Advanced Micro Devices Corporation

Michael Lee Miller

Anthony John Toprac

Alexander James Pasadyn

Christopher Allen Bode

Thomas J Sonderman

Anastasia Oshelski Peterson

Joyce S Oey Hewett

Elfido Coss, Jr

Qingsu Wang

William Jarrett Campbell

Terrence J Riley

Brian K Cusson

Michael R Conboy

Richard J Markle

Eric Omar Green

Naomi M Jenkins

Matthew A Purdy

Sam H Allen, Jr

Robert J Chong

Christopher H Raeder

Gregory A Cherry

Jin Wang

Si-Zhao J Qin

Scott Gregory Bushman

Greg Alan Goodwin

Howard Ernest Castle

W Jarrett Campbell

Timothy L Jackson

Patrick M Cowan

Glen W Scheid

Anatasia L Oshelski

Jeff Thompson

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 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 is provided for routing workpieces based upon detecting a fault. The method comprises routing a workpiece to a first processing tool identified by a dispatch system, detecting a fault condition associated with the first processing tool and notifying the dispatch system of the detected fault condition. The method further comprises routing a second workpiece to a second processing tool in response to the dispatch system being notified of the fault condition.

Routing workpieces based upon detecting a fault

A method and apparatus is provided for fault detection spanning multiple processes. The method comprises receiving operational data associated with a first process, receiving operational data associated with a second process, which is downstream to the first process and performing fault detection analysis based on the operational data associated with the first process and second process using a common fault detection unit.

Fault detection spanning multiple processes

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 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 and an apparatus for implementing enhancing data population based upon manufacturing data. A first and a second workpiece are processed. Metrology data relating to the first workpiece is acquired. The metrology data is extrapolated to generate representative metrology data relating to the second workpiece.

Multi-level process data representation

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 and apparatus is provided for selecting control algorithms based on business rules. The method comprises processing a workpiece using a processing tool. The processing tool is capable of processing the workpiece under a control of at least a first and a second control algorithm. The method further comprises detecting an occurrence of an event that affects an operation of the processing tool, selecting at least one of the first and second control algorithm based on detecting the occurrence of the event and processing a workpiece using the processing tool in accordance with the selected control algorithm.

Selecting control algorithms based on business rules

A method and apparatus are provided for determining a next tool state based on fault detection information. The method comprises receiving operational data associated with processing of a workpiece by a processing tool, determining at least a portion of noise associated with the processing of the workpiece based on analyzing the operational data and estimating a next state of the processing tool based on at least the determined portion of the noise.

Determining a next tool state based on fault detection information

A method for distinguishing between sources of process variation includes processing a plurality of manufactured items in a process flow; storing a set of production environment data associated with each of the manufactured items; identifying manufactured items associated with a process drift; generating a plurality of characteristic threads based on the production environment data; comparing the characteristic threads for at least those manufactured items associated with the process drift; and determining at least one potential cause for the process drift based on the comparison of the characteristic threads. A manufacturing system for distinguishing between sources of process variation is also provided. The manufacturing system includes a plurality of tools for processing manufactured items in a process flow, a database server, and a drift monitor.

Method and apparatus for distinguishing between sources of process variation

A method includes receiving incoming fault detection and correction (FDC) data. The incoming FDC data is stored in a real-time database, A first subscriber list designating a first subscriber for at least a portion of the incoming FDC data is provided. The portion of the incoming FDC data designated in the first subscriber list is sent to the first subscriber. A system includes at least one data collection source, a real-time database, and a database management unit. The data collection source is configured to generate incoming fault detection and correction (FDC) data. The database management unit is configured to store the incoming FDC data in the real-time database, provide a first subscriber list designating a first subscriber for at least a portion of the incoming FDC data, and send the portion of the incoming FDC data designated in the first subscriber list to the first subscriber.

Fault detection system with real-time database

A method and system for monitoring a performance of at least one system component of a manufacturing system. At least one event that can occur within the system is defined. It is determined whether the at least one event has occurred within the system, and altering a frequency at which the at least one system component is monitored providing the at least one event has occurred within the system.

Method and apparatus for dynamically monitoring system components in an advanced process control (APC) framework

A method for controlling a manufacturing system includes processing workpieces in a plurality of tools; initiating a baseline control script for a selected tool of the plurality of tools; providing context information for the baseline control script; determining a tool type based on the context information; selecting a group of control routines for the selected tool based on the tool type; determining required control routines from the group of control routines based on the context information; and executing the required control routines to generate control actions for the selected tool. A manufacturing system includes a plurality of tools adapted to process workpieces, a control execution manager, and a control executor. The control execution manager is adapted to initiate a baseline control script for a selected tool of the plurality of tools and provide context information for the baseline control script. The control executor is adapted to execute the baseline control script, determine a tool type based on the context information, select a group of control routines for the selected tool based on the tool type, determine required control routines from the group of control routines based on the context information, and execute the required control routines to generate control actions for the selected tool.

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Cedar Park, TX, United States of America

Michael Lee Miller