DETAILED ACTION
The office action is responsive to an application filed on 5/5/23 and is being
examined under the first inventor to file provisions of the AIA . Claims 1-20 are pending.
Priority
The current application filed on 5/5/23 claims priority from provisional application
63/339,149 filed on 5/6/2022.
Claim Objections
Claim 7 is objected to because of the following informalities: In claim 7 there appears to
be a grammatical error within the limitation where the word “based” inserted after the phrase “model-based point field” and before “and at least one measure-based point field”. The examiner recommends removing the word “based” after the phrase “model-based point field”. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under the broadest reasonable interpretation, the claims covers performance of the limitation in the mind or by pencil and paper and as a mathematical concept.
Claims 1 and 15
Regarding step 1, claims 1 and 15 are directed towards a method and medium which has the claims fall within the eligible statutory categories of processes, machines, manufactures and composition of matter under 35 U.S.C. 101.
Claim 1
Regarding step 2A, prong 1, claim 1 recites “generating at least one point field”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “computing at least one process metric from the at least one point field”. This limitation is computing at least one process metric. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 1 recites “wherein computing the at least one process metric includes: selecting at least one principal point from the point field”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “determining at least one neighborhood using an additive manufacturing model search algorithm for the at least one principal point”. The at least one neighborhood is determined using an additive manufacturing model search algorithm, see paragraph [0030] of the specification. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 1 recites “and integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood”. This limitation is integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 1 recites “and updating the at least one point field with the at least one process metric computed.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper, see paragraph [0010] of the specification. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, this limitation is updating the at least one point field with the at least one process metric computed. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of “obtaining a build file containing instructions to additively manufacture a component” amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the claim language of claim 1 does not recite a computer or components of a computer such as a processor, where an additional element is not claimed. Accordingly, the additional element of a processor does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B, the limitation of “obtaining a build file containing instructions to additively manufacture a component” is also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the claim language of claim 10 does not recite a computer or components of a computer such as a processor, where an additional element is not claimed.
Claim 15
Regarding step 2A, prong 1, claim 15 recites “generating at least one point field for the component”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 15 recites “computing at least one process metric from the at least one point field”. This limitation is computing at least one process metric. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 15 recites “wherein computing the at least one process metric includes: selecting at least one principal point from the point field”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 15 recites “determining at least one neighborhood using an additive manufacturing model search algorithm for the at least one principal point”. The at least one neighborhood is determined using an additive manufacturing model search algorithm, see paragraph [0030] of the specification. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 15 recites “and integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood”. This limitation is integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 15 recites “and updating the at least one point field with the at least one process metric computed.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper, see paragraph [0010] of the specifciation. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, this limitation is updating the at least one point field with the at least one process metric computed. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of “obtaining a build file containing instructions to additively manufacture a component” amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the claim language includes the additional elements of a processor and medium. The processor and medium are recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B, the limitation of “obtaining a build file containing instructions to additively manufacture a component” is also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a processor and medium amounts no more than mere instructions to apply the exception using a generic computer component that does not impose any meaningful limits on practicing the abstract idea and therefore cannot provide an inventive concept (See MPEP 2106.05(b).
Claims 2 and 16
Dependent claims 2 and 16 recite “including determining if the build file should be modified based on the at least one process metric.”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, this limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what value the process metric is to decide that the build file should be modified. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claims 3 and 17
Dependent claims 3 and 17 recite “including modifying the build file for the component based on the at least one process metric if it is determined that the build file should be modified.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate how the build file would be modified. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claims 4 and 18
Dependent claims 4 and 18 recite “wherein the at least one additive manufacturing model kernel function is a non-constant kernel convolution calculation.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claims 5 and 19
Dependent claims 5 and 19 recite “wherein integrating at least one additive manufacturing model kernel function for the at least one principal point is based on a single point in time for the at least one principal point.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate how the additive manufacturing model kernel function is being integrated.
