W][LLIAMS, MORGAN & AMERSON, P.C.
`I I oo. HOUSTON, TEXAS 77042
`17 I 3> 934-7000
`FAX: 17 l 3l 934-70 l I
`
`I 0333 RICHMOND, STE.
`
`Danny L. Williams
`Terry D. Morgan
`J. Mike Amerson
`Kenneth D. Goodman
`Jeffrey A. Pyle
`Jaison C. John
`Ruben S. Bains
`
`Writer's Direct Dial
`(713} 934-4055
`
`MS PATENT APPLICATION
`Commissioner for Patents
`P.O. Box 1450
`Alexandria, VA 22313-1450
`
`Scott F. Diring*
`Shelley P.M. Fossey, Ph.D.*
`Mark D. Moore, Ph.D.*
`Raymund F. Eich, Ph.D.*
`Daren C. Davis*
`Stephanie A. Wardwell, Ph.D.*
`Mark W. Sincell, Ph.D.*
`
`*Patent Agent
`
`File: 2000.107700/Tf5494
`
`May 1, 2003
`
`CERTIFICATE OI• EXPRESS MAILING UNDER C.F.R. § l.8
`
`EXPRESS MAIL NO.
`
`DA TE OF DEPOSIT:
`
`EV 291 349 099 US
`Ma 1, 2003
`I hereby certify that this paper or fee is being deposited with the United
`States Postal Service with sufficient postage as "EXPRESS MAIL"
`MS PATENT PPLICATION, Commissioner for Patents,
`223
`-1450.
`
`RE:
`
`U.S. Patent Application Entitled: METHOD AND APPARATUS FOR
`FILTERING METROLOGY DATA BASED ON COLLECTION PURPOSE
`James Broe Stirton
`(2000.107700/TT5494)
`
`Sir:
`
`Transmitted herewith for filing are:
`
`(1) 21-page patent specification with 20 claims and an abstract (also Figures 1-2 on 2
`sheets);
`(2) Declaration;
`(3) Power of Attorney;
`( 4) Assignment and Assignment Cover Sheet; and
`(5) Request and Certification Under 35 U.S.C. § 122(b)(2)(B)(i).
`
`All correspondence, notices, official letters and other communications should be directed
`to Scott F. Diring, Williams, Morgan & Amerson, P.C., 10333 Richmond, Suite 1100, Houston,
`TX 77042, and all telephone calls should be directed to Scott F. Diring at (608) 833-0748.
`
`The Assistant Commissioner is authorized to deduct the amount of the total filing
`fee (listed below) from Advanced Micro Devices, Inc. Deposit Account No. 01-0365/TT5494.
`In the event the monies in that account are insufficient, the Assistant Commissioner is authorized
`
`PDF Solutions v Ocean Semiconductor, IPR2022-01196
`PDF Exhibit 1002, Page 1 of 163
`
`

`

`WlILLlAMS, MORGAN & AMERSON, P.C.
`
`Commissioner for Patents
`May 1, 2003
`Page 2
`
`from Williams, Morgan & Amerson, P.C. Deposit Account No.
`to withdraw funds
`50-0786/2000.107700/SFD.
`
`FILING FEE CALCULATION
`
`FOR
`Total Claims
`Independent Claims
`Multiple Dependent Claim(s)
`Basic Fee:
`Assignment Recording Fee:
`TOT AL FILING FEES
`
`20-20
`3 - 3
`
`0
`0
`
`($40 per assignee)
`
`Small Entity
`$
`x$9
`$
`X $42 =
`+ $140 =
`$
`+ $370 =
`$
`+
`$
`$
`
`Large Entity
`or x $18 =
`or x $84 =
`or+ $280 =
`or+ $740 =
`+
`
`0.00
`$
`0.00
`$
`0.00
`$
`$ 740.00
`40.00
`$
`$780.00
`
`0.00
`
`Pursuant to 3 7 C.F .R. § 1.10 the Applicants request the Patent and Trademark Office to
`accept this application and accord a serial number and filing date as of the date this application is
`deposited with the U.S. Postal Service for Express Mail.
`
`Please date stamp and return the enclosed postcards to evidence receipt of these materials.
