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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The term “behind” in claim 1 is a relative term which renders the claim indefinite. The term “behind” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear what behind means in the context of the claim, if it is referring to a physically being behind or in terms of process of one happening before another.
Claim 6 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The term “behind” in claim 1 is a relative term which renders the claim indefinite. The term “behind” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear what behind means in the context of the claim, if it is referring to a physically being behind or in terms of process of one happening before another.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 6-9 is/are rejected under 35 U.S.C. 102(a) as being taught by Nogariya et al. (US Patent Number 2025/0308011-A1, hereinafter “Nogariya”)
Regarding claim 1, Nogariya teaches: A method of integrating production line data as auxiliary data for abnormality analysis,
wherein the method is applied to a device or a system, the device or the system is disposed in or applied to a production line of a target material, and the method comprises:
after the target material is passed through an automated optical inspection (AOI) device disposed on the production line, ([0031], "FIG. 1 is a view showing the configuration of an abnormality estimation system 1 according to the present embodiment. The abnormality estimation system 1 is a system which establishes a battery laminate for which the internal state thereof is known (more specifically, for example, an all solid-state battery or semi-solid state battery configured by laminating a negative electrode collector, a negative electrode layer, a solid electrolyte layer containing all solid or a semi-solid such as a gel, a positive electrode layer, a positive electrode collector, etc.) as a test object 7, and estimates abnormalities in this test object 7, based on X-ray image data of the test object 7 generated by an X-ray CT device 81.")
obtaining an optical inspection result generated by the AOI device and control management data of the target material generated by control management systems on the production line; ([0034], "The input data reception unit 2 receives X-ray CT image data 7D of the test object 7 generated by the X-ray CT device 81 as input data.")
integrating the optical inspection result and the control management data to generate an optical test data sheet; obtaining defect repair information, by a repair/repairable system, ([0037], "The model estimation unit 4 uses the abnormality estimation model generated by the aforementioned model generation unit 3 to estimate abnormalities in this test object 7 based on the input data of the test object 7 received by the input data reception unit 2. The model estimation unit 4, when inputting the input data received by the input data reception unit 2 to the abnormality estimation model, establishes the abnormality data outputted from this abnormality estimation model as the estimation results for abnormalities in the test object 7, and sends these to the display unit 5.")
wherein the defect repair information is generated by an inspection station which is sited behind the AOI device and determines that the target material is abnormal, and the defect repair information comprises defect location information and a defect location image; (Fig. 2A)
reading material data of the target material from the optical test data sheet based on the defect location information, wherein the material data comprises the control management data; ([0035], " Herein, in the abnormality data outputted from the abnormality estimation model, information related to the shape and composition of abnormalities in the test object 7 as described later (more specifically, information related to the presence/absence of abnormalities such as cracks, voids, Li precipitate and foreign matter adhesion, as well as occurrence locations of these abnormalities and three-dimensional structure of abnormalities) is included.")
obtaining a material image of the target material, and extracting a component location image from the material image based on the defect location information; (Fig. 2A, Fig. 4A, Fig. 4B)
integrating the material data, the defect repair information and the component location image to generate integration information of the target material; and outputting the integration information. (Fig. 3, St4)
Regarding claim 2, Nogariya teaches: The method of integrating production line data as auxiliary data for abnormality analysis according to claim 1, wherein after the step of generating the integration information of the target material, further comprising:generating an abnormality determination result based on the integration information,and outputting the abnormality determination result. ([0037], "The model estimation unit 4 uses the abnormality estimation model generated by the aforementioned model generation unit 3 to estimate abnormalities in this test object 7 based on the input data of the test object 7 received by the input data reception unit 2. The model estimation unit 4, when inputting the input data received by the input data reception unit 2 to the abnormality estimation model, establishes the abnormality data outputted from this abnormality estimation model as the estimation results for abnormalities in the test object 7, and sends these to the display unit 5.")