Claims 6 and 20
Dependent claims 6 and 20 recite “wherein generating the at least one point field for the component includes generating a model-based point field from the build file or generating at least one measure-based point field from in-situ measured data.”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate what the data in the build file is or the in-situ measured data is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Claim 7
Dependent claim 7 recites “wherein the at least one point field for the component includes the model-based point field based and at least one measure-based point field.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 8
Dependent claim 8 recites “wherein the at least one measure-based point field includes a first measure-based point field from measured data of a first component and a second measure-based point field from measured data of a second component.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 9
Dependent claim 9 recites “wherein the first component and the second component are constructed from a single build file.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 10
Dependent claim 10 recites “wherein the in-situ measured data is obtained from in-situ sensors recording time resolved mirror positions and laser powers during a build process for the component from the build file.”. This limitation amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Claim 11
Dependent claim 11 recites “including creating a comparison point field comparing at least one computed process metric from corresponding points from the model-based point field and the at least one measure-based point field.”. This limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12
Dependent claim 12 recites “wherein the in-situ measured data is obtained from in-situ sensors recording time resolved position and heat source intensity during a build process for the component from the build file.”. This limitation amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Claim 13
Dependent claim 13 recites “wherein the at least one process metric computed includes a melt pool dimension determined from using a value computed for a thermal rise as a substrate temperature.”. This limitation is computing a value for a thermal rise as a substrate temperature. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Also, this limitation doesn’t distinguish itself from being able to be conducted in the human or with pencil and paper, see paragraph [0034] of the specification. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 14
Dependent claim 14 recites “wherein the process metrics provide instantaneous point-in-time data regarding the additive manufacturing process for the component.”. This limitation amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
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 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) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Blom et al.
(U.S. PGPub 2019/0004496) in view of Medalsy et al. (U.S. PGPub 2020/0353687).
With respect to claim 1, Blom et al. discloses “A method of generating a model for additive manufacturing” as [Blom et al. (paragraph [0033] “The computing device may use one more of preexisting data, whether measured, modeled or virtual data, that is relevant to the part including building of the part, to modify the part, including, for example the starting shape of the part, build file or build directly.”, Blom et al. paragraph [0055] “Controller 26 includes, for example, a 3D model of part 28 to be fabricated by system 10.”
“obtaining a build file containing instructions to additively manufacture a
component” as [Blom et al. (paragraph [0006] “The method includes storing a build file for building the part including one or more build parameters and receiving a plurality of build information. Each build information of the plurality of build information includes sensor information of a build of the part by at least one of a plurality of machines.”)];
“generating at least one point field” as [Blom et al. (paragraph [0032] “As used herein,
the term geometry refers to any section, characteristic, or feature of a part or build. A geometry may be in a single layer, a build of an individual part, a section of a part, a scan line, a time series of a build, and a geometric feature of a part.”, The examiner considers the time series of a build to be the point filed, since a point field is made of time-stamped points, see paragraph [0029] of the specification)];
“computing at least one process metric from the at least one point field” as [Blom et al. (paragraph [0049] “Computing device 24 includes a computer system that includes at least one processor (not shown in FIG. 1) that executes executable instructions to operate system 10. Computing device 24 includes, for example, a calibration model of system 10 and an electronic computer build file associated with a component, such as part 28. The calibration model includes, without limitation, an expected or desired melt pool size and temperature under a given set of operating conditions (e.g., a power of laser device 14) of system 10. In the exemplary embodiment, the melt pool size includes one or more dimensions of the melt pool, such as, but not limited to, length, width, depth, area, and volume. In the exemplary embodiment, the melt pool temperature profile represents the temperature of the melt pool at certain points in the melt pool, such as the center. In other embodiments, the melt pool temperature profile represents a measured temperature from samples of the melt pool or from a function of the 2D/3D temperature distribution profile.”, The examiner considers the melt pool size to be the process metric, since a process metric can be the melt pool size (dimensions), see paragraphs [0033] and [0034] of the specification)];
