Abstract: Methods for consistent updates to APC models with partitioning along multiple components are generally described. In one example, a method includes acquiring measurement data from one or more semiconductor wafers of a processed first lot, the data having a plurality of contexts, applying a model having parameters with partitioning along the contexts to the measurement data; and applying a constraint on a subset of the model parameters such that the subset remains centered around zero to provide consistent updates for automated process control of lots processed after the first lot.

Abstract: Execution control systems for optimizing the efficiency of manufacturing processes are described in this application. For example, an execution management system may optimize IC processes and scheduling by analyzing a number of desired metrics along with system constraints, such as tool availability, tool reliability, etc, along with information from conventional processing tools such as APC and SPC. The optimized processing schedule may then be implemented in real-time and updated with new process requests and current information relating to tools and other metrics, thereby reducing human interaction and inefficiency. Other embodiments are also described in this application.

Abstract: The present invention facilitates multi-zone furnace (102) based deposition processes by iteratively adjusting deposition time and zonal setpoint temperatures to mitigate deviations from desired target thickness(es). Coupled feedback loops are employed to update the deposition time (520) and the zonal setpoint temperatures (510) lot to lot and batch to batch while mitigating deviations fro the desired target thickness(es). Error checking is performed by computing an error metric (506) and only updating the setpoint temperatures on the error metric being within an acceptable value (508). Additionally, an excitation parameter (512) is determined that indicates variations in furnace operation.

Abstract: Methods for consistent updates to APC models with partitioning along multiple components are generally described. In one example, a method includes acquiring measurement data from one or more semiconductor wafers of a processed first lot, the data having a plurality of contexts, applying a model having parameters with partitioning along the contexts to the measurement data; and applying a constraint on a subset of the model parameters such that the subset remains centered around zero to provide consistent updates for automated process control of lots processed after the first lot.

Abstract: Systems and methods associated with configurable advanced process control (APC) application development are described. One embodiment includes a computing system that includes configuration files corresponding to APC clients. The computing system also includes computational models corresponding to the configuration files. The computing system also includes a Rapid Advanced Control Enabler (RACE). A RACE may select a configuration file to process based, at least in part, on a request received from an APC client. A RACE may also dynamically load a computational model that corresponds to the selected configuration file. A RACE may also execute the dynamically loaded computational model and provide a response to the APC client from which the request was received.

Abstract: In one embodiment, an apparatus and method for implementing intelligent and accurate updates to state-based advanced process control (APC) models are disclosed. In one embodiment, the method comprises receiving at least one of a re-measurement or a data invalidation at a state-based advanced process control (APC) model, referencing a state value table and a state update table to determine the current state of lot measurements in the state-based APC model, updating the state value table and the state update table to reflect the at least one of the re-measurement or the data invalidation, and determining settings to apply to a lot at a process tool based on process variability patterns established by the state-based APC model from the updated values in the state value table and the state update table.

Abstract: In one embodiment, an apparatus and method for implementing intelligent and accurate updates to state-based advanced process control (APC) models are disclosed. In one embodiment, the method comprises receiving at least one of a re-measurement or a data invalidation at a state-based advanced process control (APC) model, referencing a state value table and a state update table to determine the current state of lot measurements in the state-based APC model, updating the state value table and the state update table to reflect the at least one of the re-measurement or the data invalidation, and determining settings to apply to a lot at a process tool based on process variability patterns established by the state-based APC model from the updated values in the state value table and the state update table.

Abstract: The present invention defines a system (200) for selectively controlling post-CMP dishing effects occurring in semiconductor wafers having copper metallization. The system has a CMP system (202) that performs copper overpolish and barrier polish on a copper-based semiconductor wafer (206). A profilometer (204) measures actual dishing occurring in the copper metallization after polishing. An input data set (220) includes a dishing target for the semiconductor wafer. A data integrity function (212) evaluates the profilometer's measurement, and generates an indicator of the reliability of the measurement. A modeling function (214) receives the measurement, the indicator, and the dishing target, and evaluates any differential between the dishing target and actual dishing. The modeling function generates a processing target to eliminate the differential, and modifies this process responsive to the indicator.

Abstract: The present invention defines a versatile system for analyzing accuracy of industrial measurement data. The system of the present invention compiles measurements of a primary device characteristic from a representative cross-section of a population of devices. The system provides a modeling function, from which is determined a variance for each measurement—forming a corresponding compilation of variances (200). The compilation of variances is evaluated for discontinuities (300), to identify a discontinuity within the compilation of variances. This discontinuity is utilized to determine a demarcation (302) between accurate and inaccurate measurement data.

Abstract: A tuned run-to-run controlled system is disclosed that provides tuned run-to-run control of a system. The system includes a controlled system coupled to a tuned run-to-run controller, which contains a feedback controller coupled to a tuner. Tuned run-to-run controller determines a feedback command based on a nominal gain, a maximum gain, a process error, and a tuning gain.

Abstract: A method is provided for controlling a wafer polishing process. The method includes determining a polishing characteristic for a particular type of device from a set of measurements obtained from a wafer having a device of the particular type, and updating the polishing characteristic in response to polishing and measuring a wafer having a device of the particular type. The method further includes determining the polish rate of a polisher using a set of measurements obtained from a wafer polished on the polisher; and updating the polish rate of the polisher in response to polishing a wafer on the polisher and measuring the wafer. The method also includes determining a desired polishing time on the polisher for a wafer having a device of the particular type using the updated polishing characteristic of the device and the updated polish rate of the polisher.

Abstract: A method for dispatching available lots to unallocated machines is provided that includes receiving metrics data (26) providing performance measurements for a plurality of machines (18). The method next provides for determining a state for each of the machines (18) based on the metrics data (26). The method next provides for receiving one or more lots (22) to be dispatched where each lot (22) has a lot type and each lot type is associated with one of a plurality of models. The method next provides for selecting a preferred lot type (50) for each of the plurality of models associated with each of the machines (18) based on the state of the machine. The method next provides for selecting a preferred model (52) based on a time since a last run of the model, a cost of switching to a new model and lot type, and the state of the machine (18).

Abstract: A method for dispatching available lots to unallocated machines is provided that includes receiving metrics data (26) providing performance measurements for a plurality of machines (18). The method next provides for determining a state for each of the machines (18) based on the metrics data (26). The method next provides for receiving one or more lots (22) to be dispatched where each lot (22) has a lot type and each lot type is associated with one of a plurality of models. The method next provides for selecting a preferred lot type (50) for each of the plurality of models associated with each of the machines (18) based on the state of the machine. The method next provides for selecting a preferred model (52) based on a time since a last run of the model, a cost of switching to a new model and lot type, and the state of the machine (18).