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 1-10 in the reply filed on 07/28/26 is acknowledged.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-2 and 4-10 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2 and 4-10 of copending Application No. 20250276374 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because 2025027637 teaches each and every limitations.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Claim Rejections - 35 USC § 102
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 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.
Claim(s) 1-4 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nelson et al. (PG/PUB 20230091046).
Claim 1.
Nelson teaches an additive manufacturing system (ABSTRACT, summary of invention), comprising:
an energy delivery device configured to deliver energy to a build surface of a component to form a melt pool in the build surface of the component (0074-75 e.g. “Similarly, one or more computing devices 12 may be configured to control energy delivery device 16 to deliver energy 34 to first layer 24 to establish a given heat input (see bottom left of FIG. 7 ). For example, one or more computing device 12 may control one or more operating parameters of energy delivery device 16, such as intensity, pulse rate, pulse width, or the like; one or more positional parameters related to energy delivery device 16, such as dwell time at a location, a movement rate relative to first layer 24, an overlap between adjacent passes of energy 34 across first layer 24, a pause time between adjacent passes of energy 34 across first layer 24, or the like to control heat input to system 10 (e.g., to melt pool 32 and component 22).”)
a powder delivery device configured to direct a powder stream toward the melt pool (0071 e.g. “One or more computing devices 12 may be configured to receive data from one or more mass flow monitoring sensors, including PFMS 18, powder flow mass sensor 44, and/or topology sensor 48. Data received from powder flow mass sensor 44 indicates a mass flow of powder from powder source 42 to powder delivery device. Data from PFMS 18 indicates a mass flow of powder in powder stream 30 between powder delivery device 14 to adjacent melt pool 32. Data from topology sensor 48 indicates powder mass captured by melt pool 32 and added to component 22.”)
at least one sensor configured to generate powder data (0071-73 e.g. “One or more computing devices 12 may be configured to receive data from one or more mass flow monitoring sensors, including PFMS 18, powder flow mass sensor 44, and/or topology sensor 48. Data received from powder flow mass sensor 44 indicates a mass flow of powder from powder source 42 to powder delivery device. Data from PFMS 18 indicates a mass flow of powder in powder stream 30 between powder delivery device 14 to adjacent melt pool 32. Data from topology sensor 48 indicates powder mass captured by melt pool 32 and added to component 22.”)
a computing device configured to:
receive the powder data from the at least one sensor (0071-73 e.g. “One or more computing devices 12 may be configured to receive data from one or more mass flow monitoring sensors, including PFMS 18, powder flow mass sensor 44, and/or topology sensor 48. Data received from powder flow mass sensor 44 indicates a mass flow of powder from powder source 42 to powder delivery device. Data from PFMS 18 indicates a mass flow of powder in powder stream 30 between powder delivery device 14 to adjacent melt pool 32. Data from topology sensor 48 indicates powder mass captured by melt pool 32 and added to component 22.”)
determine, based on the powder data, at least one particle characteristic (0051-54 e.g. “PFMS 50 may include a computing device (e.g., computing device 12 of FIG. 1 ) configured to analyze images captured by imaging device 62 to identify a number of particle detections in each captured image and, optionally, derive further parameters from the number of particle detections. As such, computing device 12 may be configured to receive image data representing an image captured by imaging device 62. The image data may include representations of illuminated powder of powder stream 58, as imaged by imaging device 62 (e.g., as captured in an image frame by imaging device 62). Computing device 12 may be configured to generate a representation of powder stream based on the image data and output the representation of the powder stream for display at a display device.”)
generate a signal indicative of the at least one particle characteristic (0051-54 e.g. “For instance, computing device 12 may be configured determine a powder mass flow represented by the image data. To do so, computing device 12 may be configured to identify a number of powder particles within each image frame. In some examples, computing device 12 additionally may be configured to identify a size and/or shape of each powder particle within each image frame. Computing device 12 may be configured to implement any suitable image analysis technique to identify powder particles, and, optionally, size and/or shape of powder particles.”)
control, based on the at least one particle characteristic, the energy delivery device and the powder delivery device to deposit a plurality of layers based on a set of deposition parameters (0043, 0071-76 e.g. “Further, one or more computing devices 12 may determine an overall mass flux using the data received from PFMS 18, powder flow mass sensor 44, and/or topology sensor 48. One or more computing devices 12 then may use the overall mass flux as an input to the control algorithm used to control the powder feed rate output by powder source 42 (see top left of FIG. 7 ,” see also “In some examples, one or more computing devices 12 also may use the deposit topology (captured powder mass) and/or capture efficiency metric in the determination of the heat flux, as the added powder mass and quench effects associated with the captured powder affect the cooling rate.”)