`
`Respectfully submitted,
`
`Date: May 1, 2003
`
`IIIIIIIIIIIIIIIIIIIIIIIIIII IIIIIIII
`23720
`
`PA TENT TRADEMARK OFFICE
`
`JMA/ym
`Enclosures
`
`cc: Ms. Samantha Cardona (w/enc.)
`
`1 e Amerson
`eg No. 35,426
`IAMS, MORGAN & AMERSON, P.C.
`10333 Richmond, Suite 1100
`Houston, Texas 77042
`(713) 934-7000
`(713) 934-7011 (facsimile)
`ATTORNEY FOR APPLICANT(S
`
`PDF Solutions v Ocean Semiconductor, IPR2022-01196
`PDF Exhibit 1002, Page 2 of 163
`
`

`

`PTO/SB/35 (l l-00}
`Approved for use through I 0/3 l /2002. 0MB 0651-0031
`U.S. Patent and Trademark Office; U.S. DEPARTMENT OF COMMERCE
`Under the Paperwork Reduction Act of 1995, no persons arc required to respond to a collection of information unless it displays a valid 0MB control number.
`First Named Inventor: JAMES BROC STIRTON
`REQUEST AND CERTIFICATION
`UNDER
`35 U.S.C. 122{b)(2)(B)(i)
`
`Title: METHOD AND APPARATUS FOR
`FILTERING METROLOGY DATA BASED ON
`COLLECTION PURPOSE
`
`Attorney Docket Number: 2000.107700fIT5494
`
`I hereby certify that the invention disclosed in the attached application has not and will not be
`the subject of an application filed in another country, or under a multilateral agreement, that
`I hereby request that the attached
`requires publication at eighteen months after filing.
`application npt be published under 35 U.S.C. 122(b).
`
`Date: May I, 2003
`
`Signature
`
`J Mike Amerson
`Typed or printed name
`
`This request must be signed in compliance with 37 CFR l.33(b) and submitted with the
`application upon filing.
`
`Applicant may rescind this nonpublication request at any time. If applicant rescinds a request
`that an application not be published under 35 U.S.C. ·122(b), the application will be scheduled
`for publication at eighteen months from the earliest claimed filing date for which a benefit is
`claimed.
`
`If applicant subsequently files an application directed to the invention disclosed in the attached
`application in another country, or under a multilateral international agreement, that requires
`publication of applications eighteen months after filing, the applicant must notify the United
`States Patent and Trademark Office of such filing within forty-five (45) days after the date of
`the filing of such foreign or international application. Failure to do so will result in
`abandonment of this application (35 U.S.C. 122(b )(2)(B)(iii).
`
`Burden Hour Statement: This collection of information is required by 37 CFR l.213(a). The information is used by the public to request that an
`application not be published under 35 U.S.C. 122(b) (and the PTO to process that request). Confidentiality is governed by 35 U.S.C. 122 and 37
`CFR 1.14. This form is estimated to take 6 minutes to complete. This time will vary depending upon the needs of the individual case. Any
`comments on the amount of time you are required to complete this form should be sent to the Chief Information Officer, U.S. Patent and
`Trademark Office, Washington, DC 20231. DO NOT SEND FEES OR COMPLETED FORMS TO THIS ADDRESS. SEND TO: Assistant
`Commissioner for Patents, Washington, DC 20231.
`
`PDF Solutions v Ocean Semiconductor, IPR2022-01196
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`

`.JL 1[]i--1L-il,=-ii:~!~ ·:;~· tf~1 -u:~~: -![]!
`-m -iL]t --~~;-_,[]i ~iL !I~U _::_§:
`2000.107700/DIR
`'IT5494
`
`Application for United States Letters Patent
`
`for
`
`METHOD AND APPARATUS FOR FILTERING METROLOGY DATA
`
`BASED ON COLLECTION PURPOSE
`
`by
`
`James Broe Stirton
`
`CERTIFICATE OF EXPRESS MAILING UNDER C.F.R. § 1.8
`
`EXPRESS MAIL NO.
`
`EV 291 349 099 US
`
`DATE OF DEPOSIT:
`
`May 1,2003
`
`l hereby certify that this paper or fee is being deposited with the United
`States Postal Service with sufficient postage as "EXPRESS MAIL"
`addressed to: MS PATENT APPLICATION, Commissioner for Patents,
`P.O. Box 1450
`xandria, V
`2313-1450.
