Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 1 of 26 PageID #: 235
`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 1 of 26 PageID #: 235
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`EXHIBIT J
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`EXHIBIT J
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 2 of 26 PageID #: 236
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`Analysis of Infringement of U.S. Patent No. 6,725,402 by Huawei Device USA Inc., Huawei Device Co., Ltd., and HiSilicon Technologies Co., Ltd.
` (Based on Public Information Only)
`
`Plaintiff Ocean Semiconductor LLC (“Ocean Semiconductor”), provides this preliminary and exemplary infringement analysis with respect to
`
`infringement of U.S. Patent No. 6,725,402, entitled “METHOD AND APPARATUS FOR FAULT DETECTION OF A PROCESSING TOOL AND
`CONTROL THEREOF USING AN ADVANCED PROCESS CONTROL (APC) FRAMEWORK” (the “’402 patent”) by Huawei Device USA Inc., Huawei
`Device Co., Ltd., and HiSilicon Technologies Co., Ltd. (“Huawei”). The following chart illustrates an exemplary analysis regarding infringement by Defendant
`Huawei’s semiconductor products, systems, devices, components, and integrated circuits, and products containing such circuits, fabricated or manufactured
`using PDF Solutions, Inc.’s (“PDF Solutions”) platforms, and/or framework, including PDF Solutions’ software and APC system, including the Exensio
`platform hardware and/or software (collectively, “Exensio”) and/or other APC system and platform hardware and/or software. Such products include, without
`limitation, SoC chipsets and solutions (e.g., Hi3559A V100, Hi3519A V100, Hi3516D V300, Hi3556A V100, Hi3559 V200, Hi3559A V100, Hi3559C V100,
`Hi3559 V100, Hi3716M V430, Hi3716M V430, Hi3798C V200, Hi3798M V200H, Hi3798M V300, Hi3798M V310, Hi3796M V200, Hi3798M V200,
`Hi3796M V100, Hi3798M V100, Hi3716M V420, Hi3716M V410, and Hi3751 V553), processors (e.g., Hi3536, Hi3536C, Hi3536D V100, Hi3531D V100,
`Hi3521D V100, Hi3520D V400, Hi3520D V300, and Hi3520D V200), TV solutions (e.g., Hi3731 V201, Hi3731 V101, Hi3751 V811, HI3751 V810, Hi3751
`V551, Hi3751 V730, Hi3751 V620, Hi3751 V510, Hi3751 V310, Hi3751 V320, and Hi3751 V600), Kirin solutions (e.g., Kirin 9000/E, Kirin 1020, Kirin 990,
`Kirin 980, Kirin 970, Kirin 960, Kirin 950, Kirin 930, Kirin 920, Kirin 910, and Kirin 710); Ascend solutions (e.g., Ascend 310 and Ascend 910); Kunpeng
`solutions (e.g., Kunpeng 920); and Balong solutions (e.g., Balong 5000, Balong 5G01, Balong 765, Balong 750, Balong 720, Balong 710, and Balong 700),
`systems, products, or devices containing these solutions, and similar systems, products, devices, and integrated circuits (collectively, the “’402 Infringing
`Instrumentalities”).
`
`The analysis set forth below is based only upon information from publicly available resources regarding the ’402 Infringing Instrumentalities, as
`Huawei has not yet provided any non-public information.
`
`Unless otherwise noted, Ocean Semiconductor contends that Huawei directly infringes the ’402 patent in violation of 35 U.S.C. § 271(g) by using,
`
`selling, and/or offering to sell in the United States, and/or importing into the United States, the ’402 Infringing Instrumentalities. The following exemplary
`analysis demonstrates that infringement. Unless otherwise noted, Ocean Semiconductor further contends that the evidence below supports a finding of indirect
`infringement under 35 U.S.C. § 271(b) in conjunction with other evidence of liability.
