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 .
Election/Restrictions
Applicant’s election without traverse of claims 1-8 and 17-20 in the reply filed on 06/15/2026 is acknowledged.
Claims 9-16 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected method, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 06/15/2026.
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.
Claims 1, 3-5, 7, and 17-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Reese (US-20160236414-A1).
Regarding claim 1, Reese teaches method of fabricating an object, comprising: fabricating a three-dimensional (3D) structure using additive processing; detecting a defect in the 3D structure; identifying a location of the 3D structure corresponding to a 3D space occupied by the defect; and removing material from the location of the 3D structure using subtractive processing to correct the defect (¶0022-0039).
Regarding claims 3-4, as applied to claim 1, Reese teaches method further comprising adding additional material to the 3D structure using additive processing after removing material (¶0067,0075) and further comprising modifying a print parameter before adding additional material, based on the defect, to prevent future defects (¶0067-0068,0089).
Regarding claim 5, as applied to claim 1, Reese teaches method wherein detecting the defect includes scanning the 3D structure to generate a 3D scan and comparing the 3D scan to an original 3D design used to fabricate the 3D structure (¶0084,0090).
Regarding claim 7, as applied to claim 1, Reese teaches method wherein the additive processing includes a five-dimensional (5D) process that performs a rotation of the 3D structure or a print head in one or more spatial dimensions (¶0012,0029-0030).
Regarding claim 17, Reese teaches a computer program product, comprising: one or more computer-readable storage media; and program instructions stored on the one or more computer-readable storage media to perform operations comprising: controlling a print head to fabricate a three-dimensional (3D) structure using additive processing; detecting a defect in the 3D structure; identifying a location of the 3D structure corresponding to a 3D space occupied by the defect; and controlling a subtractive processing system to remove material from the location of the 3D structure to correct the defect (¶0022-0039, ¶0079-0091).
Regarding claim 18, as applied to claim 17, Reese teaches a computer program product wherein the operations further comprise controlling the print head to add additional material to the 3D structure after the subtractive processing system removes material (¶0022-0039,0067,0075).
Regarding claim 19, as applied to claim 17, Reese teaches a computer program product wherein the operations further comprise modifying a print parameter before adding additional material, based on the defect, to prevent future defects (¶0022-0039,0067-0068,0089).
Claim Rejections - 35 USC § 103
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Reese (US-20160236414-A1), as applied to claim 1, and in further view of Vadugappatty Srinivasan (US-20230093834-A1).
Regarding claim 2, as applied to claim 1, while Reese teaches a method wherein the subtractive processing uses milling (¶0008,0037), Reese does not explicitly teach a method wherein the subtractive processing uses a computer numerical control (CNC) system to selectively remove material from the 3D structure.
However, reasonably pertinent to the particular problem with which the applicant was concerned (computer numerical control (CNC) systems; see MPEP 2141.01(a)), Vadugappatty Srinivasan discloses that the cutting method may include, but not limited to, computer numerical control (CNC) milling (subtractive processing uses a computer numerical control (CNC) system to selectively remove material) (known technique applicable to the base method) (¶0069)
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to modify the method disclosed in Reese by applying the known technique of subtractive processing using a computer numerical control (CNC) system to selectively remove material disclosed in Vadugappatty Srinivasan to the method wherein the subtractive processing uses milling disclosed in Reese to selectively remove material from the 3D structure as instantly claimed with predictable results and resulting in an improved method. MPEP 2143(D).
Claims 6 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Reese (US-20160236414-A1).
Regarding claim 6, as applied to claim 5, Reese does not explicitly teach a method wherein detecting the defect includes determining that the scan deviates from the 3D design by an above-threshold amount.
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to modify the method taught by Reese to further comprise determining that the scan deviates from the 3D design by an above-threshold amount with a reasonable expectation of success in order to identify any properties that fall outside the specifications (¶0090).
Regarding claim 20, as applied to claim 17, Reese teaches a computer program product wherein detecting the defect includes scanning the 3D structure to generate a 3D scan and comparing the 3D scan to an original 3D design used to fabricate the 3D structure (¶0084,0090).
While Reese does not explicitly teach a computer program product further comprising determining that the scan deviates from the 3D design by an above-threshold amount, one of ordinary skill in the art before the effective filing date of the invention would have found it obvious to modify a computer program product taught by Reese to further comprise determining that the scan deviates from the 3D design by an above-threshold amount with a reasonable expectation of success in order to identify any properties that fall outside the specifications (¶0090).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Reese (US-20160236414-A1), as applied to claim 1, and in further view of Goyal (US-20230076556-A1 - of record).
Regarding claim 8, as applied to claim 1, while Reese teaches a method wherein detecting the defect includes identifying a defect (¶0022-0039), Reese does not explicitly teach a method wherein detecting the defect includes identifying a defect using a trained machine learning model based on an image of the 3D structure.
However, reasonably pertinent to the particular problem with which the applicant was concerned (performing corrective actions during three-dimensional printing jobs; see MPEP 2141.01(a)), Goyal discloses a method comprising utilizing machine learning and a self-updating knowledge base for identifying and applying corrective actions, thereby increasingly improving the 3D printing process over time (identifying a defect using a trained machine learning model) (known technique applicable to the base method) (¶0016).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to modify the method disclosed in Reese by applying the known technique of identifying a defect using a trained machine learning model disclosed in Goyal to the method wherein detecting the defect includes identifying a defect disclosed in Reese based on an image of the 3D structure as instantly claimed with predictable results and resulting in an improved method. MPEP 2143(D).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Hasanain (US-20210365016-A1 - of record) discloses the known technique that machine learning and artificial intelligence processes may be utilized for both pattern recognition (e.g., using a neural network or other type of machine learning technique), such as to identify features or signatures indicative of defects or normal AM processing and operations, and may also be utilized for decision making, such as to modify or adjust an AM process when an anomaly or defect is detected (¶0031).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JaMel M Nelson whose telephone number is (571)272-8174. The examiner can normally be reached 9:00 a.m. to 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Galen Hauth can be reached on (571) 270-5516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMEL M NELSON/Primary Examiner, Art Unit 1743
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