“wherein computing the at least one process metric includes: selecting at least one principal point from the point field” as [Blom et al. (paragraph [0057] “Controller 26 is configured to control the position, movement, and scan speed of first mirror 46 and second mirror 50 based on at least one of the position of mirror 34 of first scanning device 18 and the position of melt pool 22. In one embodiment, for example, the position of mirror 34 at a given time during the build process is determined, using computing device 24 and/or controller 26, based upon a predetermined path of a build file used to control the position of mirror 34. Controller 26 controls the position, movement, and scan speed of first mirror 46 and second mirror 50 based upon the determined position of mirror 34. In another embodiment, first scanning device 18 is configured to communicate the position of mirror 34 to controller 26 and/or computing device 24, for example, by outputting position signals to controller 26 and/or computing device 24 that correspond to the position of mirror 34. In yet another embodiment, controller 26 controls the position, movement, and scan speed of first mirror 46 and second mirror 50 based on the position of melt pool 22. The location of melt pool 22 at a given time during the build process is determined, for example, based upon the position of mirror 34.”, The examiner considers the location of the melt pool at a given time to be the principal point, since this is the time point at which the controller is controlling the scanning device to direct EM radiation from the melt pool];
“determining at least one neighborhood using an additive manufacturing model
search algorithm for the at least one principal point” as [Blom et al. (paragraph [0032] “As used herein, the term geometry refers to any section, characteristic, or feature of a part or build. A geometry may be in a single layer, a build of an individual part, a section of a part, a scan line, a time series of a build, and a geometric feature of a part.”, Blom paragraph [0054] “For example, as system 10 builds part 28, computing device 24 processes electrical signals 44 from first optical detector 38 using data processing algorithms to determine the size and temperature of melt pool 22.”, Blom paragraph [0142] “The machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition, and may be trained after processing multiple examples.”, The examiner considers the time series of a build to be a neighborhood, since the neighborhood is a plurality of time points, see paragraph [0032] of the specification)];
“and updating the at least one point field with the at least one process metric computed” as [Blom et al. (paragraph [0050] “Build parameters may also comprise one or more of, without limitation, materials used by the system to carry out the methods such as gases, gas pressures, and flow of gases; melt pool sizes and melt pool temperature profiles”, Blom paragraph [0068] “ In some embodiments, MC computer device 302 is further configured to store build file 210 for building part 28 including a plurality of geometries that each include one or more values of a first build parameter, receive sensor information of a build of part 28 by system 10 using build file 210, compare the sensor information for each geometry of the plurality of geometries to the corresponding one or more values of the first build parameter to determine one or more differences, determine one or more values for a second build parameter for each of the geometries based on the one or more differences, generate an updated build file 210 for part 28 including the one or more values for the second build parameter, and transmit the updated build file 210 to system 10.”)];
While Blom et al. teaches selecting a principal point from a point field and determining a
neighborhood using an additive manufacturing model search algorithm for the at least one principal point, Blom et al. does not explicitly disclose “and integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood”
Medalsy et al. discloses “and integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood” as [Medalsy et al. (paragraph [0004] “In one embodiment of the invention, the optimal printing speed and orientation are so arrived at by first determining, for each pixel map that defines a cross-section of the object to be fabricated, a critical size of a convolution kernel for which convolving the convolution kernel with the pixel map provides an activation map having a maximum activation pixel value less than or equal to a predetermined threshold value. The pixel maps of the cross-sections of the object to be fabricated are ranked relative to one another according to their respective critical sizes of convolution kernels. For each respective pixel map of the cross-sections of the object to be fabricated, a printing time is estimated as a function of adjusted base lift velocity and base lift height of an extractor plate of the a printing apparatus within which the additive manufacturing process is performed, where the base lift velocity and base lift height are so adjusted according to a parameter derived from the respective critical size convolution kernel of the respective pixel map.”, The examiner considers the pixel map to be the neighborhood, since the neighborhood is filled with points and the pixel map is filled with pixels (points) within the pixel map)];
Blom et al. and Medalsy et al. are analogous art because they are from the same field endeavor of analyzing data for 3D printing of an object.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Blom et al. of selecting a principal point from a point field and determining a neighborhood using an additive manufacturing model search algorithm for the at least one principal point by incorporating and integrating at least one additive manufacturing model kernel function for the at least one principal point and the at least one neighborhood as taught by Medalsy et al. for the purpose of determining an optimal printing speed and orientation for an object to be manufactured using an additive manufacturing process.
Blom et al. in view of Medalsy et al. teaches determining an optimal printing speed and orientation for an object to be manufactured using an additive manufacturing process.