Regarding claim 3, Nogariya teaches: The method of integrating production line data as auxiliary data for abnormality analysis according to claim 1, wherein the step of obtaining the material image of the target material comprises:reading the material image from the optical inspection result or downloading the material image from the AOI device.([0037], "The model estimation unit 4 uses the abnormality estimation model generated by the aforementioned model generation unit 3 to estimate abnormalities in this test object 7 based on the input data of the test object 7 received by the input data reception unit 2. The model estimation unit 4, when inputting the input data received by the input data reception unit 2 to the abnormality estimation model, establishes the abnormality data outputted from this abnormality estimation model as the estimation results for abnormalities in the test object 7, and sends these to the display unit 5.")
Regarding claim 4, Nogariya teaches: The method of integrating production line data as auxiliary data for abnormality analysis according to claim 1, wherein the control management systems comprise at least one of a factory information system, a manufacturing execution system, and an integrated manufacturing data management system, ([0031], "FIG. 1 is a view showing the configuration of an abnormality estimation system 1 according to the present embodiment. The abnormality estimation system 1 is a system which establishes a battery laminate for which the internal state thereof is known (more specifically, for example, an all solid-state battery or semi-solid state battery configured by laminating a negative electrode collector, a negative electrode layer, a solid electrolyte layer containing all solid or a semi-solid such as a gel, a positive electrode layer, a positive electrode collector, etc.) as a test object 7, and estimates abnormalities in this test object 7, based on X-ray image data of the test object 7 generated by an X-ray CT device 81.")
and the control management data comprises at least one of material identification data, an inspection time and an inspection result of the target material generated by the AOI device, a material type of the target material obtained by the factory information system, the material identification data of the target material and an apparatus status of a surface mounted technology apparatus obtained by the manufacturing execution system, and material information of the target material obtained by the integrated manufacturing data management system. ([0031], "FIG. 1 is a view showing the configuration of an abnormality estimation system 1 according to the present embodiment. The abnormality estimation system 1 is a system which establishes a battery laminate for which the internal state thereof is known (more specifically, for example, an all solid-state battery or semi-solid state battery configured by laminating a negative electrode collector, a negative electrode layer, a solid electrolyte layer containing all solid or a semi-solid such as a gel, a positive electrode layer, a positive electrode collector, etc.) as a test object 7, and estimates abnormalities in this test object 7, based on X-ray image data of the test object 7 generated by an X-ray CT device 81.")
Regarding claim 6, claim 6 has been analyzed with regard to claim 1 and is rejected for the same reasons of obviousness as used above as well as in accordance with Nogariya further teaching on: A device of integrating production line data as auxiliary data for abnormality analysis,comprising:a memory, configured to store at least one computer instruction; anda processor, connected to the memory and configured to execute the at least one computer instruction to generate: ([0033], “The abnormality estimation system 1 is a computer configured by hardware such as an arithmetic processing means such as a CPU, an auxiliary storage means such as a HDD or SSD storing various programs, a main storage means such as RAM for storing data which is necessitated temporarily upon the arithmetic processing means executing a program, and a display means which displays arithmetic processing results by the arithmetic processing means in a manner visibly recognizable by a user.”)
Regarding claim 7, claim 7 has been analyzed with regard to claim 2 and is rejected for the same reasons of obviousness as used above as well as in accordance with Nogariya further teaching on: A device of integrating production line data as auxiliary data for abnormality analysis,comprising:a memory, configured to store at least one computer instruction; anda processor, connected to the memory and configured to execute the at least one computer instruction to generate: ([0033], “The abnormality estimation system 1 is a computer configured by hardware such as an arithmetic processing means such as a CPU, an auxiliary storage means such as a HDD or SSD storing various programs, a main storage means such as RAM for storing data which is necessitated temporarily upon the arithmetic processing means executing a program, and a display means which displays arithmetic processing results by the arithmetic processing means in a manner visibly recognizable by a user.”)
