Abstract: The present invention provides methods and apparatus for predictive maintenance of semiconductor process equipment. In some embodiments, a method for performing predictive maintenance on semiconductor processing equipment includes performing at least one self-diagnostic test on the semiconductor processing equipment with no substrate present in the equipment; comparing a result of the at least one self diagnostic test to at least one baseline characterization of the equipment; and determining whether equipment maintenance is required based upon the comparison.

Abstract: A method and apparatus for processing a semiconductor wafer is provided for reducing dimensional variation by feeding forward information relating to photoresist mask CD and profile and underlying layer thickness measured at several points on the wafer to adjust the next process the inspected wafer will undergo (e.g., the etch process). After the processing step, dimensions of a structure formed by the process, such as the CD and depth of a trench formed by the process, are measured at several points on the wafer, and this information is fed back to the process tool to adjust the process for the next wafer to further reduce dimensional variation. In certain embodiments, the CD, profile, thickness and depth measurements, etch processing and post-etch cleaning are performed at a single module in a controlled environment.

Abstract: A method is provided that includes (1) receiving information about a substrate processed within a low K dielectric deposition subsystem from an integrated inspection system of the low K dielectric deposition subsystem; (2) determining an etch process to perform within an etch subsystem based at least in part on the information received from the inspection system of the low K dielectric deposition subsystem; and (3) directing the etch subsystem to etch at least one low K dielectric layer on the substrate based on the etch process. Other methods, systems, apparatus, data structures and computer program products are provided.

Abstract: Plasma events are detected by analyzing the spectral emissions of a plasma process of a substrate. A plasma is monitored by a spectrometer which produces plasma emission data which includes an intensity value for each individual wavelength which is a large quantity of information. The plasma emission data is processed with an algorithm or combination of algorithms to reduce the quantity of the plasma emission data. A peak finding algorithm which identifies the wavelengths of light which are associated with a plasma process allowing the other wavelengths to be ignored. A data reduction algorithm provides a single value representative of the intensity of the emitted light from each peak. A noise reduction algorithm removes noise from the spectral signal by eliminating signals at wavelengths which do not exceed a threshold intensity and do not exceed a threshold wavelength span. The data may also be processed with principal component analysis to further reduce the optical emission data.

Abstract: A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component.

Abstract: A method and apparatus for processing a semiconductor wafer is provided for reducing dimensional variation by feeding forward information relating to photoresist mask CD and profile and underlying layer thickness measured at several points on the wafer to adjust the next process the inspected wafer will undergo (e.g., the etch process). After the processing step, dimensions of a structure formed by the process, such as the CD and depth of a trench formed by the process, are measured at several points on the wafer, and this information is fed back to the process tool to adjust the process for the next wafer to further reduce dimensional variation. In certain embodiments, the CD, profile, thickness and depth measurements, etch processing and post-etch cleaning are performed at a single module in a controlled environment.

Abstract: Plasma events are detected by analyzing the spectral emissions of a plasma process of a substrate. A plasma is monitored by a spectrometer which produces plasma emission data which includes an intensity value for each individual wavelength which is a large quantity of information. The plasma emission data is processed with an algorithm or combination of algorithms to reduce the quantity of the plasma emission data. A peak finding algorithm which identifies the wavelengths of light which are associated with a plasma process allowing the other wavelengths to be ignored. A data reduction algorithm provides a single value representative of the intensity of the emitted light from each peak. A noise reduction algorithm removes noise from the spectral signal by eliminating signals at wavelengths which do not exceed a threshold intensity and do not exceed a threshold wavelength span. The data may also be processed with principal component analysis to further reduce the optical emission data.

Abstract: Run-to-run variation of a semiconductor fabrication tool is minimized utilizing a mirror image target. A goal represents a process result desired from operation of the tool. The mirror image target is generated by adding the goal to a difference between an output from a previous tool run and the goal. Prediction of tool performance is based upon a data-based modeling engine utilizing a reference library correlating operational parameters with observed process results for prior tool runs. The mirror image target vector is compared to the reference library and serves as a basis for generating the recipe for the subsequent process run. This recipe automatically brings operation of the tool back toward the goal. The method may further include comparison of the suggested recipe with the recipe of the prior run to determine whether run-to-run variation is serious enough to warrant a change in tool conditions, or whether run-to-run variation is so serious as to indicate a major tool problem.

Abstract: A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component.

Abstract: A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component.

Abstract: A method and apparatus for monitoring process state using plasma attributes are provided. Electromagnetic emissions generated by a plasma are collected, and a detection signal having at least one frequency component is generated based on the intensity of the collected electromagnetic emissions; or, the RF power delivered to a wafer pedestal is monitored and serves as the detection signal. The magnitude of at least one frequency component of the detection signal then is monitored over time. By monitoring the magnitude of at least one frequency component of the detection signal over time, a characteristic fingerprint of the plasma process is obtained. Features within the characteristic fingerprint provide process state information, process event information and process chamber information. In general, any chemical reaction having an attribute that varies with reaction rate may be similarly monitored.

Abstract: A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component.

Abstract: A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component.

Abstract: The present invention provides an apparatus and method for processing a workpiece in an inductively coupled plasma reactor. Inductive power is applied to the reactor to generate a plasma. A magnetic field is generated within the plasma reactor having lines of force oriented perpendicular to the workpiece surface. It is a feature of the invention to control the electron temperature near the surface of the workpiece by controlling the applied magnetic field. It is a further feature to increase average ion density near the workpiece without otherwise causing damage to the workpiece due to uneven charge build-up. The applied magnetic field can be time invariant or time variant. In both cases processing can be optimized by adjusting the magnitude of the magnetic field to a level just below where damage due to uneven charge build-up occurs. With the time variant field, the average ion density can be adjusted with respect to average electron temperature.

Abstract: The present invention provides an apparatus and method for processing a workpiece in an inductively coupled plasma reactor. Inductive power is applied to the reactor to generate a plasma. A magnetic field is generated within the plasma reactor having lines of force oriented perpendicular to the workpiece surface. It is a feature of the invention to control the electron temperature near the surface of the workpiece by controlling the applied magnetic field. It is a further feature to increase average ion density near the workpiece without otherwise causing damage to the workpiece due to uneven charge build-up. The applied magnetic field can be time invariant or time variant. In both cases, processing can be optimized by adjusting the magnitude of the magnetic field to a level just below where damage due to uneven charge build-up occurs. With the time variant field, the average ion density can be adjusted with respect to average electron temperature.