Claim 2.
The additive manufacturing system of claim 1, wherein the at least one sensor comprises at least one of an acoustic sensor, a laser diffraction sensor, a high-speed imaging sensor, a magnetic sensor, or an organic sensor (0046, 0068 e.g. “Returning to FIG. 5 , system 10 also includes melt pool monitor (“MP monitor”) 82. Melt pool monitor 82 may include a sensor for monitoring a characteristic of melt pool 32. The sensor may include an imaging system, such as a visual or thermal camera, e.g., camera to visible light or infrared (IR) radiation. A visible light camera may monitor the geometry of the melt pool, e.g., a width, diameter, shape, or the like. A thermal (or IR) camera may be used to detect the size, temperature, or both of the melt pool. In some examples, a thermal camera may be used to detect the temperature of the melt pool at multiple positions within the melt pool, such as a leading edge, a center, and a trailing edge of the melt pool. In some examples, the imaging system may include a relatively high speed camera capable of capturing image data at a rate of tens or hundreds of frames per second or more, which may facilitate real-time detection of the characteristic of the melt pool.”)
Claim 3.
The additive manufacturing system of claim 1, wherein the at least one particle characteristic comprises at least one of a mass-averaged particle size, a volume-averaged particle size, a particle size distribution, a particle morphology, a particle composition, a particle contaminant concentration, or a particle inclusion size (0050-54 e.g. see particle distribution - “For instance, computing device 12 may be configured determine a powder mass flow represented by the image data. To do so, computing device 12 may be configured to identify a number of powder particles within each image frame. In some examples, computing device 12 additionally may be configured to identify a size and/or shape of each powder particle within each image frame. Computing device 12 may be configured to implement any suitable image analysis technique to identify powder particles, and, optionally, size and/or shape of powder particles.”)
Claim 4.
The additive manufacturing system of claim 1, wherein the computing device is further configured to determine at least one deposit quality metric or at least one abnormal event based on the at least one particle characteristic (0007, 0035-0042 e.g. see topology as a deposit quality metric and/or powder flow e.g. “System 10 further includes a topology sensor 48. Topology sensor 48 is configured to monitor an amount of powder captured by melt pool 32 by imaging melt pool 32 and the added material, allowing the mass to be quantified (e.g., by computing device 12) using the dimensions of the added material and density of the material (powder). In some examples, topology sensor 48 includes a laser and a sensor (e.g., an imaging device), which senses laser light reflected by the structure being imaged (e.g., melt pool 32 and the added material). The laser may have a defined wavelength, which may affect the resolution of the topology sensor 48. In some examples, the wavelength and sensor may be selected such that the resolution of topology sensor 48 is a great as about 10 microns (e.g., about 6 microns).”)
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 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 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(s) 5-7 and 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view over Nelson (PG/PUB 20230090298).
Claim 5.
The additive manufacturing system of claim 4 but does not expressly teach the abnormal event limitations described below. Nelson teaches the abnormal event limitations described below
wherein the at least one abnormal event comprises at least one of powder contamination, powder agglomeration, powder segregation, or a deviation of the at least one particle characteristic beyond a predetermined threshold value or a predetermined range (0093 e.g. As shown in FIG. 13 , the powder range and standard deviation may change in response to powder agglomeration (e.g., a clog). Similarly, powder range and standard deviation may change in response to nozzle wear or damage. For instance, a clog, agglomeration, or nozzle wear or damage may cause an increase in powder range and standard deviation (as suggested by FIGS. 11 and 12 ). This may enable computing device 12 or an operator of computing device 12 to detect a clog, agglomeration, or nozzle wear or damage rapidly after the clog, agglomeration, or nozzle wear or damage occurs.
One of ordinary skill in the art before the effective filing date of the claimed invention applying the teachings of Nelson, namely adjusting control parameters based on comparing powder characteristics to thresholds to determine an abnormal condition, to the teachings of Nelson, namely identifying particle characteristics for control, would achieve an expected and predictable result via combining said elements using known methods.
Claim 6.