`
`Unless otherwise noted, Ocean Semiconductor believes and contends that each element of each claim asserted herein is literally met through Huawei’s
`
`provision or importation of the ’402 Infringing Instrumentalities. However, to the extent that Huawei attempts to allege that any asserted claim element is not
`literally met, Ocean Semiconductor believes and contends that such elements are met under the doctrine of equivalents. More specifically, in its investigation
`and analysis of the ’402 Infringing Instrumentalities, Ocean Semiconductor did not identify any substantial differences between the elements of the patent
`claims and the corresponding features of the Infringing Instrumentalities, as set forth herein. In each instance, the identified feature of the ’402 Infringing
`
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`Instrumentalities performs at least substantially the same function in substantially the same way to achieve substantially the same result as the corresponding
`claim element.
`
`Ocean Semiconductor notes that the present claim chart and analysis are necessarily preliminary in that Ocean Semiconductor has not obtained
`substantial discovery from Huawei nor has Huawei disclosed any detailed analysis for its non-infringement position, if any. Further, Ocean Semiconductor
`does not have the benefit of claim construction or expert discovery. Ocean Semiconductor reserves the right to supplement and/or amend the positions taken in
`this preliminary and exemplary infringement analysis, including with respect to literal infringement and infringement under the doctrine of equivalents, if and
`when warranted by further information obtained by Ocean Semiconductor, including but not limited to information adduced through information exchanges
`between the parties, fact discovery, claim construction, expert discovery, and/or further analysis.
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 4 of 26 PageID #: 238
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`
`
`
`
`USP No. 6,725,402
`
`1. A method comprising:
`receiving at a first interface
`operational state data of a
`processing tool related to the
`manufacture of a processing
`piece;
`
`Infringement by the ’402 Accused Instrumentalities
`
`PDF Solutions Inc.’s (“PDF”) Exensio platform (“Exensio System”) receives at a first interface operational state data of
`a processing tool related to the manufacture of a processing piece.
`
`For example, the Exensio System includes a first interface (e.g., platform modules including the control module (to
`detect and identify process or tool problems in fab and assembly in real time), the char module (to provide big data
`analytics on processing tools), and the ALPS module (to trace wafers, dies, and multichip modules)):
`
`
`
`See PDF Solutions, Inc. Overview Jefferies Conferences (Aug. 28-29, 2018) at 9, available at
`https://www.pdf.com/upload/File/Investors/PDFExecOveriew2018II.pdf (last visited Oct. 12, 2020) (“PDF Overview”)
`(annotated).
`
`
`
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`The operational state data of a processing tool related to the manufacture of a processing piece received at the first
`interface can include data from integrated circuit design, fabrication, and sorting to assembly, testing, and system
`control:
`
`
`
`
`
`See PDF Solutions, Inc. Overview Jefferies Conferences (Aug. 28-29, 2018) at 5, available at
`https://www.pdf.com/upload/File/Investors/PDFExecOveriew2018II.pdf (last visited Oct. 12, 2020) (“PDF Overview”)
`(annotated).
`
`The operational state data of a processing tool related to the manufacture of a processing piece received at the first
`interface can also include data associated with multi-chip module (“MCM”) components and consumables that identify
`where a particular die is in a package, whether a particular die is wire-bonded or laser-marked, and what the device ID
`is for a particular chipset, etc.:
`
`
`
`
`4
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`
`
`See PDF Solutions, “Cognitive End to End Analytics for Semiconductor Manufacturing: A Smart Testing Application”
`(Oct. 30, 2019) at 13, available at http://liralingerie.com/nldfpd/end-to-end-analytics.html (last visited Oct. 12, 2020)
`(“Cognitive End to End Analytics Presentation”).
`
`The operational state data can cover process control, test operations, manufacturing analytics, assembly operations, and
`process characterization:
`
`
`
`
`
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`5
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 7 of 26 PageID #: 241
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`
`
`
`See S1.2—Exensio Platform, 16th Annual PDF Solutions Users Conference (Oct. 15, 2019) at 3, available at
`http://www.pdf.com/upload/File/Investors/PUG2019/S1.2%20PUG2019_ExensioPlatform_SaidAkar.pdf (“S1.2—
`Exensio Platform Presentation”) (last visited Oct. 12, 2020) (annotated).
