DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Style
In this action unitalicized bold is used for claim language, while italicized bold is used for emphasis.
Information Disclosure Statement
All information disclosure statements were submitted prior to the first action and are incompliance with the provisions of 37 C.F.R. § 1.97. Accordingly, they have been considered.
Applicant Reply
“The claims may be amended by canceling particular claims, by presenting new claims, or by rewriting particular claims as indicated in 37 CFR 1.121(c). The requirements of 37 CFR 1.111(b) must be complied with by pointing out the specific distinctions believed to render the claims patentable over the references in presenting arguments in support of new claims and amendments. . . . The prompt development of a clear issue requires that the replies of the applicant meet the objections to and rejections of the claims. Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. . . . An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” MPEP § 714.02. Generic statements or listing of numerous paragraphs do not “specifically point out the support for” claim amendments. “With respect to newly added or amended claims, applicant should show support in the original disclosure for the new or amended claims. See, e.g., Hyatt v. Dudas, 492 F.3d 1365, 1370, n.4, 83 USPQ2d 1373, 1376, n.4 (Fed. Cir. 2007) (citing MPEP § 2163.04 which provides that a ‘simple statement such as ‘applicant has not pointed out where the new (or amended) claim is supported, nor does there appear to be a written description of the claim limitation ‘___’ in the application as filed’ may be sufficient where the claim is a new or amended claim, the support for the limitation is not apparent, and applicant has not pointed out where the limitation is supported.’)” MPEP § 2163(II)(A).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over Takeda (WO 2020184078, Control System for Controlling Polishing Device for Polishing Substrate, and Polishing Method; Same Assignee, published September 2020, more than one year before 4 October 2021) and Ren (State of the Art in Defect Detection Based on Machine Vision, may 2021.)
1. An information processing apparatus comprising: an information acquisition section configured to acquire crack occurrence state information including crack state information (“defect data related to a defect of the substrate” Takeda ¶52 cited below.) and device state information, ((“data related to processing content of the substrate in the polishing device” Takeda ¶52.) Takeda teaches: “The control system 102 includes: a defect data reception unit 112 configured to receive defect data related to a defect of the substrate; a processing data reception unit 114 configured to receive processing data related to processing content of the substrate in the polishing device[.]” Takeda ¶52. “In the case of a scratch generated immediately after the idle state of the polishing device 1000 (a state in which polishing is not performed) continues for a long time, it is considered that a solid material in which the slurry adhered to the slurry supply nozzle or the top ring is solidified falls on the polishing table, and a scratch has occurred due to the influence of the solid matter.” Takeda ¶110. “In the case of a scratch generated immediately after the polishing recipe is changed, it is considered that the pressure of pressing the wafer onto the pad is too strong[.] . . . At this time, . . . the pressure for pressing the wafer against the pad is checked, and a defect correction procedure for reducing the pressure within the range of the reference value allowed by the host computer 126 is instructed.” Takeda ¶111. One of ordinary skill in the art would understand a parameter used to modify the process as having been input to the control system for the process. “The processing data is, for example, at least one of lot information for identifying the substrate individually or in a plurality of units, information on processing received by the substrate in each process inside and outside the polishing apparatus, alarm information received by the substrate in each process, consumable member information used for processing the substrate (a type of a consumable member such as a polishing pad, a use time, and the like). Note that the defect data receiving unit and the processing data receiving unit may be one data receiving unit.” Takeda ¶11.) the crack state information indicating crack state of a substrate that has been cracked in a substrate processing process performed by a substrate processing device including a polishing unit configured to perform a polishing process on the substrate and a substrate transport unit configured to transport the substrate to and from the polishing unit, (For the transport unit, see Takeda ¶¶29-31. For damage to the substrate and the polishing unit, see Takeda ¶¶52 and 111, cited above. Takeda teaches information indicating scratches of a substrate that has been damaged during processing, and responding by modifying the pressure of the pad used to buffer the wafer. See Above. But does not expressly teach “crack state information indicating a cracked state of a substrate that has been cracked in a substrate processing[.]”
Ren teaches “Machine vision detection technology can improve the detection efficiency and degree of automation, enhance the real-time performance and accuracy of detection, and reduce manpower requirements, especially for some large-scale repetitive industrial production processes. As a non-contact and nondestructive detection method, machine vision can be easily employed to perform information integration, automation, intelligence, and precise control. It has become the basic technology required in computer integrated manufacturing and intelligent manufacturing.” Ren p. 661-662. “The common defects in surface inspection can be categorized into two categories: (i) geometric defects, such as pits, scratches, cracks, burrs, bulges, scratches, and bumps[.]” Ren p. 664 col. 1. “The coaxial forward lighting can be used to detect surface defects, cracks, scratches, etc.” Ren p. 664 col. 2.
