Applied Materials, Inc.

Brooks Automation Gmbh

Jianping Zou

James Robert Moyne

Jimmy Iskandar

Parris C M Hawkins

Keith A Edwards

James Anthony Mullins

Described herein are methods, apparatuses, and systems for reducing equipment repair time. In one embodiment, a computer implemented method includes collecting test substrate data or other metrology data and fault detection data for maintenance recovery of at least one manufacturing tool in a manufacturing facility and determining a relationship between tool parameter settings for the manufacturing tool and the test substrate data. The method further includes utilizing virtual metrology predictive algorithms and at least some collected data to obtain a metrology prediction and applying multivariate run-to-run (R2R) control modeling to obtain a state estimation including a current operating region of the at least one manufacturing tool. Applying multivariate run-to-run (R2R) control modeling to obtain tool parameter adjustments for at least one manufacturing tool to reduce maintenance recovery time and to reduce requalification time.

Methods and systems for applying run-to-run control and virtual metrology to reduce equipment recovery time

Described herein are methods, apparatuses, and systems for reducing equipment repair time. Disclosed methods include collecting data including test substrate data or other metrology data and fault detection data for maintenance recovery of at least one manufacturing tool in a manufacturing facility. Disclosed methods include determining a relationship between tool parameter settings for the at least one manufacturing tool and at least some collected data including the test substrate data. The disclosure includes utilizing virtual metrology predictive algorithms and at least some collected data to obtain a metrology prediction and applying multivariate run-to-run (R2R) control modeling to obtain a tool parameter adjustment for at least one target parameter for the at least one manufacturing tool. The disclosure further includes applying the R2R control modeling to obtain tool parameter adjustments for at least one manufacturing tool.

A system and method for reducing pilot runs of run-to-run control in a manufacturing facility calculates an unbiased estimation of an independent model intercept based on a state space model associated with the manufacturing facility. A determination is made as to whether to perform a pilot run in the manufacturing facility. Upon determining that the run is to be performed, an indication that the pilot run is to be performed is generated. Pilot run data is received in response to the pilot run being performed, and the state space model is updated based on the received data.

Reducing pilot runs of run-to-run control in a manufacturing facility

A method and system for estimating context offsets for run-to-run control in a semiconductor fabrication facility is described. In one embodiment, contexts associated with a process are identified. The process has one or more threads, and each thread involves one or more contexts. A set of input-output equations describing the process is defined. Each input-output equation corresponds to a thread and includes a thread offset expressed as a summation of individual context offsets. A state-space model is created that describes an evolution of the process using the set of input-output equations. The state-space model allows to estimate individual context offsets.

Method and system for estimating context offsets for run-to-run control in a semiconductor fabrication facility

A method for a run-to-run (R2R) control system includes processing materials using a process input and producing a process output, storing the process input in a database, the storing including using a timestamp, and storing at least one measurement of the process output in the database aligned with each process input using the timestamp. The method further includes iterating over the data in the database to estimate one or more coefficients for a model, and, if one or more measurements is missing, replacing the missing measurements based on a prediction from said model. The model is updated with said coefficient estimates. The method additionally includes iterating over the data from the database to estimate a process state, and, if one or more of the measurements is missing from the database, replacing the missing measurements based on prediction from the model. The model is updated with said process state estimate. A controller may receive the updated model and utilize the model to produce the next process input. The updated model may also be utilized to generate an estimate for a measurable process variable, wherein the estimate can be compared to an actual measurement to determine if the estimate is within confidence limits. If the estimate is not within confidence limits, a fault is indicated.

Semiconductor run-to-run control system with state and model parameter estimation

A method for a run-to-run (R2R) control system includes processing materials using a process input and producing a process output, storing the process input in a database, the storing including using a timestamp, storing at least one measurement of the process output in the database aligned with each process input using the timestamp, iterating over the data from the database to estimate a process state, and, if one or more of the measurements is missing from the database, predicting the missing measurements for the database based on a model, and determining an error for calculating a next process input, the error based on the data in the database.

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Austin, TX, United States of America

Jianping Zou