`
`
`The operational state data can also include data associated with the rule ensemble engine, spatial signature analysis, fail
`signature detection and analysis, product sensitivity analysis, parameter screening report, indicator screening report,
`and automatic spatial classification, all of which are related to the manufacture of a processing piece:
`
`
`
`
`6
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`
`
`
`
`See S1.3— Machine Learning in Exensio, 16th Annual PDF Solutions Users Conference (Oct. 15, 2019) at 21,
`available at http://www.pdf.com/upload/File/Investors/PUG2019/S1.3%20PUG2019_AISolutions_JeffDavid.pdf
`(“S1.3—Machine Learning in Exensio”) (last visited Oct. 12, 2020).
`
`The operational state data of a processing tool related to the manufacture of a processing piece can also include the
`following:
`
`
`• Material descriptions (e.g., lot #, wafer #, die);
`• Meta data (e.g., recipe data/time, process flow, stages, and steps);
`• Fault detection and control (e.g., trace charts, model prediction, real time data collection on defects);
`• Defect & metrology (e.g., lot/wafer summaries, defect summary, kill ratio, and defect images); and
`• Assembly system (e.g., location of reel/tube, die traceability, and equipment parameters):
`
`
`
`
`
`7
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 9 of 26 PageID #: 243
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`sending the state data
`from the first interface to a
`fault detection unit, wherein
`the act of sending comprises:
`sending the state data from
`the first interface to a data
`collection unit;
`
`
`See S1.2—Exensio Platform Presentation at 11 (annotated).
`
`
`
`
`PDF’s Exensio System sends the state data from the first interface to a fault detection unit, wherein the act of sending
`comprises sending the state data from the first interface to a data collection unit.
`
`For example, the Exensio System includes a centralized database as a data collection unit that receives the state data:
`
`“The Exensio database integrates, organizes, consolidates, aligns and tracks data from all process and testing data
`sources. This drives fast, efficient data analysis, correlation between data sources and drill-down to tool and test data.
`The database genealogy fully supports lot, wafer and die level traceability from wafer start to multi-chip packaged
`product.”
`
`See PDF Solution’s The Complete Semiconductor Data Platform, available at http://pdf.com/exensio-old (last visited
`Oct. 12, 2020).
`
`This centralized database can also be used as a data collection unit to store fault detection and classification data:
`
`“… Dedicated centralized database — Exensio –Control provides solutions fitted to FDC requirements. The entire fab's
`FDC data can be stored in one single location, enabling further analyses such as trend analysis or yield excursion root-
`cause analysis. … ”
`
`
`
`8
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`
`
`See Exensio Control, available at http://www.pdf.com/Exensio-Control (last visited Oct. 12, 2020):
`
`As another example, the Exensio System includes a “unified” database that receives the state data:
`
`
`
`See Cognitive End to End Analytics Presentation at 9.
`
`The data collection unit also can reside in Exensio’s Design-for-Inspection (“DFI”) system on the cloud:
`
`
`
`
`
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`9
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`
`
`See S1.2—Exensio Platform Presentation at 4 (annotated).
`
`
`accumulating the state data at The data collection unit of the Exensio System accumulates the state data at the data collection unit.
`the data collection unit;
`
`For example, the state data can be accumulated at the Exensio database, the dedicated centralized database, or in a
`“cloud” database. See above.
`
`As another example, through on-premise subscription of Software-as-a-Service, the Exensio System accumulates the
`state data from users, tool connections, and PDF machines and store them on the accused system:
`
`
`
`
`
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`10
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`
`
`
`
`See Kibarian et al., PDF Solutions, Inc. Needham Growth Conference (Jan. 16, 2019) at 12, available at
`https://www.pdf.com/upload/File/Investors/INVPres2019/PDFS%20investor%20presentation%2016-Jan-
`2019%20(final).pdf (last visited Oct. 12, 2020) (“PDF Needham Conference Presentation”).
