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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Response to Amendment
Applicant’s amendment filed on 18 April 2026 has been entered. Claims 1, 7, 34, and 100 are amended. Claim 134 has been canceled. Claim 135 has been added. Claims 1, 2, 7, 16-19, 22-31, 34, 100, and 135 are pending.
Applicant’s arguments, filed 18 April 2026, with respect to the rejection(s) of Claims 1, 2, 7, 16-18, 30, 31, 34, 100, and 134 under 35 U.S.C. § 103 for being unpatentable over Seurat (US 2017/10232515) and Siemens (WO 2017/174160) with reference made to equivalent US 2020/0398379 have been fully considered and are persuasive.
Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Collins et al. (US 20200327267).
Applicant’s arguments with respect to the rejection(s) of Claims above 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.
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.
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.
Claims 1, 2, 7, 16-18, 30, 31, 34, 100, and 135 are rejected under 35 U.S.C. 103 as being unpatentable over US 201710232515 (Seurat Technologies, Inc) in view of WO 2017174160 (SIEMENS AKTIENGESELLSCHAFT) with reference made to equivalent US 20200398379, and further in view of Collin et al. (hereafter Collin – US 20200327267).
Claim 1 recites “a method.” Seurat Technologies, Inc teaches such a method, as will be shown.
Seurat Technologies, Inc teaches a method comprising (Abstract - Manufacture of a part is simulated and compared to selected design tolerance. If the simulated manufactured part is outside selected design tolerances, simulation parameters can be adjusted until results indicate the simulated manufactured part is within selected design tolerances): processing an input signal to generate an output signal, wherein the input signal, the output signal are associated with a simulated additive manufacturing process (para [0057][0062], additive manufacturing process can be simulated using data related to the Computer Aided Design (CAD) geometry for the powder bed, material type, printer model (or printer capabilities), and desired resultant material properties such as stress distribution, thermal warpage, or crystal structure); adjusting the input signal based on comparing the output signal to a reference signal (para 0058-0062, 0069-0070: Simulation results can be compared to a part material specification, and power flux, dwell time, and print order along with other geometrical parameters such as part orientation, support structure, and part topology can be adjusted in the simulated machine and the simulation repeated); thereafter processing the input signal to generate the output signal (para 0058-0062: the simulation repeated). Seurat Technologies, Inc does not teach using a finite element model (FEM) associated with a simulated additive manufacturing process. However, SIEMENS AKTIENGESELLSCHAFT teaches using a finite element model (FEM) associated with a simulated additive manufacturing process (Abstract; page 2 and 8 - processor uses data describing the geometry of the building structure in order to generate a network of finite elements; the processor or the processor corresponding to this processor has a temperature distribution in the irradiation tracks by a finite Element method calculated; simulation). It would have been obvious to one of ordinary skill in the art to combine the additive manufacturing optimization as taught by Seurat Technologies, Inc with the finite element modeling as taught by SIEMENS AKTIENGESELLSCHAFT since doing so would prevent insufficient reliability and undesirable in-process variations.
However, modified Seurat Technologies, Inc does not teach wherein processing the input signal to generate the output signal comprises processing a first value of the input signal that corresponds to a first time interval to generate a second value of the output signal that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval.
Collins teaches a method (Figs. 27-30) comprising processing an input signal using a finite element model (FEM) to generate an output signal associated with a simulated additive manufacturing process (abstract) wherein processing the input signal to generate the output signal (see Fig. 28 and para. 0143-0145) comprises processing a first value of the input signal (see example of Fig. 28, first feed rate) that corresponds to a first time interval to generate a second value of the output signal (molten state location, temperature), that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal (new feed rate) that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval (see Fig. 28, restarting after step 2840).
Collins further teaches that using such an FEM associated with a simulated additive manufacturing can be used to predict and improve the additive manufacturing end product composition while avoiding trial and error procedures, which can reduce efficiency of the manufacturing process (para. 0130, 0134).
It would have been obvious for a person having ordinary skill in the art to apply the teachings of Collins to the method of modified Seurat Technologies, Inc to have processing the input signal to generate the output signal comprises processing a first value of the input signal that corresponds to a first time interval to generate a second value of the output signal that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval, as the references and applicant’s invention are directed to methods for additive manufacturing. Doing so would result in faster and improved additive manufacturing product composition, as recognized by Collins.
Regarding Claim 2, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 1, wherein the input signal represents a powder flow rate or one or more of a power setting for an energy beam, a scan speed for the energy beam, a target location for the energy beam, or a heating time for the energy beam (para. 0055-0057).