`
`PDF Solutions v Ocean Semiconductor, IPR2022-01196
`PDF Exhibit 1002, Page 4 of 163
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`

`

`.:-~ll .. l[]i •lt~Ho, ii:~::: :};:' :i!~::11 :iE:!~ ,fi:]t m -~{[]! ·!!;i; J[]I .:}L--2~]t :~tl;
`2000.107700/DIR
`IT5494
`
`METHOD AND APPARATUS FOR FILTERING METROLOGY DATA
`BASED ON COLLECTION PURPOSE
`
`BACKGROUND OF THE INVENTION
`
`5
`
`1. FIELD OF THE INVENTION
`
`This invention relates generally to an industrial process, and, more particularly, to a
`
`method and apparatus for filtering metrology data based on collection purpose in a
`
`semiconductor device manufacturing environment.
`
`2. DESCRIPTION OF THE RELATED ART
`
`10
`
`There is a constant drive within the semiconductor industry to increase the quality,
`
`reliability and throughput of integrated circuit devices, e.g., microprocessors, memory
`
`devices, and the like. This drive is fueled by consumer demands for higher quality computers
`
`and electronic devices that operate more reliably. These demands have resulted in a
`
`continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well
`
`15
`
`as
`
`in
`
`the manufacture of integrated circuit devices
`
`incorporating such
`
`transistors.
`
`Additionally, reducing the defects in the manufacture of the components of a typical
`
`transistor also lowers the overall cost per transistor as well as the cost of integrated circuit
`
`devices incorporating such transistors.
`
`Generally, a set of processing steps is performed on a wafer using a variety of
`
`20
`
`processing tools, including photolithography steppers, etch tools, deposition tools, polishing
`
`tools, rapid thermal processing tools, implantation tools, etc. One technique for improving
`
`the operation of a semiconductor processing line includes using a factory wide control system
`
`to automatically control the operation of the various processing tools. The manufacturing
`
`tools communicate with a manufacturing framework or a network of processing modules.
`
`Page 2 of21
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`.::«.. iC:ri ,iL1i.. ;;-~.::: ::?" '6, i::!~ K:11200ii;~'fub/6lkli :::1:::
`
`Tf5494
`
`Each manufacturing tool is generally connected to an equipment interface. The equipment
`
`interface is connected to a machine interface which facilitates communications between the
`
`manufacturing tool and the manufacturing framework. The machine interface can generally
`
`be part of an advanced process control (APC) system. The APC system initiates a control
`
`5
`
`script based upon a manufacturing model, which can be a software program that
`
`automatically retrieves the data needed to execute a manufacturing process.
`
`Often, semiconductor devices are staged through multiple manufacturing tools for
`
`multiple processes, generating data relating to the quality of the processed semiconductor
`
`devices. Pre-processing and/or post-processing metrology data is collected on a regular basis,
`
`10
`
`generally in accordance with a sampling plan, for process control purposes. The collected
`
`metrology data is used by the process controllers for the tools. Operating recipe parameters
`
`are calculated by the process controllers based on the performance model and the metrology
`
`information to attempt to achieve post-processing results as close to a process target value as
`
`possible. Reducing variation in this manner leads to increased throughput, reduced cost,
`
`15
`
`higher device performance, etc., all of which equate to increased profitability.
`
`Metrology data is also used for other purposes not related to process control. One
`
`such use is for fault detection and classification (FDC). Fault monitors apply FDC
`
`techniques to identify devices or tools with fault conditions. For example, if a particular
`
`device has a critical dimension outside a predetermined range, it is flagged as being defective.
`
`20
`
`The wafer may be reworked, the die may be marked defective, or the wafer may be scrapped,
`
`depending on the magnitude and nature of the fault condition. Process tools may be
`
`monitored during their processing runs. If an anomaly is observed during the processing, the
`
`tool may be shut down for maintenance. The wafers processed by the tool may be flagged for
`
`Page 3 of21
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`.:t 11:J n~1~;i~:'. )'' ii'.:iii it:!: ![ffi 206b~1ij~~~~!bM' :::~s;
`
`TT5494
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`subsequent metrology to determine if the tool anomaly caused a degradation of the devices
`
`formed thereon. Again, the suspect wafers may be reworked or scrapped.
