Advanced Micro Devices Corporation

Other

Amd Inc.

Christopher Allen Bode

Alexander James Pasadyn

Anthony John Toprac

Thomas J Sonderman

Joyce S Oey Hewett

Michael Lee Miller

Anastasia Oshelski Peterson

Richard David Edwards

Matthew A Purdy

Elfido Coss, Jr

Robert J Chong

Jin Wang

James Broc Stirton

Kevin R Lensing

Richard J Markle

William Jarrett Campbell

Gregory A Cherry

Gary C Jones

Brian K Cusson

Eric Omar Green

Si-Zhao J Qin

Naomi M Jenkins

J Broc Stirton

Qinghua He

Rick Good

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 apparatus is provided for associating operational data with workpieces and correlating the operational data with yield data. The method comprises processing a workpiece using a processing tool, associating the operational data with the workpiece during the processing of the workpiece and measuring the yield data associated with the processed workpiece. The method further comprises correlating the operational data with the yield data to make one or more determinations.

Associating data with workpieces and correlating the data with yield data

A method includes providing a set of initial characteristic values associated with the semiconductor device. A first fabrication process is performed on the semiconductor device. Fabrication data associated with the first fabrication process is collected. At least one of the initial characteristic values is replaced with the fabrication data collected for the first fabrication process to generate a first modified set of characteristic values. A first value for at least one electrical characteristic of the semiconductor device is predicted based on the modified set of characteristic values. A system includes a first process tool, a first data collection unit, and a prediction unit. The first process tool is configured to perform a first fabrication process on the semiconductor device. The first data collection unit is configured to collect fabrication data associated with the first fabrication process. The prediction unit is configured to provide a set of initial characteristic values associated with the semiconductor device, replace at least one of the initial characteristic values with the fabrication data collected for the first fabrication process to generate a first modified set of characteristic values, and predict a first value for at least one electrical characteristic of the semiconductor device based on the modified set of characteristic values.

Method and apparatus for predicting device electrical parameters during fabrication

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

The present invention provides a method and apparatus for dynamic adjustment of a sensor sampling rate. The method includes providing a data collection plan indicative of at least one first sampling rate for at least one sensor associated with at least one processing tool, receiving tool trace data from the at least one sensor via a network, and modifying, based on the tool trace data and a bandwidth associated with the network, the data collection plan to indicate at least one second sampling rate different from a corresponding at least one first sampling rate.

Method and apparatus for dynamic adjustment of a sensor sampling rate

The present invention provides a method and apparatus for integrating multiple sample plans. The method includes receiving a first wafer state data set from an in situ wafer measurement device, the first wafer state data set being indicative of at least one characteristic of at least one wafer processed by a processing tool and receiving a second wafer state data set from an ex situ wafer measurement device, the second wafer state data set being indicative of the at least one characteristic of the at least one wafer processed by the processing tool. The method also includes forming a third wafer state data set using the first and second wafer state data sets and determining the at least one characteristic of the at least one wafer based upon the third wafer state data set.

Method and apparatus for integrating multiple sample plans

The present invention provides a method and apparatus for dynamic adjustment of sensor and/or metrology sensitivities. The method includes accessing measurement information provided by a first measurement device and modifying a sensitivity of a second measurement device based on the measurement information provided by the first measurement device.

Method and apparatus for dynamic adjustment of sensor and/or metrology sensitivities

The present invention provides a method and apparatus for dynamic adjustment of a sampling plan. The method includes accessing wafer electrical test data associated with at least one workpiece that has been processed by at least one processing tool. The method also includes determining, based on the wafer electrical test data, at least one sampling plan for at least one measurement device configured to measure at least one parameter associated with workpieces processed by the at least one processing tool.

Method and apparatus for dynamic adjustment of a sampling plan based on wafer electrical test data

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

The present invention provides a method and apparatus for detecting step and impulse disturbances. The method includes determining a pattern based on a plurality of probabilities associated with a corresponding plurality of wafer processing parameters and determining a type of a disturbance based upon the pattern.

Method and apparatus for fast disturbance detection and classification

A method is provided for manufacturing, the method including processing a workpiece in a processing step, measuring a parameter characteristic of the processing performed on the workpiece in the processing step, and forming an output signal corresponding to the characteristic parameter measured. The method also includes setting a target value for the processing performed in the processing step based on the output signal.

Method for determining optimal photolithography overlay targets based on process performance and yield in microelectronic fabrication

The present invention provides for a method and an apparatus for performing field-to-field compensation during semiconductor manufacturing. At least one semiconductor device is processed. Metrology data is collected from the processed semiconductor device. A field-to-field metrology analysis is performed based upon the metrology data. Residual-error analysis is performed based upon the field-to-field analysis.

Method and apparatus for performing field-to-field compensation

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 and apparatus provided for controlling cumulative wafer effects. The method comprises processing a workpiece, determining a cumulative effect of the processing on the workpiece and comparing the determined cumulative effect to a reference target value. The method further comprises adjusting a downstream process of the workpiece based on comparing the determined cumulative effect to the reference target value.

Controlling cumulative wafer effects

A method includes defining a design window for a manufacturing process performed by a tool and a process window within the design window. A workpiece likely to have a characteristic outside the process window is identified. The characteristic of the identified workpiece is measured. A control model for controlling the tool is updated using the measured characteristic. A system includes a tool, a process controller, a metrology tool, and a sampling controller. The tool is adapted to process workpieces in accordance with a manufacturing process. The manufacturing process has an associated design window and a process window defined within the design window. The process controller is adapted to control the tool using a control model. The sampling controller is adapted to identify a workpiece likely to have a characteristic outside the process window and direct the metrology tool to measure the characteristic of the identified workpiece. The process controller is further adapted to update the control model using the measured characteristic.

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Austin, TX, United States of America

Christopher Allen Bode