Regarding claim 8, claim 8 has been analyzed with regard to claim 3 and is rejected for the same reasons of obviousness as used above as well as in accordance with Nogariya further teaching on: A device of integrating production line data as auxiliary data for abnormality analysis,comprising:a memory, configured to store at least one computer instruction; anda processor, connected to the memory and configured to execute the at least one computer instruction to generate: ([0033], “The abnormality estimation system 1 is a computer configured by hardware such as an arithmetic processing means such as a CPU, an auxiliary storage means such as a HDD or SSD storing various programs, a main storage means such as RAM for storing data which is necessitated temporarily upon the arithmetic processing means executing a program, and a display means which displays arithmetic processing results by the arithmetic processing means in a manner visibly recognizable by a user.”)
Regarding claim 9, claim 9 has been analyzed with regard to claim 4 and is rejected for the same reasons of obviousness as used above as well as in accordance with Nogariya further teaching on: A device of integrating production line data as auxiliary data for abnormality analysis,comprising:a memory, configured to store at least one computer instruction; anda processor, connected to the memory and configured to execute the at least one computer instruction to generate: ([0033], “The abnormality estimation system 1 is a computer configured by hardware such as an arithmetic processing means such as a CPU, an auxiliary storage means such as a HDD or SSD storing various programs, a main storage means such as RAM for storing data which is necessitated temporarily upon the arithmetic processing means executing a program, and a display means which displays arithmetic processing results by the arithmetic processing means in a manner visibly recognizable by a user.”)
Claim Rejections - 35 USC § 103
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.
Claim(s) 5 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nogariya et al. (US Patent Number 2025/0308011-A1, hereinafter “Nogariya”) in view of Nishizawa et al. (US Patent Number 2021/0374942-A1, hereinafter “Nishizawa”)
Regarding claim 5, Nogariya does not teach: The method of integrating production line data as auxiliary data for abnormality analysis according to claim 1, wherein the step of extracting the component location image from the material image based on the defect location information, comprises:converting the defect location information into a pixel location coordinate corresponding to the material image, and extracting the component location image from the material image based on the pixel location coordinate.
However, Nishizawa does teach: The method of integrating production line data as auxiliary data for abnormality analysis according to claim 1, wherein the step of extracting the component location image from the material image based on the defect location information, comprises:converting the defect location information into a pixel location coordinate corresponding to the material image, and extracting the component location image from the material image based on the pixel location coordinate. (Nishizawa, [0185], "After the process at S287, the defect candidate detecting processor 35a subtracts the image binarized with 0 and α at S287 from the belt image obtained during the band-like noise removal step at S144 (S288). The process at S288 is to subtract, from the color value of each pixel of the belt image obtained during the band-like noise removal step at S144, the value of the pixel that is present at the same coordinates as those of the corresponding pixel and that is in the image binarized with 0 and α at S287.")
At the time the invention was made, it would have been obvious to one of ordinary skill in the art to modify abnormality detection (as taught by Nogariya) to include abnormality pixel location through coordinates (as taught by Nishizawa) because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, abnormality detection (as taught by Nogariya) as modified by abnormality pixel location through coordinates (as taught by Nishizawa) can yield a predictable result of allowing for more accurate data for abnormality location in the image data. Thus, a person of ordinary skill would have appreciated including in abnormality detection (as taught by Nogariya) the ability to do abnormality pixel location through coordinates (as taught by Nishizawa) since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 10, claim 10 has been analyzed with regard to claim 5 and is rejected for the same reasons of obviousness as used above as well as in accordance with Nogariya further teaching on: A device of integrating production line data as auxiliary data for abnormality analysis,comprising:a memory, configured to store at least one computer instruction; anda processor, connected to the memory and configured to execute the at least one computer instruction to generate: ([0033], “The abnormality estimation system 1 is a computer configured by hardware such as an arithmetic processing means such as a CPU, an auxiliary storage means such as a HDD or SSD storing various programs, a main storage means such as RAM for storing data which is necessitated temporarily upon the arithmetic processing means executing a program, and a display means which displays arithmetic processing results by the arithmetic processing means in a manner visibly recognizable by a user.”)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jinsu Hwang whose telephone number is (703)756-1370. The examiner can normally be reached Mon -Thu 10am-8am EST.
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/JINSU HWANG/Examiner, Art Unit 2667 /MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