`
`Typically, when a process controller gathers metrology data to update its control
`
`model or generate a control action for subsequent processing, it retrieves metrology data
`
`5
`
`related to wafers processed in the tool or tools under its control and employs that data to
`
`perform its control task. The data retrieved includes metrology data collected through the
`
`regular sampling plans implemented in the facility, and the metrology data collected for other
`
`purposes. Some of the metrology data does not accurately reflect the state of the process or
`
`the devices manufactured. For example, devices processed by a tool that was malfunctioning
`
`10 may have characteristics that were affected by the malfunction (i.e., a special cause) rather
`
`than by normal process variation (i.e., common cause). Employing this data for use in
`
`process control routines may introduce a source of variation that icannot be addressed by. the
`
`process controller and thus reduce the effectiveness of the process controller.
`
`The present invention is directed to overcoming, or at least reducing the effects of,
`
`15
`
`one or more of the problems set forth above.
`
`SUMMARY OF THE INVENTION
`
`One aspect of the present invention is seen in a method for filtering metrology data.
`
`The method includes collecting metrology data related to the processing of workpieces in a
`
`plurality of tools. Context data for the metrology data is generated. The context data
`
`20
`
`includes collection purpose data. The metrology data is filtered based on the collection
`
`purpose data. A process control activity related to one of the tools is conducted based on the
`
`filtered metrology data.
`
`Page 4 of21
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`.:!L il:]l Tl4f~ ii:~!'. ~;;;;i· f.:'.'.il ;;::~1: JE!~db&i tti;,Jtd:dP :;~~;
`TI5494
`
`Another aspect of the present invention is seen in a system including at least one
`
`metrology tool, a computer, and a process controller. The metrology tool is configured to
`
`collect metrology data related to the processing of workpieces in a plurality of tools. The
`
`computer is configured to generate context data for the metrology data, the context data
`
`5
`
`including collection purpose data. The process controller is configured to filter the metrology
`
`data based on the collection purpose data and conduct a process control activity related to one
`
`of the tools based on the filtered metrology data.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`The invention may be understood by reference to the following description taken in
`
`10
`
`conjunction with the accompanying drawings, in which like reference numerals identify like
`
`elements, and in which:
`
`Figure 1 is a simplified block diagram of a manufacturing system in accordance with
`
`one embodiment of the present invention; and
`
`Figure 2 is a simplified flow diagram of a method for filtering metrology data in
`
`15
`
`accordance with another embodiment of the present invention.
`
`While the invention is susceptible to various modifications and alternative forms,
`
`specific embodiments thereof have been shown by way of example in the drawings and are
`
`herein described in detail. It should be understood, however, that the description herein of
`
`specific embodiments is not intended to limit the invention to the particular forms disclosed,
`
`20
`
`but on the contrary, the intention is to cover all modifications, equivalents, and alternatives
`
`falling within the spirit and scope of the invention as defined by the appended claims.
`
`Page 5 of21
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`i!i (]I'~~ {]i :il. i[:fi ::~:!;
`.:3t.-·n::~ it4f,,i~::~ :;;w ,n:;~1-~n:;~ ll~::U
`2000.107700/DIR
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`
`DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS
`
`Illustrative embodiments of the invention are described below.
`
`In the interest of
`
`clarity, not all features of an actual implementation are described in this specification. It will
`
`of course be appreciated that in the development of any such actual embodiment, numerous
`
`5
`
`implementation-specific decisions must be made to achieve the developers' specific goals,
`
`such as compliance with system-related and business-related constraints, which will vary
`
`from one implementation to another. Moreover, it will be appreciated that such a
`
`development effort might be complex and time-consuming, but would nevertheless be a
`
`routine undertaking for those of ordinary skill in the art having the benefit of this disclosure.
`
`10
`
`Referring to Figure 1, a simplified block diagram of an illustrative manufacturing
`
`system 10 is provided.
`
`In the illustrated embodiment, the manufacturing system 10 is
`
`adapted to fabricate semiconductor devices. Although the invention is described as it may be
`
`implemented in a semiconductor fabrication facility, the invention is not so limited and may
`
`be applied to other manufacturing environments. The techniques described herein may be
`
`15
`
`applied to a variety of workpieces or manufactured items, including, but not limited to,
`
`microprocessors, memory devices, digital signal processors, application specific integrated
`
`circuits (ASICs), or other devices. The techniques may also be applied to workpieces or
`
`manufactured items other than semiconductor devices.