The additive manufacturing system of claim 4, but does not teach the process response described below. Nelson teaches the process response described below
wherein the computing device is further configured to determine at least one process response based on the at least one particle characteristic (Nelson, 0100, 0034-35 e.g. “one or more computing devices 12 may be configured to determine that the at least one metric indicates the abnormal state in response to the comparison showing differences between the metrics above a threshold difference value. For instance, with reference to FIG. 12 , one or more computing devices 12 may compare a powder mass flux associated with quadrant 1 to powder mass fluxes associated with quadrants 2, 3, and 4, may compare a powder mass flux associated with quadrant 2 to powder mass fluxes associated with quadrants 3 and 4, and may compare a powder mass flux associated with quadrant 3 to powder mass fluxes associated with quadrant 4, such that each powder mass flux is compared to each other powder mass flux. In the example of FIG. 11 , the powder mass fluxes for quadrants 1 and 4 differ from the powder mass fluxes for quadrants 2 and 3, and may differ by more than a threshold difference value. This may indicate an abnormal state. As a counter example, the mass fluxes for each of the quadrants shown in FIG. 8A are substantially similar and may not differ by more than a threshold difference value. This may indicate a normal state.”)
One of ordinary skill in the art before the effective filing date of the claimed invention applying the teachings of Nelson, namely adjusting control parameters based on comparing powder characteristics to thresholds to determine an abnormal condition, to the teachings of Nelson, namely identifying particle characteristics for control, would achieve an expected and predictable result via combining said elements using known methods.
Claim 7.
The additive manufacturing system of claim 6, wherein the computing device is further configured to determine the at least one quality metric by comparing the process response with a threshold response value (Nelson, 0100 e.g. “one or more computing devices 12 may be configured to determine that the at least one metric indicates the abnormal state in response to the comparison showing differences between the metrics above a threshold difference value. For instance, with reference to FIG. 12 , one or more computing devices 12 may compare a powder mass flux associated with quadrant 1 to powder mass fluxes associated with quadrants 2, 3, and 4, may compare a powder mass flux associated with quadrant 2 to powder mass fluxes associated with quadrants 3 and 4, and may compare a powder mass flux associated with quadrant 3 to powder mass fluxes associated with quadrant 4, such that each powder mass flux is compared to each other powder mass flux. In the example of FIG. 11 , the powder mass fluxes for quadrants 1 and 4 differ from the powder mass fluxes for quadrants 2 and 3, and may differ by more than a threshold difference value. This may indicate an abnormal state. As a counter example, the mass fluxes for each of the quadrants shown in FIG. 8A are substantially similar and may not differ by more than a threshold difference value. This may indicate a normal state.”)
“
Claim 9. The additive manufacturing system of claim 4 but does expressly teach adjusting the powder control limitations described below. Nelson teaches adjusting the powder control limitations described below
wherein the computing device is further configured to adjust at least one powder control parameter based on the at least one deposit quality metric or the at least one abnormal event (Nelson, 0032-33 e.g. “ In some implementations, the computing device may be configured to control the blown powder additive manufacturing technique based on the image data. For instance, upon detecting a clog, the computing device may be configured to cause the powder delivery device to be cleaned, e.g., using a temporary high flow rate of gas though the powder delivery device, through mechanical cleaning of the powder delivery device, or the like. As another example, the computing device may be configured to compare a measured parameter, such as a measured particle detections, a measured mass flow rate, a measured detection or mass flow distribution, or the like to a setpoint or set range. Upon determining that the measured parameter deviates from the setpoint or set range, the computing device may control one or more process variables (e.g., mass flow of powder from a powder source, process gas flow rate, or the like) supra claim 1 Nelson 0015 e.g. “The properties of the final component, including the presence or absence of material defects and the resulting microstructure, are a function of a number of variables related to mass flux and heat flux. As such, measurement of mass flux and heat flux within the blown powder additive manufacturing system may enable characterization or prediction of final component properties, control of the blown powder additive manufacturing technique, quality assurance for the final component, development of new blown powder additive manufacturing techniques, and the like.,”
One of ordinary skill in the art before the effective filing date of the claimed invention applying the teachings of Nelson, namely adjusting control parameters based on comparing powder characteristics to thresholds to determine an abnormal condition, to the teachings of Nelson, namely identifying particle characteristics for control, would achieve an expected and predictable result via combining said elements using known methods.
