Advanced Micro Devices Corporation

Globalfoundries Inc.

Thomas J Sonderman

Alexander James Pasadyn

Christopher Allen Bode

Anthony John Toprac

Michael Lee Miller

Anastasia Oshelski Peterson

Joyce S Oey Hewett

Elfido Coss, Jr

Richard J Markle

William Jarrett Campbell

Craig William Christian

H Jim Fulford

Robert J Chong

Brian K Cusson

Christopher H Raeder

Jin Wang

Scott Gregory Bushman

Naomi M Jenkins

Jeremy Sam Lansford

Qingsu Wang

Matthew S Ryskoski

Gregory A Cherry

Ernest Dean Adams, Iii

Howard Ernest Castle

Timothy L Jackson

Patrick M Cowan

Pirainder S Lall

Robert W Anderson

A method, apparatus and a system, for performing a process control using analysis of an upstream process is provided. The method comprises performing a first process on a workpiece and performing a qualitative analysis upon the workpiece relating to the first process, the qualitative analysis comprises analyzing at least one metrology measurement relating to the first process and a workpiece feature to evaluate a characteristic of the workpiece. The method further comprises selecting a process control parameter for performing a second process upon the workpiece based upon the qualitative analysis.

Process control using analysis of an upstream process

A method and an apparatus are provided for parallel fault detection. The method comprises receiving data associated with processing of a workpiece by a first processing tool, receiving data associated with processing of a workpiece by a second processing tool and comparing at least a portion of the received data to a common fault model to determine if a fault associated with at least one of the processing of the workpiece by the first processing tool and processing of the workpiece by the second processing tool occurred.

Parallel fault detection

A method and an apparatus for dynamically adjusting a sampling rate relating to wafer examination. A process step is performed upon a plurality of workpieces associated with a lot. A sample rate for acquiring metrology data relating to at least one of the processed workpiece is determined. A dynamic sampling rate adjustment process is performed to adaptively modify the sample rate. The dynamic sampling rate adjustment process includes comparing a predicted process outcome and an actual process outcome and modifying the sampling rate based upon the comparison.

Dynamic adaptive sampling rate for model prediction

The present invention is generally directed to plasma state monitoring to control etching processes and across-wafer uniformity, and a system for performing same. In one illustrative embodiment, the method comprises generating a plasma within an etching tool, monitoring at least one characteristic of the generated plasma, and controlling at least one parameter of a plasma etching process performed in the tool based upon the monitored at least one characteristic of the plasma. In another illustrative embodiment, the method comprises generating a plasma within an etch tool, performing a plasma etching process within the etch tool, determining at least one characteristic of the plasma, and controlling at least one parameter of the etching process based upon a comparison of the determined at least one characteristic of the plasma and a target value for the determined at least one characteristic of the plasma.

Plasma state monitoring to control etching processes and across-wafer uniformity, and system for performing same

A method is provided, the method comprising monitoring consumption of a sputter target to determine a deposition rate of a metal layer during metal deposition processing using the sputter target, and modeling a dependence of the deposition rate on at least one of deposition plasma power and deposition time. The method also comprises applying the deposition rate model to modify the metal deposition processing to form the metal layer to have a desired thickness.

Run-to-run control method for automated control of metal deposition processes

The present invention provides a method and apparatus for controlling processing tools and related control units. The method includes accessing information indicative of at least one excursion of at least one processing tool detected by a first control unit associated with the at least one processing tool. The method also includes determining at least one action to be taken by at least one second control unit associated with the at least one processing tool based on the information indicative of said at least one excursion.

Total tool control for semiconductor manufacturing

A method and an apparatus for implementing a multi-variate process control system. A workpiece is processed using a primary process control function during a first time period. A secondary process control function is performed during at least a portion of the first time period for processing of the workpiece. The secondary process control function is capable of modifying at least one secondary control parameter.

Secondary process controller for supplementing a primary process controller

The present invention is generally directed to various methods of controlling properties and characteristics of a gate insulation layer based upon electrical test data, and a system for performing same. In one illustrative embodiment, the method comprises performing at least one electrical test on at least one semiconductor device, determining at least one parameter of at least one process operation to be performed to form at least one gate insulation layer on a subsequently formed semiconductor device based upon electrical data obtained from the electrical test, and performing at least one process operation comprised of the determined parameter to form the gate insulation layer.

