Prosecution Insights
Last updated: August 30, 2026
Application No. 18/283,792

PART FEATURES AND SPECIFIC PRINT MODES

Non-Final OA §103
Filed
Sep 23, 2023
Priority
Mar 29, 2021 — nonprovisional of PCTUS2021024690
Examiner
MACHNESS, ARIELLA
Art Unit
1743
Tech Center
1700 — Chemical & Materials Engineering
Assignee
HP Inc.
OA Round
3 (Non-Final)
62%
Grant Probability
Moderate
3-4
OA Rounds
0m
Est. Remaining
90%
With Interview

Examiner Intelligence

Grants 62% of resolved cases
62%
Career Allowance Rate
104 granted / 169 resolved
-3.5% vs TC avg
Strong +29% interview lift
Without
With
+28.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
34 currently pending
Career history
214
Total Applications
across all art units

Statute-Specific Performance

§101
0.3%
-39.7% vs TC avg
§103
51.8%
+11.8% vs TC avg
§102
21.6%
-18.4% vs TC avg
§112
22.5%
-17.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 169 resolved cases

Office Action

§103
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/10/2026 has been entered. Election/Restrictions Claims 23-28 are withdrawn, since they are directed to nonelected Groups II and III, as discussed in the Requirement for Restriction mailed 04/11/2025 and the Office Action mailed 01/12/2026. Response to Amendment In view of the amendment filed 04/10/2026: Claims 1-11, 13, 21, and 22 are pending. Claims 12 and 14-20 are cancelled. Claims 23-28 are withdrawn from further consideration. 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 (i.e., changing from AIA to pre-AIA ) 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. The factual inquiries 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. 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. Claim(s) 1-6 are rejected under 35 U.S.C. 103 as being unpatentable over Das et al. (US20160221262), and further in view of Gosch et al. (US20180178451). Regarding claim 1, Das teaches a method performed by a three dimensional printing system ([0203] The control system 400 may comprise the PCS 405 for the LAMP system 100. In essence, the PCS 405 forms the brains of the LAMP system 400 and is the central processing unit of the system, responsible for automation functions. The PCS 405 may include the software algorithms to conduct adaptive slicing of the integral cored mold CAD files for optimized layer thickness, part surface finish, avoidance of stairstepping, and minimum build time as a function of critical features and feature sizes present in the mold design) and comprising: receiving a print job ([0182] and [0204] The PCS may include all the necessary CAD data interfaces, machine automation and control hardware and software interfaces, and fault detection and recovery in order for the LAMP machine to function as a fully automated, operator-free solid freeform fabrication (SFF) machine…. FIG. 10a illustrates a plurality of stacked cross-sectional views of the 3D image that results in the turbine airfoil mold 3D casting of FIG. 10b) comprising a plurality of parts to be printed by the three dimensional printing system (see multiple turbine airfoil molds being formed in Figure 4 and the CAD slice patterns of multiple turbine airfoil molds in Figure 5a to Figure 5c); identifying that at least some of the plurality of parts include a particular part feature intended to be printed in a specific print mode, customized for printing the particular part feature ([0205] Intelligent adaptive slicing algorithms optimize build speed and throughput while at the same time carefully accounting for necessary feature resolution and/or surface finish embedded in each slice layer thickness. For example, sections of the integral cored mold containing critical features may be sliced at approximately 25 micron layer thickness, while other regions corresponding to the platform and pour cup with non-critical features or mostly vertical walls may be sliced at approximately 100 microns or larger layer thickness); executing the print job using the specific print mode for the particular part feature ([0012] the SLMs project a two-dimensional image (e.g., from a CAD file) thereon. The two-dimensional image comprises a cross-section of a three-dimensional object to be formed within the various layers of the photopolymer, once cured and [0205] sections of the integral cored mold containing critical features may be sliced at approximately 25 micron layer thickness, while other regions corresponding to the platform and pour cup with non-critical features or mostly vertical walls may be sliced at approximately 100 microns or larger layer thickness. Data transfer and file format protocols transmit the CAD slice data to the SLM array. Intelligent software and hardware algorithms convert the CAD data slices to the stack of image frames necessary to be flashed at a high refresh rate to the array of SLMs in the MOIS); and monitoring the usage of the specific print mode ([0187] The SLM array may receive a real-time video stream of CAD data-slice bitmap images from the control system 400 and [0203] Software algorithms may also adaptively adjust the exposure dose in real-time as a function of slice layer thickness to achieve the necessary full cure depth through the layer thickness regardless of the layer thickness; also see Figure 58 and Figure 59 where layer thickness is monitored as a function of part height and as noted in [0205] critical features may have a particular slice layer thickness and non-critical features will have a different slice layer thickness). However, Das fails to teach a step of determining that the print job is authorized to use the specific print mode customized for printing the particular part feature, that the identifying step occurs in response to determining that the print job is authorized to use the specific print mode, and that the print job is executed when it has been authorized. In the same field of endeavor pertaining to additive manufacturing, Gosch teaches a first step M1 of