The motivation for doing so would have been because Medalsy et al. teaches that by determining an optimal printing speed and orientation for an object to be manufactured, the manufacturing time of the object can be known. This allows a user to know how long it will take to print their object (Medalsy et al. paragraph [0002] – [0003]).
With respect to claim 2, the combination of Blom et al. and Medalsy et al. discloses the method of claim 1 above, and Blom et al. further discloses “including determining if the build file should be modified based on the at least one process metric.” as [Blom et al. (paragraph [0065] “In the exemplary embodiment, build file 210 includes the melt pool size as a build parameter. Computer device 24 adjusts the laser power and speed to achieve the desired melt pool size. In the exemplary embodiment, computer device 24 receives sensor information including the melt pool size and adjusts the laser settings to achieve the desired melt pool size.”, Blom paragraph [0070] “Each build information of the plurality of build information includes sensor information of a build of part 28 by one of a plurality of machines 10 using build file 210. MC computer device 302 is further configured to compare the plurality of sensor information to the one or more build parameters to determine one or more differences, determine one or more adjustments to the one or more build parameters based on the one or more differences, generate an updated build file 210 based on the one or more adjustments, and transmit the updated build file 210 to at least one system 10 of the plurality of systems 10 for manufacture.”)];
With respect to claim 3, the combination of Blom et al. and Medalsy et al. discloses the method of claim 2 above, and Blom et al. further discloses “including modifying the build file for the component based on the at least one process metric if it is determined that the build file should be modified.” as [Blom et al. (paragraph [0065] “In the exemplary embodiment, build file 210 includes the melt pool size as a build parameter. Computer device 24 adjusts the laser power and speed to achieve the desired melt pool size. In the exemplary embodiment, computer device 24 receives sensor information including the melt pool size and adjusts the laser settings to achieve the desired melt pool size.”, Blom paragraph [0070] “Each build information of the plurality of build information includes sensor information of a build of part 28 by one of a plurality of machines 10 using build file 210. MC computer device 302 is further configured to compare the plurality of sensor information to the one or more build parameters to determine one or more differences, determine one or more adjustments to the one or more build parameters based on the one or more differences, generate an updated build file 210 based on the one or more adjustments, and transmit the updated build file 210 to at least one system 10 of the plurality of systems 10 for manufacture.”)];
With respect to claim 4, the combination of Blom et al. and Medalsy et al. discloses the method of claim 1 above, and Medalsy et al. further discloses “wherein the at least one additive manufacturing model kernel function is a non-constant kernel convolution calculation.” as [Medalsy et al. (paragraph [0004] “In one embodiment of the invention, the optimal printing speed and orientation are so arrived at by first determining, for each pixel map that defines a cross-section of the object to be fabricated, a critical size of a convolution kernel for which convolving the convolution kernel with the pixel map provides an activation map having a maximum activation pixel value less than or equal to a predetermined threshold value. The pixel maps of the cross-sections of the object to be fabricated are ranked relative to one another according to their respective critical sizes of convolution kernels. For each respective pixel map of the cross-sections of the object to be fabricated, a printing time is estimated as a function of adjusted base lift velocity and base lift height of an extractor plate of the a printing apparatus within which the additive manufacturing process is performed, where the base lift velocity and base lift height are so adjusted according to a parameter derived from the respective critical size convolution kernel of the respective pixel map.”)];
With respect to claim 5, the combination of Blom et al. and Medalsy et al. discloses the method of claim 1 above, and Medalsy et al. further discloses “wherein integrating at least one additive manufacturing model kernel function for the at least one principal point is based on a single point in time for the at least one principal point.” as [Medalsy et al. (paragraph [0004] “In one embodiment of the invention, the optimal printing speed and orientation are so arrived at by first determining, for each pixel map that defines a cross-section of the object to be fabricated, a critical size of a convolution kernel for which convolving the convolution kernel with the pixel map provides an activation map having a maximum activation pixel value less than or equal to a predetermined threshold value. The pixel maps of the cross-sections of the object to be fabricated are ranked relative to one another according to their respective critical sizes of convolution kernels. For each respective pixel map of the cross-sections of the object to be fabricated, a printing time is estimated as a function of adjusted base lift velocity and base lift height of an extractor plate of the a