Regarding Claim 7, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 1, wherein the output signal represents one or more of a width of a melt pool, an area of the melt pool, a volume of the melt pool, an average temperature of the melt pool, a shape of the melt pool, a peak temperature of the melt pool, a depth of a melt pool, a thermal stress of a material, a liquid flow velocity of the material, a temperature of the material, or a porosity of a manufactured component (SIEMENS AKTIENGESELLSCHAFT para. 0010-0011- thermal stress, temperature).
Regarding Claim 16, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 1, wherein processing the input signal using the FEM comprises using the input signal to numerically determine temperature, stress, and/or fluid flow of respective positions within a powder bed after an energy beam has been applied to the powder bed according to the input signal (SIEMENS AKTIENGESELLSCHAFT para. 0024-0025: thermal stress, temperature after energy beam applied).
Regarding Claim 17, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 1, wherein adjusting the input signal comprises adjusting the input signal based on an error signal representing a difference between the output signal and the reference signal (SIEMENS AKTIENGESELLSCHAFT par. 0068-0071: corrected data is produced by accounting for difference in signals).
Regarding Claim 18, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 17, wherein adjusting the input signal comprises processing the error signal using a baseline control algorithm (SIEMENS AKTIENGESELLSCHAFT par. 0041: geometry of the construction can be corrected in such a way that a form deviation in the structure in the opposite direction to the calculated form deviation is provided).
Regarding Claim 30, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 1, further comprising: adjusting time-dependent input signals for a real additive manufacturing process by evaluating results of the simulated additive manufacturing process; and performing the real additive manufacturing process using the time-dependent input signals (SIEMENS AKTIENGESELLSCHAFT para. 0045 processor bases a calculation of the resultant stresses and form deviations on a time-dependent continuous temperature curve T.sub.l(t) in the relevant layer).
Regarding Claim 31, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 30, further comprising: performing the simulated additive manufacturing process in one or more simulated experiments; and confirming that output variations of the one or more simulated experiments do not exceed a threshold value, wherein performing the real additive manufacturing process comprises performing the real additive manufacturing process based on confirming that the output variations of the one or more simulated experiments do not exceed the threshold value (SIEMENS AKTIENGESELLSCHAFT para. 0046-0047 real conditions kept within boundaries/acceptable limits, i.e. threshold value).
Claim 34 recites a computer readable medium storing instructions. Seurat Technologies, Inc teaches such a computer readable medium storing instructions as will be shown.
Seurat Technologies, Inc teaches a computer readable medium storing instructions that, when executed by a computing device, cause the computing device to perform functions comprising (Abstract; para (0070]): processing an input signal to generate an output signal, wherein the input signal, the output signal are associated with a simulated additive manufacturing process (para 0057-0062, 0069-0070, additive manufacturing process can be simulated using data related to the Computer Aided Design (CAD) geometry for the powder bed, material type, printer model (or printer capabilities), and desired resultant material properties such as stress distribution. thermal warpage, or crystal structure); adjusting the input signal based on comparing the output signal to a reference signat (para 0058- 0069-0070,006 Simulation results can be compared to a part material specification, and power flux, dwell time, and print order along with other geometrical parameters such as part orientation, support structure, and part topology can be adjusted in the simulated machine and the simulation repeated); thereafter processing the input signal generate the output signal (para. 0058-0062). Seurat Technologies, Inc does not teach using a finite element model (FEM) associated with a simulated additive manufacturing process. However, SIEMENS AKTIENGESELLSCHAFT teaches using a finite element model (FEM) associated with a simulated additive manufacturing process (Abstract; page 2 and 8 - processor uses data describing the geometry of the building structure in order to generate a network of finite elements; the processor or the processor corresponding to this processor has a temperature distribution in the irradiation tracks by a finite Element method calculated; simulation). It would have been obvious to one of ordinary skill in the art to combine the additive manufacturing optimization as taught by Seurat Technologies, Inc with the finite element modeling as taught by SIEMENS AKTIENGESELLSCHAFT since doing so would prevent insufficient reliability and undesirable in-process variations.
However, modified Seurat Technologies, Inc does not teach wherein processing the input signal to generate the output signal comprises processing a first value of the input signal that corresponds to a first time interval to generate a second value of the output signal that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval.
Collins teaches a method (Figs. 27-30) comprising processing an input signal using a finite element model (FEM) to generate an output signal associated with a simulated additive manufacturing process (abstract) wherein processing the input signal to generate the output signal (see Fig. 28 and para. 0143-0145) comprises processing a first value of the input signal (see example of Fig. 28, first feed rate) that corresponds to a first time interval to generate a second value of the output signal (molten state location, temperature), that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal (new feed rate) that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval (see Fig. 28, restarting after step 2840).