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Ren, modifying the teaching of Takeda to identify cracks, because detection of cracks improves the output of the manufacturing process (i.e. by avoiding repeated manufacture of cracked products.)) the device state information indicating a state of the polishing unit when the substrate processing process is performed on the cracked substrate; (“The control system 102 includes: a defect data reception unit 112 configured to receive defect data related to a defect of the substrate; a processing data reception unit 114 configured to receive processing data related to processing content of the substrate in the polishing device[.]” Takeda ¶52.) and a crack occurrence process identifying section configured to identify a process that causes the crack in the substrate by inputting the crack occurrence state information acquired by the information acquisition section to a learning model in response to the occurrence of the crack in the substrate, the learning model having been generated by machine learning that causes the learning model to learn a correlation between the crack occurrence state information and crack occurrence process information indicating the process that causes the crack in the substrate, the process being among processes included in the substrate processing process. (“The defect knowledge database 144 has data indicating the correspondence between the defect data and the processing data and the cause of the occurrence of the defect and the defect correction procedure.” Takeda ¶70. “The neural network 150 performs automatic learning, and specifically, may perform machine learning and perform deep learning as machine learning. Learning data (defect data and processing data) is input to the neural network 150, and the neural network 150 outputs output data (a cause of a defect and a defect correction procedure).” Takeda ¶72. “In order to obtain the correspondence relationship, the database update unit 142 can determine the cause of the occurrence of the defect and the defect correction measure by using any method such as a decision tree, a neural network, a simulation, or the like. FIG. 5 illustrates an example in which a neural network is used.” Takeda ¶71. “Referring back to FIG. 4, the defect occurrence cause identifying unit 116 accesses the defect knowledge database 144, identifies the cause of the defect occurrence with respect to the defect data and the processing data indicating the newly added defect, and outputs the defect occurrence cause to the defect correction treatment unit 118. The data output by the defect occurrence cause identifying unit 116 May be referred to as a lot information of a substrate in which a defect has occurred, a polishing apparatus 1000 in which a defect has been generated, and a unit (referred to as a "chamber") in the polishing apparatus 1000 in which a defect has been generated. The identification information, the cause of the occurrence of the defect (the component in which the defect has been generated and/or the content of the processing), and the like are used. The cause of generating the defect may be a failure of the device and/or a malfunction of the device and/or an error in setting of the device and/or improper processing of the device, etc.” Takeda ¶92.)
2. The information processing apparatus according to claim 1, wherein the crack state information included in the crack occurrence state information includes: image information indicating the cracked substrate that has been photographed; or sketch information indicating the cracked substrate that has been sketched. (Ren teaches “Machine vision detection technology can improve the detection efficiency and degree of automation, enhance the real-time performance and accuracy of detection, and reduce manpower requirements, especially for some large-scale repetitive industrial production processes. As a non-contact and nondestructive detection method, machine vision can be easily employed to perform information integration, automation, intelligence, and precise control. It has become the basic technology required in computer integrated manufacturing and intelligent manufacturing.” Ren p. 661-662. “The common defects in surface inspection can be categorized into two categories: (i) geometric defects, such as pits, scratches, cracks, burrs, bulges, scratches, and bumps[.]” Ren p. 664 col. 1. “The coaxial forward lighting can be used to detect surface defects, cracks, scratches, etc.” Ren p. 664 col. 2. The motivation to combine in claim 1 applies here.
3. The information processing apparatus according to claim 1, wherein the device state information included in the crack occurrence state information includes the state of the polishing unit which includes at least one of: a position of a top ring of the polishing unit; a height of the top ring; pressure in a pressure chamber provided in the top ring; and a flow rate of pressurized fluid supplied to the pressure chamber. (“The top ring 330A holds the substrate and presses the substrate against the polishing pad 310A. The top ring 330A is rotationally driven by a drive source (not shown). The substrate is polished by being held by the top ring 330A and pressed by the polishing pad 310A.” Takeda ¶28. “At the time of polishing, the polishing table 320A and the top ring 330A are rotationally driven. The substrate WF is polished by being pressed against the polishing surface of the polishing pad 310A by the top ring 330A.” Takeda ¶36. “In the case of a scratch generated immediately after the polishing recipe is changed, it is considered that the pressure of pressing the wafer onto the pad is too strong[.] . . . At this time, . . . the pressure for pressing the wafer against the pad is checked, and a defect correction procedure for reducing the pressure within the range of the reference value allowed by the host computer 126 is instructed.” Takeda ¶111.)