Methods of controlling properties and characteristics of a gate insulation layer based upon electrical test data, and system for performing same

A method and an apparatus for characterizing an uncertainty factor relating to processing workpieces. A first processing step is performed upon a workpiece. A first uncertainty factor associated with the first processing step is calculated. A final uncertainty factor associated with an end-of-line parameter relating to the workpiece is calculated based upon the first uncertainty factor. A process control function based upon the final uncertainty factor is performed.

Determining transmission of error effects for improving parametric performance

A method for initializing process controllers based on tool event data includes providing a tool having a process controller adapted to employ a control model to control an operating recipe of the tool; receiving a tool event notification; and initializing the control model in response to receiving the tool event notification. A manufacturing system includes a tool and a process controller. The tool is adapted to process wafers in accordance with an operating recipe. The process controller is adapted to employ a control model to control the operating recipe in accordance with a control algorithm. The process controller is further adapted to receive a tool event notification and initialize the control model in response to receiving the tool event notification.

Method and apparatus for initializing tool controllers based on tool event data

A method for controlling a manufacturing process includes processing a plurality of workpieces in a tool; monitoring a rework rate associated with the workpieces processed in the tool; and initiating an automatic corrective action in response to the rework rate being greater than a predetermined threshold. A manufacturing system includes a tool adapted to process a plurality of workpieces and a rework controller adapted to monitor a rework rate associated with the workpieces processed in the tool and initiate an automatic corrective action in response to the rework rate being greater than a predetermined threshold.

Method and apparatus for updating control state variables of a process control model based on rework data

A method includes processing a plurality of workpieces in accordance with an operating recipe. Metrology data associated with the processing is collected. A control model including at least one tuning parameter having a default value is provided. A plurality of perturbations is introduced to shift the tuning parameter from its default value. Control actions are generated based on the metrology data and the perturbations to the tuning parameter in the control model to modify the operating recipe. An error signal associated with each of the perturbations is generated. The default value of the tuning parameter is modified based on the error signals.

Method and apparatus for dynamically monitoring controller tuning parameters

A method for controlling a tool adapted to process workpieces in accordance with an operating recipe based on a process target value is provided. The method includes collecting manufacturing characteristic data associated with the workpieces; correlating the manufacturing characteristic data with a first manufacturing metric to generate a first manufacturing metric distribution for the workpieces; and adjusting the process target value based on the first manufacturing metric distribution. A manufacturing system includes a processing tool and a target monitor. The processing tool is adapted to process workpieces in accordance with an operating recipe based on a process target value. The target monitor is adapted to collect manufacturing characteristic data associated with the workpieces, correlate the manufacturing characteristic data with a first manufacturing metric to generate a first manufacturing metric distribution for the workpieces, and adjust the process target value based on the first manufacturing metric distribution.

Method and apparatus for controlling process target values based on manufacturing metrics

A method and apparatus is provided for a process control based on an estimated process result. The method comprises processing a workpiece using a processing tool, receiving trace data associated with the processing of the workpiece from the processing tool and estimating at least one process result of the workpiece based on at least a portion of the received trace data. The method further comprises adjusting processing of a next workpiece based on the estimated at least one process result.

Process control based on an estimated process result

A method includes collecting a first fabrication parameter associated with the processing of a selected semiconductor device. A second fabrication parameter is estimated for the selected semiconductor device. A first value for at least one electrical characteristic of the selected semiconductor device is predicted based on the collected first fabrication parameter and the estimated second fabrication parameter. A system includes a data collection unit and a prediction unit. The data collection unit is configured to collect a first fabrication parameter associated with the processing of a selected semiconductor device. The prediction unit is configured to estimate a second fabrication parameter for the selected semiconductor device and predict a first value for at least one electrical characteristic of the selected semiconductor device based on the collected first fabrication parameter and the estimated second fabrication parameter.

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Austin, TX, United States of America

Thomas J Sonderman