Collins further teaches that using such an FEM associated with a simulated additive manufacturing can be used to predict and improve the additive manufacturing end product composition while avoiding trial and error procedures, which can reduce efficiency of the manufacturing process (para. 0130, 0134).
It would have been obvious for a person having ordinary skill in the art to apply the teachings of Collins to the method of modified Seurat Technologies, Inc to have processing the input signal to generate the output signal comprises processing a first value of the input signal that corresponds to a first time interval to generate a second value of the output signal that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval, as the references and applicant’s invention are directed to methods for additive manufacturing. Doing so would result in faster and improved additive manufacturing product composition, as recognized by Collins.
Regarding claim 100, Seurat Technologies, Inc teaches method comprising (Abstract - Manufacture of a part is simulated and compared to selected design tolerance. If the simulated manufactured part is outside selected design tolerances, simulation parameters can be adjusted until results indicate the simulated manufactured part is within selected design tolerances): processing an input signal to generate an output signal, wherein the input signal, the output signal are associated with a simulated additive manufacturing process (para [0057][0062], 0069-0070- additive manufacturing process can be simulated using data related to the Computer Aided Design (CAD) geometry for the powder bed, material type, printer model (or printer capabilities), and desired resultant material properties such as stress distribution, thermal warpage, or crystal structure); adjusting the input signal based on comparing the output signal to a reference signal (para 0058-0062, 0069-0070- Simulation results can be compared to a part material specification, and power flux, dwell time, and print order along with other geometrical parameters such as part orientation, support structure, and part topology can be adjusted in the simulated machine and the simulation repeated); thereafter processing the input signal generate the output signal (para the simulation repeated); performing the real additive manufacturing process using the adjusted input signals (para [0068][0071]- Once a simulation is performed with sufficient accuracy, the results will typically hold for repeated machine runs; the process is complete and the resulting process parameters can be passed to the AM machine to carry out the manufacturing process). Seurat Technologies, Inc does not teach using a finite element model (FEM) associated with a simulated additive manufacturing process; adjusting time-dependent input signals for a real additive manufacturing process by evaluating results of the simulated additive manufacturing process. However, SIEMENS AKTIENGESELLSCHAFT teaches using a finite element model (FEM) associated with a simulated additive manufacturing process.(Abstract; page 2 and 8 - processor uses data describing the geometry of the building structure in order to generate a network of finite elements; the processor or the processor corresponding to this processor has a temperature distribution in the irradiation tracks by a finite Element method calculated; simulation); adjusting time-dependent input signals for a real additive manufacturing process by evaluating results of the simulated additive manufacturing process (- it is therefore advantageously possible for the processor to use a time-dependent, continuous temperature profile Ti (t) in the relevant position, which is derived from the melting temperature . Form, when calculating the resulting stresses and shape deviations runs to the mean temperature). It would have been obvious to one of ordinary skill in the art to combine the additive manufacturing optimization as taught by Seurat Technologies, Inc with the finite element modeling as taught by SIEMENS AKTIENGESELLSCHAFT since doing so would prevent insufficient reliability and undesirable in-process variations.
However, modified Seurat Technologies, Inc does not teach wherein processing the input signal to generate the output signal comprises processing a first value of the input signal that corresponds to a first time interval to generate a second value of the output signal that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval.
Collins teaches a method (Figs. 27-30) comprising processing an input signal using a finite element model (FEM) to generate an output signal associated with a simulated additive manufacturing process (abstract) wherein processing the input signal to generate the output signal (see Fig. 28 and para. 0143-0145) comprises processing a first value of the input signal (see example of Fig. 28, first feed rate) that corresponds to a first time interval to generate a second value of the output signal (molten state location, temperature), that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal (new feed rate) that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the output signal that characterizes the state of the component during the second time interval (see Fig. 28, restarting after step 2840).
Collins further teaches that using such an FEM associated with a simulated additive manufacturing can be used to predict and improve the additive manufacturing end product composition while avoiding trial and error procedures, which can reduce efficiency of the manufacturing process (para. 0130, 0134).
It would have been obvious for a person having ordinary skill in the art to apply the teachings of Collins to the method of modified Seurat Technologies, Inc to have processing the input signal to generate the output signal comprises processing a first value of the input signal that corresponds to a first time interval to generate a second value of the output signal that characterizes a state of a component during the first time interval, wherein adjusting the input signal comprises generating a third value of the input signal that corresponds to a second time interval that is after the first time interval, and processing the third value of the input signal using the FEM to generate a fourth value of the outp ut signal that characterizes the state of the component during the second time interval, as the references and applicant’s invention are directed to methods for additive manufacturing. Doing so would result in faster and improved additive manufacturing product composition, as recognized by Collins.
Regarding Claim 135, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the output signal indicates a size of a melt pool (see Collin. Para. 0055).
