. The components are each provided with at least one transponder. The transponder has a data memory, on which data relating to the respective component are stored. The transponder is configured to pick up wirelessly arriving signals of a reader and to respond with data from the data memory. The data are stored on the data memory during the production of the component and/or during the production of the lithography system and/or after the start-up of the lithography system.

Abstract: A method for the tracking and identification of components of lithography systems, for example of projection exposure apparatuses for semiconductor lithography is provided. The components are each provided with at least one transponder. The transponder has a data memory, on which data relating to the respective component are stored. The transponder is configured to pick up wirelessly arriving signals of a reader and to respond with data from the data memory. The data are stored on the data memory during the production of the component and/or during the production of the lithography system and/or after the start-up of the lithography system.

Abstract: 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.

Abstract: A method and a device for characterizing a mask for microlithography in a characterization process carried out using an optical system, wherein the optical system includes an illumination optical unit and an imaging optical unit and wherein in the characterization process structures of the mask are illuminated by the illumination optical unit, the mask is imaged onto a detector unit by the imaging optical unit and image data recorded by the detector unit are evaluated in an evaluation unit. A method includes the following steps: determining a temporal variation of at least one variable that is characteristic of the thermal state of the optical system, and modifying the characterization process depending on the temporal variation determined.

Abstract: The invention relates to a method and a device for characterizing a mask for microlithography in a characterization process carried out using an optical system, wherein the optical system comprises an illumination optical unit and an imaging optical unit and wherein in the characterization process structures of the mask are illuminated by the illumination optical unit, the mask is imaged onto a detector unit by the imaging optical unit and image data recorded by the detector unit are evaluated in an evaluation unit. A method according to the invention comprises the following steps: determining a temporal variation of at least one variable that is characteristic of the thermal state of the optical system, and modifying the characterization process depending on the temporal variation determined.

Abstract: 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.