`
`A network 20 interconnects various components of the manufacturing system 10,
`
`20
`
`allowing them to exchange information. The illustrative manufacturing system 10 includes a
`
`plurality of tools _30-80. Each of the tools 30-80 may be coupled to a computer (not shown)
`
`for interfacing with the network 20. The tools 30-80 are grouped into sets of like tools, as
`
`denoted by lettered suffixes. For example, the set of tools 30A-30C represent tools of a
`
`certain type, such as a chemical mechanical planarization tool. A particular wafer or lot of
`
`Page 6 of21
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`2000.107700/DIR
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`wafers progresses through the tools 30-80 as it is being manufactured, with each tool 30-80
`
`performing a specific function in the process flow. Exemplary processing tools for a
`
`semiconductor device fabrication environment include photolithography steppers, etch tools,
`
`deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc.
`
`5
`
`Exemplary metrology
`
`tools
`
`include
`
`thickness metrology
`
`tools, scanning electron
`
`microscopes, optical metrology tools, electrical measurement tools, etc. The tools 30-80 are
`
`illustrated in a rank and file grouping for illustrative purposes only.
`
`In an actual
`
`implementation, the tools 30-80 may be arranged in any physical order or grouping.
`
`Additionally, the connections between the tools in a particular grouping are meant to
`
`10
`
`1 represent connections to the network 20, rather than interconnections between the tools 30-
`
`80.
`
`Portions of the invention and corresponding detailed description are presented .in
`
`terms of software, or algorithms and symbolic representations of operations on data bits
`
`within a computer memory. These descriptions and representations are the ones by which
`
`15
`
`those of ordinary skill in the art effectively convey the substance of their work to others of
`
`ordinary skill in the art. An algorithm, as the term is used here, and as it is used generally, is
`
`conceived to be a self-consistent sequence of steps leading to a desired result. The steps are
`
`those requiring physical manipulations of physical quantities. Usually, though not
`
`necessarily, these quantities take the form of optical, electrical, or magnetic signals capable of
`
`20
`
`being stored, transferred, combined, compared, and otherwise manipulated. It has proven
`
`hese signals as bits,
`
`1t
`
`convenient at times, principally for reasons of common usage, to refer to
`
`values, elements, symbols, characters, terms, numbers, or the like.
`
`It should be borne in mind, however, that all of these and similar terms are to be
`
`associated with the appropriate physical quantities and are merely convenient labels applied
`
`Page 7 of21
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`

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`TTS494
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`to these quantities. Unless specifically stated otherwise, or as is apparent from the
`
`discussion, terms such as "processing" or "computing" or "calculating" or "determining" or
`
`"displaying" or the like, refer to the action and processes of a computer system, or similar
`
`electronic computing device, that manipulates and transforms data represented as physical,
`
`5
`
`electronic quantities within the computer system's registers and memories into other data
`
`similarly represented as physical quantities within the computer system memories or registers
`
`or other such information storage, transmission or display devices.
`
`An exemplary information exchange and process control framework suitable for use
`
`in the manufacturing system 10 is an Advanced Process Control (APC) framework, such as
`
`10 may be implemented using the Catalyst system offered by KLA-Tencor, Inc. The Catalyst
`
`system uses Semiconductor Equipment and Materials International (SEMI) Computer
`
`Integrated Manufacturing (CIM) Framework compliant system technologies and is based. the
`
`Advanced Process Control (APC) Framework. CIM (SEMI E81-0699 - Provisional
`
`Specification for CIM Framework Domain Architecture) and APC (SEMI E93-0999 -
`
`15
`
`Provisional Specification for CIM Framework Advanced Process Control Component)
`
`specifications are publicly available from SEMI, which is headquartered in Mountain View,
`
`CA.
`
`A manufacturing execution system (MES) server 90 directs the high level operation of
`
`the manufacturing system 10. The MES server 90 monitors the status of the various entities
`
`20
`
`in the manufacturing system 10 (i.e., lots, tools 30-80) and controls the flow of articles of
`
`manufacture (e.g., lots of semiconductor wafers) through the process flow. A database server
`
`100 may be provided for storing data related to the status of the various entities and articles
`
`of manufacture in the process flow. The database server 100 may store information in one or
`
`Page 8 of21
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`2000.107700/DIR
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`
`more data stores 110. The data may include pre-process and post-process metrology data,
`
`tool states, lot priorities, etc.