Claim 10. The additive manufacturing system of claim 9, wherein the at least one powder control parameter comprises at least one of a powder feed rate, a powder feeder source, a powder feeder type, a powder flow rate, a carrier gas flow rate, a carrier gas pressure, a center purge flow rate, or a center purge pressure (0033 e.g. “ In some implementations, the computing device may be configured to control the blown powder additive manufacturing technique based on the image data. For instance, upon detecting a clog, the computing device may be configured to cause the powder delivery device to be cleaned, e.g., using a temporary high flow rate of gas though the powder delivery device, through mechanical cleaning of the powder delivery device, or the like. As another example, the computing device may be configured to compare a measured parameter, such as a measured particle detections, a measured mass flow rate, a measured detection or mass flow distribution, or the like to a setpoint or set range. Upon determining that the measured parameter deviates from the setpoint or set range, the computing device may control one or more process variables (e.g., mass flow of powder from a powder source, process gas flow rate, or the like) and re-measure the measured parameter until computing device determines that the….
“)
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view over Nelson (PG/PUB 20230090298) in view over Wilson (PG/PUB 20150261196)
Claim 8. The additive manufacturing system of claim 6 but does not expressly teach the response described below. Wilson teaches the response described below
wherein the at least one process response comprises at least one of a build quality, a build height, or a layer thickness (0019-20, 0046 e.g. “For example, if the layer thickness is less than the desired thickness at a location, more powder than expected may be present at that location than would be present if the layer thickness was as desired. When energy is delivered to heat the powder at that location, the amount of energy may be insufficient to sinter or melt all of the powder (due to the excess amount), which may lead to porosity, lack of fusion, or the like.”)
One of ordinary skill in the art before the effective filing date of the claimed invention applying the teachings of Wilson, namely adjusting control parameters based on a process response including at least layer accumulation, to the teachings of Nelson, namely identifying particle characteristics for control, would achieve an expected and predictable result via combining said elements using known methods.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
11185925 e.g. “A process abnormality detection system for a three-dimensional additive manufacturing device which performs additive modeling by emitting a beam to a powder bed determines that a laying abnormality of the powder bed is occurring if at least one of a first condition that an average height of the powder bed from a reference position is out of a first predetermined range or a second condition that a height variation of the powder bed is out of a second predetermined range is satisfied, on the basis of a detection result of a shape measurement sensor.”)
20230089809 -0103 e.g. “The at least one action may depend on the abnormal state indicated by the at least one metric. For instance, if the at least one metric indicates a powder mass flux that is lower than a set powder mass flux, one or more computing devices 12 may be configured to cause a powder feed rate to nozzles 56 to increase, e.g., by increasing a carrier gas flow rate through a powder source, increasing a powder agitation rate within the powder source to entrain more powder in the carrier gas, or the like. Alternatively, if the at least one metric indicates a powder mass flux that is lower than a set powder mass flux for a single nozzle, one or more computing devices 12 may be configured to cause a powder feed rate to the single nozzle to increase, e.g., by controlling a valve associated with the single nozzle to open further and permit greater powder flow to the single nozzle”)
20220212266 – 0084 , see abnormal powder amounts
20210331399-0043, see detecting surface uniformities , see also 20210162505- ABSTRACT
11724315 e.g. “Referring to FIGS. 1 and 16, in some embodiments, the defect analysis subsystem 18 can further include a database 40 including a plurality of defect profiles 42 and corresponding suggested correction parameters 24 for each defect profile 42, and when the defect analysis subsystem 18 determines that a defect 22 requires correction, the defect analysis subsystem 12 can be operable to select one of the defect profiles 42 in the database 40 that is an approximation of the detected defect 22 and include the suggested correction parameters 24 corresponding to the selected defect profile 42 in the correction command 20 sent to the additive manufacturing device 12. Having a database 40 including readily available correction parameters 24 for corresponding defect profiles 42 can allow optimal laser correction parameters 24 to be quickly determined based on a detected size and geometry of any void or defect. Other AM parameters (e.g. powder layer thickness, spot size) can remain fixed in some embodiments, or can also be adjustable and vary between different repair processes. In some embodiments, correction parameters 24 can be set for each defect profile 42 such that each set of parameters has nominal energy density between about 50% and about 150%. Nominal energy density outside of this range has proven to result in high porosity in the resulting product.”)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DARRIN D DUNN whose telephone number is (571)270-1645. The examiner can normally be reached M-Sat (10-8) PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Fennema can be reached at 571-272-2748. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DARRIN D DUNN/Patent Examiner, Art Unit 2117
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