Claims 19, 22-26, and 29 are rejected under 35 U.S.C. 103 as being unpatentable over US 201710232515 (Seurat Technologies, Inc) in view of WO 2017174160 (SIEMENS AKTIENGESELLSCHAFT) with reference made to US 20200398379, and further in view of Collins, and further in view of US 5,394,322 (Hansen).
Regarding Claim 19, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 18.
However, modified Seurat Technologies, Inc does not teach baseline control algorithm includes a proportional-integral-derivative control algorithm, an H-infinity loop-shaping control algorithm, or a lead-lag compensator.
However, Hansen teaches adjusting an input signal comprises processing the error signal using a baseline control algorithm (Abstract; col 9, In 30 to col 10, In 20). It would have been obvious to one of ordinary skill in the art to modify the combination of Seurat Technologies, Inc and SIEMENS AKTIENGESELLSCHAFT with those of Hansen since doing so would efficiently optimize the input parameters. It would be obvious to arrive at the baseline control algorithm includes a Proportional-integral-derivative control algorithm as taught by Hansen (see col 9, In 30 to col 10, In 20).
Regarding Claim 22, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Collins in Claim 1 above, teaches the method of claim 18.
However, modified Seurat Technologies, Inc does not teach adjusting the input signal further comprises processing the error signal using a sub-algorithm of a plug-in compensation algorithm, the sub-algorithm including a first lag compensator and an inverse plant compensator, the inverse plant compensator having a first transfer function that is an inverse of a second transfer function of a nominal model of the FEM.
However, Hansen teaches adjusting an input signal comprises processing the error signal using a baseline control algorithm (Abstract; col 9, In 30 to col 10, In 20). It would have been obvious to one of ordinary skill in the art to modify the combination of Seurat Technologies, Inc and SIEMENS AKTIENGESELLSCHAFT with those of Hansen since doing so would efficiently optimize the input parameters. It would be obvious to arrive at the baseline control algorithm includes a Proportional-integral-derivative control algorithm as taught by Hansen (see col 7, In 16 to col 8, In 67; col 11, In 35 to col 12, In 40).
Regarding Claim 23, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Hansen in Claim 22 above, teaches the method of claim 22, wherein processing the error signal comprises processing the error signal using the first lag compensator to delay the error signal by a number of samples that is equal to a relative degree of the second transfer function (Hanasen col 13, In 35 to col 14, In 25; col 19, In 46 to col 20, In 25).
Regarding Claim 24, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Hansen in Claim 22 above, teaches the method of claim 23, wherein adjusting the input signal further comprises providing the input signal to a second lag compensator of the plug-in compensation algorithm (col 13, In 35 to col 14, In 25; col 19, In 46 to col 20, In 25).
Regarding Claim 25, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Hansen in Claim 22 above, teaches the method of claim 24, wherein adjusting the input signal further comprises processing the input signal using the second lag compensator to delay the input signal by the number of samples that is equal to the relative degree of the second transfer function (Hansen col 13, In 35 to col 14, In 25; col 19, In 46 to col 20, In 25).
Regarding Claim 26, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Hansen in Claim 22 above, teaches the method of claim 25, wherein adjusting the input signal further comprises generating a sum of a first output of the second lag compensator and a second output of the sub-algorithm (col 13, In 35 to col 14, In 25; col 19, In 46 to col 20, In 25).
Regarding Claim 29, Seurat Technologies, Inc, as modified with SIEMENS AKTIENGESELLSCHAFT and Hansen in Claim 22 above, teaches the method of claim 28, wherein the input signal is equal to a second sum of the compensation signal and an output of the baseline control algorithm (Abstract; col 9, In 30 to col 10, In 20).
Allowable Subject Matter
Claims 27 and 28 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The prior art does not teach:
Claim 27, wherein adjusting the input signal further comprises generating a compensation signal by processing the sum using a filter having a transfer function
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when m=1, wherein 0≤α≤1, z is the complex indeterminate in the z-transform, N is a period of a disturbance within the output signal, and m is equal to the relative degree of the second transfer function.
Claim 28, wherein adjusting the input signal further comprises generating a compensation signal by processing the sum using a filter having a transfer function
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559
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wherein 0≤α≤1, z is the complex indeterminate in the z-transform, N is a period of a disturbance within the output signal, qlpf is a low pass filter, and m is equal to the relative degree of the second 2 function.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW BUI whose telephone number is (571) 272-0685. The examiner can normally be reached on 7:30 AM - 4:30 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Courtney Heinle can be reached on (571) 270-3508. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/ANDREW THANH BUI/Examiner, Art Unit 3745
/COURTNEY D HEINLE/Supervisory Patent Examiner, Art Unit 3745
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