4. The information processing apparatus according to claim 1, wherein the device state information included in the crack occurrence state information further includes a state of the substrate transport unit in addition to the state of the polishing unit, the state of the substrate transport unit including at least one of: a position of the substrate transport unit: a height of the substrate transport unit: and presence or absence of the substrate in the substrate transport unit. (“The defect knowledge database 144 accumulates the defect data detected by the inspection device group 110 in the polishing step and the defect data detected in addition to the polishing step and in a range that can be handled by the polishing device 1000, and the processing data detected by the polishing device group 108. The defect detected in addition to the polishing step is defect data and processing data transmitted from the host computer 126 to the defect data receiving unit 112 via the signal line 128.” Takeda ¶107. The information showing the substrate to be located in the polishing device indicates “absence of the substrate in the substrate transport unit.” Note: the language “presence or absence . . . ” reads on mere absence of the substrate from the transport unit. The teaching of a location of the substrate in the polishing device, necessarily teaches a state where the substrate is absent from the transport unit. In contrast, language similar to “the state of the substrate transport unit including . . . [only] presence of the substrate in the substrate transport unit” would not read on paragraph 107 of Takeda. The same would apply to language clearly requiring both present and absent states.)
5. The information processing apparatus according to claim 1, wherein the crack occurrence process information includes processes included in the substrate processing process, the processes including at least one of: a substrate receiving process in which the polishing unit receives the substrate from the substrate transport unit before the polishing process; a pre-polishing oscillation process in which the polishing unit moves the substrate to a polishing position before the polishing process; a pre-polishing lowering process in which the polishing unit lowers the substrate to a polishing height before the polishing process; a polishing process in which the polishing unit performs the polishing process on the substrate; a post-polishing elevating process in which the polishing unit elevates the substrate to a moving height after the polishing process; a post-polishing oscillation process in which the polishing unit moves the substrate to a transfer position after the polishing process; and a substrate delivery process in which the polishing unit delivers the substrate to the substrate transport unit after the polishing process. (“The defect knowledge database 144 has data indicating the correspondence between the defect data and the processing data and the cause of the occurrence of the defect and the defect correction procedure.” Takeda ¶70. “In order to obtain the correspondence relationship, the database update unit 142 can determine the cause of the occurrence of the defect and the defect correction measure by using any method such as a decision tree, a neural network, a simulation, or the like. FIG. 5 illustrates an example in which a neural network is used.” Takeda ¶71. “Referring back to FIG. 4, the defect occurrence cause identifying unit 116 accesses the defect knowledge database 144, identifies the cause of the defect occurrence with respect to the defect data and the processing data indicating the newly added defect, and outputs the defect occurrence cause to the defect correction treatment unit 118. The data output by the defect occurrence cause identifying unit 116 May be referred to as a lot information of a substrate in which a defect has occurred, a polishing apparatus 1000 in which a defect has been generated, and a unit (referred to as a "chamber") in the polishing apparatus 1000 in which a defect has been generated. The identification information, the cause of the occurrence of the defect (the component in which the defect has been generated and/or the content of the processing), and the like are used. The cause of generating the defect may be a failure of the device and/or a malfunction of the device and/or an error in setting of the device and/or improper processing of the device, etc.” Takeda ¶92. This teaches at least the claimed “polishing process in which the polishing unit performs the polishing process on the substrate[.]”)
6. An inference apparatus comprising: a memory; and a processor configured to perform: an information acquisition process of acquiring crack occurrence state information including crack state information and device state information, the crack state information indicating crack state of a substrate that has been cracked in a substrate processing process performed by a substrate processing device including a polishing unit configured to perform a polishing process on the substrate and a substrate transport unit configured to transport the substrate to and from the polishing unit, the device state information indicating a state of the polishing unit when the substrate processing process is performed on the cracked substrate; and an inferring process of inferring a process that causes the crack in the substrate when acquiring the crack occurrence state information in the information acquisition process in response to occurrence of the crack in the substrate, the process inferred being among processes included in the substrate processing process. (See rejection of claim 1.)
7. A machine-learning apparatus comprising: a learning-data storage section storing multiple sets of learning data including crack occurrence state information and crack occurrence process information, the crack occurrence state information including crack state information and device state information, the crack state information indicating crack state of a substrate that has been cracked in a substrate processing process performed by a substrate processing device including a polishing unit configured to perform a polishing process on the substrate and a substrate transport unit configured to transport the substrate to and from the polishing unit, the device state information indicating a state of the polishing unit when the substrate processing process is performed on the cracked substrate, the crack occurrence process information indicating a process that causes the crack in the substrate, the process being among processes included in the substrate processing process; a machine-learning section configured to cause a learning model to learn a correlation between the crack occurrence state information and the crack occurrence process information by inputting the multiple sets of learning data to the learning model; and a learned-model storage section configured to store the learning model that has learned the correlation by the machine learning section. (See rejection of claim 1.)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAUL M KNIGHT whose telephone number is (571) 272-8646. The examiner can normally be reached Monday - Friday 9-5 ET.
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PAUL M. KNIGHTPrimary ExaminerArt Unit 2148
/PAUL M KNIGHT/
Primary Examiner, Art Unit 2148
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