`
`The processing and data storage functions are distributed amongst the different
`
`computers or workstations in Figure 1 to provide general independence and central
`
`5
`
`information storage. Of course, different numbers of computers and different arrangements
`
`may be used without departing from the spirit and scope of the instant invention.
`
`Process controllers 120 may be associated with one or more of the process tools 30-
`
`80. The process controllers 120 determine control actions for controlling selected ones of the
`
`tools 30-80 serving as process tools based on metrology data collected during the fabrication
`
`10
`
`of wafers (i.e., by others of the tools 30-80 serving as metrology tools). The particular
`
`control models used by the process controllers 120 depend on the type of process tool 30-80
`
`being controlled, and the particular metrology data collected for use in conjunction with the
`
`control models depends on the feature being formed by the particular process tool 30-80. The
`
`control models may be developed empirically using commonly known linear or non-linear
`
`15
`
`techniques. The control models may be relatively simple equation-based models (e.g., linear,
`
`exponential, weighted average, etc.) or a more complex model, such as a neural network
`
`model, principal component analysis (PCA) model, partial least squares projection to latent
`
`structures (PLS) model. The specific implementation of the control models may vary
`
`depending on the modeling techniques selected and the process being controlled. The
`
`20
`
`selection and development of the particular control models would be within the ability of one
`
`of ordinary skill in the art, and accordingly, the control models are not described in greater
`
`detail herein for clarity and to avoid obscuring the instant invention.
`
`An exemplary process control scenario involves the control of a gate electrode critical
`
`dimension (CD) in a transistor structure. Various processes and process variables may be
`
`Page 9 of21
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`2000.107700/DIR
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`
`controlled to affect the gate electrode CD. For example, a photoresist mask is used to pattern
`
`the gate electrode. The photolithography processes used to form the mask may affect the
`
`dimensions of the pattern and thus the dimensions of the gate electrode formed by an etch
`
`process using the mask. Exposure time and energy may be controlled to affect the
`
`5
`
`dimensions of the mask. The parameters (e.g., etch time, plasma power, etch gas makeup and
`
`concentration, etc.) of the etch process may also affect the CD of the completed gate
`
`electrode and may be controlled by a process controller 120. The processes and variables
`
`described above that affect the gate electrode CD are not exhaustive. Other processes may be
`
`pedormed that have an impact of the CD and other variables of those processes may be
`
`10
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`controlled.
`
`In some embodiments, a fault monitor 130 executing on a workstation 135 may be
`
`provided for monitoring fault conditions with the tools 30-80 and/or devices manufactured.
`
`For example, a particular tool 30-80 may be performing poorly or feature formed on a device
`
`may have a dimension outside an acceptable range of values. The fault monitor 130 may
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`15
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`implement one or more fault detection and classification (FDC) models to evaluate the
`
`condition of the various entities or devices. Metrology data is employed by the fault monitor
`
`130 to identify fault conditions with various tools 30-80 or workpieces and also to update the
`
`FDC model(s) employed to identify the degraded conditions. The fault monitor 130 may use
`
`the metrology data collected for process control purposes to perform its defect analysis. , For
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`20
`
`example, metrology data collected during a photolithography process for forming the gate
`
`electrode etch mask may be used to control the photolithography tool 30-80. The fault
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`monitor 130 may also review the data to determine if the dimensions of the mask are within
`
`acceptable limits. If the mask dimensions are outside the acceptable range, the photoresist
`
`layer may be removed and the wafer reworked to form a new photoresist layer.
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`2000.107700/DIR
`TI5494
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`In other cases, the fault monitor 130 may target certain tools 30-80 or wafers for fault
`
`analysis and issue its own metrology requests for data related to the targeted tool 30-80 or
`
`wafer. For example, if a particular tool parameter is outside a range of expected values
`
`during a processing run, wafers processed during that run may be targeted for metrology to
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`5
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`determine if the parameter excursion introduced a defect in the processed device. The fault
`
`monitor 130 may also initiate metrology events in cases where the probability of defect is
`
`higher than a baseline probability. For example, if a process is known to produce a higher
`
`defect rate on a particular region of wafer (e.g., the periphery region), the fault monitor 130
`
`may request that additional metrology data be collected for that .particular region.