`
`
`As another example, the state data can be accumulated at a dedicated centralized data configured to store FDC-related
`state data:
`
`“Exensio –Control is a scalable Fault Detection and Classification (FDC) software solution that controls semiconductor
`manufacturing equipment and processes. Exensio-Control allows manufacturers to accurately detect and identify
`process or tool problems that arise during production, in real-time.
`…
`
`• Dedicated centralized database — Exensio –Control provides solutions fitted to FDC requirements. The entire
`fab's FDC data can be stored in one single location, enabling further analyses such as trend analysis or yield
`excursion root-cause analysis. …”
`
`
`See Exensio Control, available at http://www.pdf.com/Exensio-Control (last visited Oct. 12, 2020).
`
`
`
`
`
`11
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 13 of 26 PageID #: 247
`
`translating the state data
`from a first communications
`protocol to a second
`communications protocol
`compatible with the fault
`detection unit;
`
`PDF’s Exensio System translates the state data from a first communications protocol to a second communications
`protocol compatible with the fault detection unit.
`
`As an example, the Exensio System translates the state data from a first communications protocol to a second
`communications protocol compatible with the fault detection unit as part of the “signal transformation and
`summarization process” such that it can acquires “all the equipment and logistics data for FDC analysis, in any format
`and from any source”:
`
`“Exensio –Control is a scalable Fault Detection and Classification (FDC) software solution that controls semiconductor
`manufacturing equipment and processes. Exensio-Control allows manufacturers to accurately detect and identify
`process or tool problems that arise during production, in real-time.
`
`
`• Wide data acquisition capabilities — Exensio –Control acquires all the equipment and logistics data for FDC
`analysis, in any format and from any source (Interface A, databases, SECS/HSMS, automation, files, etc.)
`• Advanced analysis capabilities — Exensio –Control includes signal transformation and summarization,
`univariate SPC, multivariate fault detection and classification functions, plus meta-analysis based on indicators.
`In addition, Exensio –Control provides off-line and historical analysis capabilities to test FDC control strategies
`before deployment.
`• Real-time alarms and events management — Exensio –Control centralizes and assesses events and alarms to
`trigger the appropriate action. Equipment alarms and events are overlaid with trace and univariate SPC charts
`and can be analyzed in conjunction with FDC alarms. … ”
`
`
`See Exensio Control, available at http://www.pdf.com/Exensio-Control (last visited Oct. 12, 2020).
`
`
`As another example, because the Exensio System accepts multiple data types and/or formats of the state data, it
`necessarily translates these data types from a first communications protocol to a second communications protocol
`compatible with the fault detection unit in order that the fault detection unit can read and understand the state data:
`
`
`
`
`12
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`
`
`
`
`See S1.2—Exensio Platform Presentation at 6 (annotated).
`
`As another example, because the Exensio System supports state data from more than 100 fabrication tools, 20 testers,
`and 160 assembly tools and 50 data types, it necessarily translates such data from a first communications protocol to a
`second communications protocol compatible with the fault detection unit in order that the fault detection unit can read
`and understand the state data:
`
`
`
`
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`
`
`See S1.2—Exensio Platform Presentation at 11 (annotated).
`As yet another example, because the Exensio System supports state data from more than 100 equipment models for
`manufacturing, 150 equipment models for assembly, and 50 testers, probers, and handler models for test, it necessarily
`translates such data from a first communications protocol to a second communications protocol compatible with the
`fault detection unit in order that the fault detection unit can read and understand the state data:
`
`
`
`
`
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`14
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`
`
`See S1.2—Exensio Platform Presentation at 14 (annotated).
`
`
`PDF’s Exensio System sends the translated state data from the data collection unit to the fault detection unit.