transmitting printing specification data to a distributed validation network, a second step M2 of the distributed validation network validating the printing specification data and data the data to a print history log, a step M3 of transmitting the specification data to a 3D printing device, a step M4 of the actual generative manufacturing process, a step M5 of iteratively transmitting a plurality of additive manufacturing parameters from the preceding manufacturing stage to the distributed validation network, and a step M6 of matching the transmitted manufacturing parameters to printing specification data stored in the print history log ([0052]). The printing specification data in step M1 to be validated includes information regarding the printing material, temperature, pressure, quantity of material to be used, and the type of generative manufacturing processes to be implemented ([0051] the printing specification data can for example contain information regarding the printing material to be used, the temperature to be used during the additive manufacturing, the ambient pressure to be applied during the additive manufacturing, the quantity of printing material to be used and/or the type of generative manufacturing process to be implemented). Further, Gosch teaches manufacturing stages that each comprise a specified number of print layers of the generative manufacturing process ([0047] transmit to the distributed validation network 13 a plurality of manufacturing parameters that are prevailing in the preceding manufacturing stage. The manufacturing stages can, for example, each comprise a specified number of print layers of the generative manufacturing process). The validation process of Gosch can continuously monitor a print job’s compatibility with user requirements ([0045] validating the printing specification data allows the printing contractor to trace the print job and the compatibility, in each case, with the contractual requirements aids in the collaboration with the print job client) and avoid user-defined discrepancies in product requirements that can result in qualitatively inferior end products ([0013] the printing process itself can be continuously monitored in order to uncover discrepancies that occur inadvertently or are caused by contractors acting mala fide. For example, it is possible to effectively prevent acceptance of advantages when executing the print job by saving material or by using printing parameters that are cost-saving but that lead to qualitatively inferior end products). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have a step of determining that the print job of Das is authorized to use the specific print mode customized for printing the particular part feature, that the identifying step of Das occurs in response to determining that the print job is authorized to use the specific print mode, and that the print job of Das is executed when it has been authorized, as taught by Gosch, for the benefit of avoiding user-defined discrepancies in product requirements that can result in qualitatively inferior end products. Regarding claim 2, Das modified with Gosch teaches the method of claim 1. Further, Das teaches CAD slice patterns of multiple airfoil molds are analyzed ([0223] The method may further include analyzing a plurality of two-dimensional computer aided designs; the light beam presented on the portion of the photocurable medium having the shape from one of the plurality of two- dimensional computer aided designs) and projected as shown in Figure 5a to Figure 5C. Where multiple CAD slice patterns of airfoil molds are analyzed and adaptive slicing algorithms are used to optimize build speed for molds containing critical features as noted in [0205] then the monitoring the usage of the specific print mode comprises determining a number of parts comprising the particular part feature intended to be printed in the specific print mode. Regarding claim 3 and claim 4, Das modified with Gosch teaches the method of claim 1. Das teaches regions with critical features have smaller layer thicknesses than regions with non-critical features or mostly vertical walls ([0205] sections of the integral cored mold containing critical features may be sliced at approximately 25 micron layer thickness, while other regions corresponding to the platform and pour cup with non-critical features or mostly vertical walls may be sliced at approximately 100 microns or larger layer thickness). Further, Das teaches the concept of a cusp volume, which is a geometric deviation between a hemispherical part and the corresponding additive manufactured part (see Figure 56 and [0344]). The cusp volume is used to determine a % volume deviation (see algorithm 14 on pg. 27-28). A maximum volumetric deviation of 2% is used for the adaptive slicing criteria in [0358], such that the layer thickness will adapt due to the volumetric deviation percentage changing with respect to the cross- section along the part height shown in Figure 58 ([0360]). For the spherical section shown in Figure 58, the layer thickness decreases towards the top (se Figure 58 and the change in thickness after a 4 inch height in Figure 59) where this is a decreasing cross-sectional area that will cause an increase the volumetric deviation percentage. Meanwhile, the vertical cylindrical cross-section has a larger maximum layer thickness since the volume deviation is zero ([0359]). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the method of Das modified with Gosch further comprise identifying the particular part feature by selecting a feature with a cross sectional area below a threshold size, since Das teaches that layer thicknesses are varied to maintain the volumetric deviation below a threshold, where the volumetric deviation increases as a decrease in cross-sectional area is observed. Implementing the adaptive slicing methods of Das using thinner layers in regions of the part containing critical features and thicker layers elsewhere has a benefit of increasing the part build rate that results in a 25-30% cost savings per part ([0208] Calculations further reveal that by implementing adaptive slicing to use thinner layers (e.g., approximately 25-75 micrometers) in regions of the part containing critical features and thicker layers (e.g., approximately 250 micrometers) elsewhere, the part build rate may be increased to at least approximately 90 parts per hour, resulting in a cost savings of approximately 25-30% per part). Regarding claim 5, Das modified with Gosch teaches the method of claim 1. Further, Das teaches wherein the specific print mode comprises print parameters for generating the particular part feature ([0203] Software algorithms may also adaptively adjust the exposure dose in real-time as a function of slice layer thickness to achieve the necessary full cure depth through the layer thickness regardless of the layer thickness and [0205] For example, sections of the integral cored mold containing critical features may be sliced at approximately 25 micron layer thickness, while other regions corresponding to the platform and pour cup with non-critical features or mostly vertical walls may be sliced at approximately 100 microns or larger layer thicknes). Regarding claim 6, Das modified with Gosch teaches the method of claim 5. Further, Das teaches thickness variations for printing particular features in [0205] and that the layers are created by coating a photosensitive medium with a corresponding thickness on top of previously built layers ([0188] The material recoating system 600—which for illustration purposes is shown as a wire-wound draw-down bar—sweeps uniform thickness layers of the photosensitive medium at high speeds across the interior of the material build platform 500, without disturbing the previously built layers and [0192] Thinner layers of the photosensitive medium may be created when the dimensions of a feature of the three-dimensional object require so. Similarly, when the dimensions of a feature of the three-dimensional object are large, thicker layers of the photosensitive medium may be used. In an exemplary embodiment, the overall dimensions of the overall build volume 510 may be approximately 24 inches (×) by 24 inches (Y) by 16 inches (Z) (24″×24″×16″)). Given that the thickness of the photosensitive medium corresponds to an overall volume of the photosensitive medium, then the amount of a print agent to be applied to a build material when generating the particular part feature will be a print parameter when the thickness is varied. Claim(s) 7-11, 21, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Das et al. (US20160221262) and Gosch et al. (US20180178451), and further in view of Yaw et al. (US20180093417). Regarding claim 7, Das modified with Gosch teaches the method of claim 1. Further, Gosch teaches the determining step where the print job is authorized extracts a characteristic of a part and authorizes the print job based on the characteristic (a second step M2 of the distributed validation network validating the printing specification data and data the data to a print history log; see [0052] and [0055] If all of the manufacturing stages of the generative manufacturing process have been released by the distributed validation network 13, i.e. if the finished component has been validated in its entirety, a certificate, regarding successful validation of the generative manufacturing process, can be created for the additively manufactured component B in a step M7 by a certification point 1). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the determining step of Das modified with Gosch where the print job is authorized to use the specific print mode to comprise extracting a characteristic of the plurality of parts, such that authorization of the print job to use the specific print mode is determined based on the characteristic, for the benefit of avoiding user-defined discrepancies in product requirements that can result in qualitatively inferior end products. However, Das modified with Gosch fails to teach the characteristic is extraction for a sub-plurality of the plurality of parts. In the same field of endeavor pertaining to additive manufacturing, Yaw teaches a characteristic from a sub-plurality of a plurality of parts is extracted ([0021] In some embodiments, the priority for a 3D object may be determined based, at least in part, on an amount of time it takes to manufacture the 3D object. For example, the priority for a 3D object may be determined based on a printing time of the printer tray that will be used to print the 3D object and [0034] (1) access information specifying multiple 3D objects to be printed using one or more 3D printers (e.g., from a pool of 3D objects to be printed, which for example, may be maintained in a data source part of or communicatively coupled to system 202); (2) determine a priority for each of multiple 3D objects to obtain determined 3D object priorities; (3) assign, based on the determined 3D object priorities, a subset of the multiple 3D objects to a printer tray for the 3D printer; and (4) obtain a packing plan indicating an arrangement of the subset of the 3D objects within the printer tray). Extracting a characteristic from a sub-plurality of a plurality of parts is extracted allows for the parts within the plurality of parts to be prioritized such that parts are printed according to priority ([0017]). Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the characteristic of Das modified with Gosch be extracted for a sub-plurality of the plurality of parts, as taught by Yaw, for the benefit of assigning a priority to individual prints such that higher priority parts are printed sooner. Regarding claim 8, Das modified with Gosch and Yaw teaches the method of claim 7. Further, Yaw teaches wherein the characteristic comprises part descriptors of individual parts of the sub-plurality of the plurality of parts ([0035] system 202 may provide system 206 with information about the objects assigned to a printer tray (e.g., information specifying the geometric characteristics of the objects such as, for example, their sizes, dimensions, 3D object models, etc.), and system 206 may determine an arrangement in which the 3D objects are to be printed within the printer tray and provide the determined arrangement to system 202. The system 206 may determine the arrangement in which the 3D objects are to be printed within the printer tray in any suitable way. For example, in some embodiments, system 206 may determine the arrangement in which the 3D objects are to be printed using software for determining the packing of objects in a volume such as, for example, AUTODESK® NETFABB®). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the characteristic of Das modified with Gosch and Yaw comprise part descriptors of individual parts of the sub-plurality of the plurality of parts, as taught by Yaw, for the benefit of optimizing the placement of parts in a printing space (see [0039] of Yaw). Regarding claim 9, Das modified with Gosch and Yaw teaches the method of claim 8. Further, Yaw teaches wherein each part descriptor is information relative to a bounding box enclosing the part and information relative to a shape of the part ([0049] Any suitable information for a 3D object may be accessed at act 402. For example, information accessed for a 3D object may include information about the shape of a 3D object including, but not limited to, information indicating the size of the object, information indicating dimensions of the object, information indicating dimensions of a bounding box that contains the 3D object, a 3D model of the 3D object, or any suitable combination thereof). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have each part descriptor of Das modified with Gosch and Yaw be information relative to a bounding box enclosing the part and information relative to a shape of the part, as taught by Yaw, for the benefit of optimizing the placement of parts in a printing space (see [0039] of Yaw). Regarding claim 10, Das modified with Gosch and Yaw teaches the method of claim 7. Further, Yaw teaches wherein the characteristic comprises at least one job descriptor that is dependent on a combination formed by the sub-plurality of the plurality of parts ([0035] The system 206 may determine the arrangement in which the 3D objects are to be printed within the printer tray in any suitable way. For example, in some embodiments, system 206 may determine the arrangement in which the 3D objects are to be printed using software for determining the packing of objects in a volume such as, for example, AUTODESK® NETFABB®). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the characteristic of Das modified with Gosch and Yaw comprise at least one job descriptor that is dependent on a combination formed by the sub-plurality of the plurality of parts, as taught by Yaw, for the benefit of optimizing the placement of parts in a printing space (see [0039] of Yaw). Regarding claim 11, Das modified with Gosch and Yaw teaches the method of claim 10. Further, Yaw teaches wherein each job descriptor is a total parts number and a parts packing density ([0035] The system 206 may determine the arrangement in which the 3D objects are to be printed within the printer tray in any suitable way. For example, in some embodiments, system 206 may determine the arrangement in which the 3D objects are to be printed using software for determining the packing of objects in a volume such as, for example, AUTODESK® NETFABB®). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the job descriptor of Das modified with Gosch and Yaw be a total parts number and a parts packing density, as taught by Yaw, for the benefit of optimizing the placement of parts in a printing space (see [0039] of Yaw). Regarding claim 21, Das modified with Gosch and Yaw teaches the method of claim 7. Further, Gosch teaches wherein determining that the print job is authorized to use the specific print mode further comprises: computing a fingerprint for the print job from the characteristic; and comparing the computed fingerprint to a list of certified fingerprints associated with the specific print mode, wherein the print job is authorized when the computed fingerprint is found in the list of certified fingerprints ([0058] The actual printing process E3 begins thereafter, during the course of which process the 3D printing device 10 periodically sends back information, regarding the printing parameters used in the previous stage in each case, to the distributed validation network 13 for revalidation, i.e. for matching to the printing specification data. In the process, the printing parameters that are sent are in each case matched, for conformity, to the original printing specification data. The distributed validation network 13 can create a print history log (“ledger”) in which both the printing specification data and some or all of the printing parameters that are sent back in each case for the purpose of validation are stored in a concatenated manner in blocks. Cryptographic checksums can be used for this purpose, for example hash values that are formed in accordance with a hash function by a combination of data to be newly entered and the hash value of the preceding block as the hash argument and [0059] Following the step-by-step validation of the printing process E3, a completion message E4 is sent to the print job entity 11 upon successful completion. Said entity can in turn verify the correctness of the printing process E3 in a step E5. Subsequently, in a certification process E6, a certificate can optionally be requested from a certification point 12, and this can be stored, in a documentation process E7, as a block in the print history log in a similar manner to the rest of the information. All the information entered in the print history log is sorted chronologically and archived by means of the cryptographic checksums so as to be almost unmanipulable). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the determining that the print job is authorized to use the specific print mode of Das modified with Gosch and Yaw further comprise computing a fingerprint for the print job from the characteristic and comparing the computed fingerprint to a list of certified fingerprints associated with the specific print mode, wherein the print job is authorized when the computed fingerprint is found in the list of certified fingerprints, as taught by Gosch, for the benefit of avoiding user-defined discrepancies in product requirements that can result in qualitatively inferior end products. Regarding claim 22, Das modified with Gosch and Yaw teaches the method of claim 21. Further, Gosch teaches wherein computing the fingerprint comprises: sorting the parts into an ordered list; defining an identification string by concatenating individual characteristics of the sub-plurality of the plurality of parts following the ordered list; and determining a checksum from the identification string, as the computed fingerprint ([0058] In the process, the printing parameters that are sent are in each case matched, for conformity, to the original printing specification data. The distributed validation network 13 can create a print history log (“ledger”) in which both the printing specification data and some or all of the printing parameters that are sent back in each case for the purpose of validation are stored in a concatenated manner in blocks. Cryptographic checksums can be used for this purpose, for example hash values that are formed in accordance with a hash function by a combination of data to be newly entered and the hash value of the preceding block as the hash argument). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the computing the fingerprint of Das modified with Gosch and Yaw comprise sorting the sub-plurality of the plurality of parts into an ordered list, defining an identification string by concatenating individual characteristics of the sub-plurality of the plurality of parts following the ordered list, and determining a checksum from the identification string, as the computed fingerprint, as taught by Yaw, for the benefit of avoiding user-defined discrepancies in product requirements that can result in qualitatively inferior end products. Claim(s) 13 is rejected under 35 U.S.C. 103 as being unpatentable over Das et al. (US20160221262) and Gosch et al. (US20180178451), and further in view of Chu et al. (US20220244704). Regarding claim 13, Das modified with Gosch teaches the method according to claim 1. While Das teaches that method of printing can have a wide range of applications extending beyond turbine airfoils ([0214] While reference was made herein to turbine airfoil molds, the embodiments of the present invention have wide-ranging applications beyond turbine airfoils. The embodiments disclosed herein allow for the design and manufacture of components that would otherwise be difficult or impossible to manufacture conventionally), further fails to teach wherein the plurality of parts is a plurality of brushes, and the particular part feature is a brush bristle. In the same field of endeavor pertaining a method for additive manufacturing, Chu teaches the part is a brush and the particular part feature is a brush bristle([0185]). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have the plurality of parts of Das be a plurality of brushes, and for the particular feature of Das to be a brush bristle, as taught by Chu, to achieve the predictable result of manufacturing three-dimensional components with regions corresponding to critical features with fine precision and other regions with non-critical features. There would have been a reasonable expectation of success for the method of Das to form brush bristles, since both Das and Chu use light modulating technology (Chu teaches in [0004] the inventors appreciate that high resolution stereolithography 3D printing, specifically Digital Light Processing (DLP) printing technology may be used that allows printing resolution of less than 100 μm and Das teaches in [0180] The projection lens 230 reduction ratio may be between approximately 1 and approximately 50, which may result in a minimum feature size between approximately 15 microns and approximately 0.3 microns) to achieve micron-scale printing resolutions. The bristles of Chu have diameters on the order of 100 μm ([0018] According to one embodiment, the bristles have a diameter that is less than about 100 μm), and provided that the system of Das has a minimum feature size between approximately 15 microns and approximately 0.3 microns, then the system of Das would be capable of printing the bristles of Chu. Response to Arguments Applicant’s arguments with respect to claim(s) 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARIELLA MACHNESS whose telephone number is (408)918-7587. The examiner can normally be reached Monday - Friday, 6:30-2:30 PT. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Galen Hauth can be reached at 571-270-5516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ARIELLA MACHNESS/Examiner, Art Unit 1743
Read full office action

Prosecution Timeline

Sep 23, 2023
Application Filed
Jun 05, 2025
Non-Final Rejection mailed — §103
Nov 04, 2025
Response Filed
Jan 12, 2026
Final Rejection mailed — §103
Apr 10, 2026
Request for Continued Examination
Apr 13, 2026
Response after Non-Final Action
May 05, 2026
Non-Final Rejection mailed — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
62%
Grant Probability
90%
With Interview (+28.9%)
2y 11m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 169 resolved cases by this examiner. Grant probability derived from career allowance rate.

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