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`10
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`The MES server 90 may receive requests from various consumers to collect
`
`metrology data. These consumers may be fault detection entities or process control entities,
`
`for example. The metrology tool (e.g., one of the tool 30-80) collects the metrology data and
`
`the data is stored in the data store 110. The metrology data may be stored directly by the
`
`metrology tool 30-80 or the data may be returned to the MES server 90 for storage. The
`
`15 metrology data is stored also with associated context data that includes identification data and
`
`collection purpose data.
`
`Exemplary identification data includes lot identification number (ID), wafer ID,
`
`location data (e.g., location of measurement on die or wafer), process-operation data (e.g.,
`
`last completed step in the fabrication process), etc. The collection purpose data indicates the
`
`20
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`initial purpose for the collection of the metrology data. For example, the purpose may be
`
`process control sampling, fault detection sampling, targeted fault detection, etc.
`
`In one illustrative embodiment of the present invention, the collection purpose data is
`
`used to filter the metrology data for subsequent uses. For example, a process controller 120
`
`would conventionally employ all metrology data for a particular tool 30-80 and process-
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`.:it tJ 1LJ! .. ii::!: :;r· 61 ,i'i:'.'.: riooo~t\~d1ahii-J::il ·:~:It
`
`TIS494
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`operation for updating the states of its control model and generating a control action for
`
`modifying an operating recipe parameter for the tool 30-80. By using the collection purpose
`
`data to filter the metrology data, metrology data collected for fault detection purposes, where
`
`the likelihood of a fault being present is higher, can be excluded. Filtering the metrology data
`
`5
`
`in this manner may improve the performance of the process controller 120 by removing
`
`outlier data that exhibits variation from a source other than normal process variation. If the
`
`process controller 120 were to act on metrology data that included special causes of variation
`
`(e.g., tool faults), it would attempt to shift the process in a direction that might actually
`
`increase variation and reduce the stability of the process.
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`10
`
`In some cases, metrology data collected for process control purposes may also be used
`
`in fault detection. The MES server 90 would initially indicate that the collection purpose
`
`would be process control sampling. However, if the metrology data was later used in a fault
`
`detection analysis and the wafer was determined to be faulty, the MES server 90 or fault
`
`monitor 130 may change the collection purpose such that the metrology data would be
`
`15
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`filtered out for subsequent process control activities. For example, the MES server 90 may
`
`set the collection purpose data to a value indicating a known faulty wafer. However, if the
`
`metrology data indicated a fault condition that could be tracked back to a process variation
`
`cause, the metrology data may still be useful for process control purposes and the MES server
`
`may leave the collection purpose data unchanged.
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`20
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`Some fault detection sampling data may also be randomly collected. In such cases, a
`
`defect condition is not suspected, and the data is used for process oversight. Hence, it may be
`
`possible that the data collected for fault detection purposes may still be useful for process
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`control.
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`In these cases, where the initial purpose was fault detection, but no defect was
`
`identified, the MES server 90 or fault monitor 130 may change the collection purpose data to
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`a value indicating this condition, such that the metrology data so collected could still be used
`
`for process control purposes.
`
`Table 1 below lists exemplary collection purpose codes that may be stored with the
`
`collected metrology data. The list is intended to be illustrative and not exhaustive or limiting
`
`5
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`to the application of the present invention.
`
`CPCode Collection Purpose
`
`01
`
`02
`
`03
`
`88
`
`99
`
`Process Control Sampling
`
`Fault Detection Sampling
`
`Targeted Fault Detection
`
`Fault Detection - no fault identified
`
`Known Defective
`
`Table 1 - Collection Purpose Codes
`
`The following examples illustrate the use of the collection purpose codes for filtering
`
`the metrology data. Process control data is collected in accordance with a sampling plan
`
`implemented by the MES server 90 or other sampling controller (not shown). The collection
`
`10
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`purpose code for this data is set at "01." The fault monitor 130 requests metrology data for
`
`random FDC oversight. The collection purpose code for this data is set at "02." The fault
`
`monitor 130 may also use the "01" data for FDC oversight. In some cases the fault monitor
`
`130 may identify that a particular tool parameter was outside expected limits during a
`
`processing run or that the health of a particular tool 30-80 has degraded to a level indicating a
`
`15
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`need for maintenance or troubleshooting. The fault monitor 130 may request additional
`
`metrology data be collected