`
`For example, the Exensio System sends the translated state data from the data collection unit to the FDC control unit:
`
`
`
`
`and sending the translated
`state data from the data
`collection unit to the fault
`detection unit;
`
`
`
`15
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 17 of 26 PageID #: 251
`
`
`
`
`See PDF Solutions Investor Presentation (Nov. 2017) at 10, available at
`http://www.pdf.com/upload/File/Investors/PDFInvestor%20Presentation%20November%202017.pdf (last visited Oct.
`12, 2020) (“2017 Investor Presentation”) (annotated).
`
`As another example, the Exensio System sends the translated state data from the data collection unit to the fault
`detection unit via the AIM YieldAware FDC platform:
`
`“Software Related Services – We provide software maintenance and support (or M&S), data management services,
`various value-added services (or VAS) to install, configure, or create analysis templates, and other professional services
`to achieve customers’ specific outcomes using our software. We call this last type of services our AIM solutions and, in
`these cases, we tailor the user flows of one or more Exensio products to achieve a desired result. For example, our AIM
`YieldAware™ FDC offering is designed to identify the process control variables that have the greatest impact on
`product yield through professional services that analyze the data from both Exensio Control and elements of Exensio
`Yield and make recommendations for the customer to implement. VAS are provided by our professional service
`personnel with expertise that enhances and complements the engineering teams at our customers. For example, VAS
`includes our data cleaning and monitoring services. One requirement of big data analytics is to have clean, harmonized
`data to analyze. This service offering outsources the data wrangling and management effort to free the customer to
`focus their efforts on analysis, which has a greater ROI to the company than data management.”
`
`
`
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`16
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`Case 4:20-cv-00991-ALM Document 1-10 Filed 12/31/20 Page 18 of 26 PageID #: 252
`
`See PDF Solutions Inc.’s Form 10-K (filed Mar. 10, 2020) at 8, available at http://ir.pdf.com/static-files/fb23407a-
`dfbc-489f-adb1-ac54e83102ad (last visited Oct. 12, 2020) (“2020 Form 10-K”).
`
`As another example, the Exensio System sends the translated state data from the data collection unit to the fault
`detection unit via the Data Exchange Network (“DEX”):
`
`
`
`
`See S1.2—Exensio Platform Presentation at 12 (annotated).
`
`
`
`
`determining if a fault
`condition exists
`with the processing tool
`based upon the state data
`received by the fault
`detection unit;
`
`PDF’s Exensio System determines if a fault condition exists with the processing tool based upon the state data received
`by the fault detection unit.
`
`As an example, the Exensio System is adapted to receive monitor and identify a fault condition covering various
`process parameters of the processing tool:
`
`“● Exensio Control – This software provides failure detection and classification (or FDC) capabilities for monitoring,
`alarming and control of manufacturing tool sets. These capabilities include proprietary data collection and analysis of
`tool sensor trace data and summary indicators designed to rapidly identify sources of process variations and
`manufacturing excursions. When used together with Exensio Yield and related modules, the accretive data mining and
`
`
`
`17
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`correlation capabilities are designed to enable identification of tool level sources of yield loss and process variation that
`impact end of line product yield, performance and reliability.”
`
`See 2020 Form 10-K at 7.
`
`As another example, the Exensio System determines if a fault condition exists with the processing tool based upon the
`state data received by the fault detection unit to improve yield and prevent large scale excursions at the tool:
`
`
`
`
`
`See S1.3— Machine Learning in Exensio, 16th Annual PDF Solutions Users Conference (Oct. 15, 2019) at 19,
`available at http://www.pdf.com/upload/File/Investors/PUG2019/S1.3%20PUG2019_AISolutions_JeffDavid.pdf
`(“S1.3—Machine Learning in Exensio”) (last visited Oct. 12, 2020).
`
`As another example, the Exensio System determines if a fault condition (e.g., whether a sensor detects abnormality)
`exists with the processing tool:
`
`
`
`
`18
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`
`
`See S1.3—Machine Learning in Exensio at 23.
