Advanced Micro Devices Corporation

Globalfoundries Inc.

Other

Advances Micro Devices, Inc.

Alexander James Pasadyn

Christopher Allen Bode

Thomas J Sonderman

Anthony John Toprac

Joyce S Oey Hewett

Michael Lee Miller

Anastasia Oshelski Peterson

Robert J Chong

Brian K Cusson

Elfido Coss, Jr

Matthew A Purdy

Jin Wang

Naomi M Jenkins

Richard J Markle

James Broc Stirton

Christopher H Raeder

Eric Omar Green

Gregory A Cherry

Si-Zhao J Qin

Ernest Dean Adams, Iii

Howard Ernest Castle

Patrick M Cowan

Timothy L Jackson

Joyce S Obey Hewett

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

A method and an apparatus for processing semiconductor wafer based upon end-of-line (EOL) parameters. A target end-of-line parameter relating to a semiconductor wafer is determined. An inline parameter relating to processing of the semiconductor wafer is controlled in response to the target end-of-line parameter using a controller. Controlling the inline parameter includes adjusting a target inline parameter that correlates to the inline parameter.

Controlling processing of semiconductor wafers based upon end of line parameters

A method and apparatus are provided for initiating test runs based on a fault detection result. The method comprises receiving operational data associated with processing of a workpiece by a processing tool, processing the operational data to determine fault detection results; and causing a test run to be performed based on at least a portion of the fault detection results.

Initiating test runs based on fault detection results

A method and an apparatus are provided for applying a self-adaptive filter to a drifting process. The method includes processing a workpiece, measuring an output characteristic of the processed workpiece and modifying a previous estimated process state based at least on the measured output characteristic. The method further includes estimating a next process state based at least on the modified previous estimated process state.

Applying a self-adaptive filter to a drifting process

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 process includes determining incoming state information associated with the process. A plurality of control models associated with the process is provided. A confidence metric is determined for each of the control models based on the incoming state information. The one of the plurality of control models having the highest associated confidence metric is selected. A control action for determining at least one parameter in an operating recipe used to implement the process is generated using the selected control model. A system includes a process tool and a process controller. The process tool is configured to process a workpiece in accordance with an operating recipe. The process controller is configured to determine incoming state information associated with processing the workpiece, determine a confidence metric for each of a plurality of control models based on the incoming state information, select the one of the plurality of control models having the highest associated confidence metric, and generate a control action for determining at least one parameter in the operating recipe using the selected control model.

Method and apparatus for implementing competing control models

A method is provided, the method comprising sampling at least one parameter characteristic of processing performed on a workpiece in at least one processing step, and modeling the at least one characteristic parameter sampled using an adaptive sampling processing model, treating sampling as an integrated part of a dynamic control environment, varying the sampling based upon at least one of situational information, upstream events and requirements of run-to-run controllers. The method also comprises applying the adaptive sampling processing model to modify the processing performed in the at least one processing step.

Adaptive sampling method for improved control in semiconductor manufacturing

A method and an apparatus for matching data related to an integrated metrology tool and a standalone metrology tool. At least one semiconductor wafer is processed. An integrated metrology tool and/or a standalone metrology tool is matched based upon a difference between metrology data relating to a processed semiconductor wafer acquired by the integrated metrology tool and metrology data acquired by the standalone metrology tool, using a controller.

Matching data related to multiple metrology tools

A method of controlling a conductive layer deposition process includes depositing a conductive layer onto a semiconductor wafer based upon a deposition recipe, measuring a thickness of the conductive layer deposited on the semiconductor wafer, determining whether the measured thickness of the conductive layer is within a predetermined tolerance, and revising the deposition recipe if the thickness of the conductive layer is not within the predetermined tolerance. An apparatus includes a deposition unit capable of depositing a conductive layer according to a deposition recipe; a thickness measuring unit capable of measuring at least one thickness of the conductive layer and outputting thickness data; and a deposition control unit capable of receiving the thickness data from the thickness measuring unit, determining whether the thickness data is within a predetermined tolerance, revising the deposition recipe if the thickness data is not within the predetermined tolerance, and outputting the revised deposition recipe.

Method and apparatus for controlling a thickness of a conductive layer in a semiconductor manufacturing operation

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 for dispatching based on metrology tool performance includes determining a precision metric associated with each of a plurality of metrology tools. A metrology request including context information is generated. A precision requirement for the metrology request is identified based on the context information. A set of the metrology tools capable of satisfying the metrology request is identified based on the precision requirement and the precision metrics. A manufacturing system includes a manufacturing execution system server and a metrology monitor. The manufacturing execution system server is configured to generate a metrology request including context information. The metrology monitor is configured to determine a precision metric associated with each of a plurality of metrology tools, identify a precision requirement for the metrology request based on the context information, and identify a set of the metrology tools capable of satisfying the metrology request based on the precision requirement and the precision metrics.

Method and apparatus for dispatching based on metrology tool performance

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.

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Austin, TX, United States of America

Alexander James Pasadyn