`
`As another example, the Exensio System determines that a fault condition exists with the processing tool based on the
`failed patterns on the wafers:
`
`
`
`
`
`See Cognitive End to End Analytics Presentation at 9.
`
`
`
`
`
`19
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`
`
`PDF’s Exensio System performs a predetermined action on the processing tool in response to the presence of a fault
`performing a predetermined
`action on the processing tool
`condition.
`
`in response to the presence of
`a fault condition; and
`As an example, the Exensio System is adapted to control the processing tools or manufacturing tool sets to take
`corrective actions in response to a fault condition:
`
`“● Exensio Control – This software provides failure detection and classification (or FDC) capabilities for monitoring,
`alarming and control of manufacturing tool sets. These capabilities include proprietary data collection and analysis of
`tool sensor trace data and summary indicators designed to rapidly identify sources of process variations and
`manufacturing excursions. When used together with Exensio Yield and related modules, the accretive data mining and
`correlation capabilities are designed to enable identification of tool level sources of yield loss and process variation that
`impact end of line product yield, performance and reliability.”
`
`See 2020 Form 10-K at 7.
`
`As another example, the Exensio System adjusts processing of the processing tool by updating recipe tables and
`processing/tool parameters in response to the presence of a fault condition:
`
`
`
`See Cognitive End to End Analytics Presentation at 20 (annotated).
`
`
`
`
`
`
`20
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`As another example, the Exensio System adjusts the lithography, measurement, etching, or inspection parameters of the
`processing tool:
`
`
`
`
`See 2017 Investor Presentation at 10 (annotated).
`
`As another example, the Exensio System controls the processing tool to downgrade or scrape the die/package that
`contains the fault condition:
`
`
`
`
`
`
`21
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`sending an alarm signal
`indicative of the fault
`condition to an advanced
`process control framework
`from the fault detection unit
`providing that a fault
`condition of the processing
`tool was determined by the
`fault detection unit,
`
`
`
`
`See S1.2—Exensio Platform Presentation at 6 (annotated).
`
`PDF’s Exensio System sends an alarm signal indicative of the fault condition to an advanced process control
`framework from the fault detection unit providing that a fault condition of the processing tool was determined by the
`fault detection unit.
`
`As an example, the Exensio System sends an alarm signal indicative of the fault condition to the APC framework:
`
`“… Real-time alarms and events management — Exensio –Control centralizes and assesses events and alarms to trigger
`the appropriate action. Equipment alarms and events are overlaid with trace and univariate SPC charts and can be
`analyzed in conjunction with FDC alarms. …”
`
`See Exensio Control, available at http://www.pdf.com/Exensio-Control (last visited Oct. 12, 2020):
`
`As another example, the Exensio System sends an alarm signal indicative of the fault condition to the APC framework
`responsible for APC model building and APC overlay:
`
`
`
`
`22
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`
`
`
`
`See 2017 Investor Presentation at 10 (annotated).
`
`PDF’s Exensio System sends a signal by the framework to the first interface reflective of the predetermined action.
`
`As an example, the Exensio System sends a signal by the framework to the first interface reflective of the
`predetermined action as part of a feedback system in order to update its database and continue monitoring the
`processing pipeline to improve product and process control:
`
`
`wherein performing a
`predetermined action further
`comprises sending a signal
`by the framework to the first
`interface reflective of the
`predetermined action.
`
`
`
`23
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`
`
`See 2017 Investor Presentation at 10 (annotated).
`
`As another example, the Exensio System sends a signal by the framework to the first interface reflective of the
`predetermined action as part of the “inspect-analyze data-adjust-execute” methodology to continually identify and
`resolve manufacturing issues:
`
`
`
`
`
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`24
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`See Cognitive End to End Analytics Presentation at 8.
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`As another example, the Exensio System a signal by the framework to the first interface reflective of the predetermined
`action via the Data Exchange Network (“DEX”):
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`See S1.2—Exensio Platform Presentation at 12 (annotated).
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`25
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