printing apparatus within which the additive manufacturing process is performed, where the base lift velocity and base lift height are so adjusted according to a parameter derived from the respective critical size convolution kernel of the respective pixel map. The optimal printing speed and orientation for the object are estimated as a minimum value of a sum of a function of printing times for all respective pixel maps of the cross-sections of the object at each of a plurality of possible orientations of the object, where the function of the printing times includes a term proportional to a rate of change of local density of the pixel maps as a function of slice number.”, The examiner considers a printing time of the plurality of printing times to be the single point in time for the one principal point, since there’s a printing time for the adjusted base lift velocity and base lift height of an extractor plate of the printing apparatus within which the additive manufacturing process is performed)];
With respect to claim 6, the combination of Blom et al. and Medalsy et al. discloses the method of claim 1 above, and Blom et al. further discloses “wherein generating the at least one point field for the component includes generating a model-based point field from the build file or generating at least one measure-based point field from in-situ measured data.” as [Blom et al. (paragraph [0033] “The computing device may use one more of preexisting data, whether measured, modeled or virtual data, that is relevant to the part including building of the part, to modify the part, including, for example the starting shape of the part, build file or build directly. The data provided and/or used may be feedforward, feedback, pre- or post-build, modeled and virtual.”, Blom et al. paragraph [0062] “As described above, sensors 216 monitor the building 212 of part 28 in real-time and transmit the results to computing device 24. Computing device 24 uses the feedback control information to determine whether or not to change any current parameters to correct for potential issues.”, Blom et al. paragraph [0067] “As described below in more detail, MC computing device 302 is configured to store a model of a part 28 including a plurality of build parameters, receive current sensor information of at least one current sensor reading of a melt pool 22 (shown in FIG. 1) from a build of part 28 in progress, determine one or more attributes of melt pool 22 based on the current sensor information, calculate at least one unseen attribute of the melt pool 22, determine an adjusted build parameter based on the at least one unseen attribute, the one or more attributes, and the plurality of build parameters, and transmit the adjusted build parameter to a machine, such as system 10, currently manufacturing the part.”)];
With respect to claim 7, the combination of Blom et al. and Medalsy et al. discloses the method of claim 6 above, and Blom et al. further discloses “wherein the at least one point field for the component includes the model-based point field based and at least one measure-based point field.” as [Blom et al. (paragraph [0033] “The computing device may use one more of preexisting data, whether measured, modeled or virtual data, that is relevant to the part including building of the part, to modify the part, including, for example the starting shape of the part, build file or build directly. The data provided and/or used may be feedforward, feedback, pre- or post-build, modeled and virtual.”, Blom et al. paragraph [0067] “As described below in more detail, MC computing device 302 is configured to store a model of a part 28 including a plurality of build parameters, receive current sensor information of at least one current sensor reading of a melt pool 22 (shown in FIG. 1) from a build of part 28 in progress, determine one or more attributes of melt pool 22 based on the current sensor information, calculate at least one unseen attribute of the melt pool 22, determine an adjusted build parameter based on the at least one unseen attribute, the one or more attributes, and the plurality of build parameters, and transmit the adjusted build parameter to a machine, such as system 10, currently manufacturing the part.”)];
With respect to claim 8, the combination of Blom et al. and Medalsy et al. discloses the method of claim 7 above, and Blom et al. further discloses “wherein the at least one measure-based point field includes a first measure-based point field from measured data of a first component and a second measure-based point field from measured data of a second component.” as [Blom et al. (paragraph [0119] “In the exemplary embodiment, feedforward control computer device 702 stores 1002 a build file 210 for building 212 (shown in FIG. 2) part 28 including a plurality of geometries that each include one or more values of a first build parameter. In the exemplary embodiment, the first build parameter includes at least one of a desired melt pool size and a desired melt pool temperature profile. Feedforward control computer device 702 receives 1004 sensor information of a build 212 of part 28 by system 10 (shown in FIG. 1) using build file 210. Feedforward control computer device 702 compares 1006 the sensor information for each geometry of the plurality of geometries to the corresponding one or more values of the first build parameter for those geometries to determine one or more differences.”, Blom et al. paragraph [0120] “Based on the one or more differences, feedforward control computer device 702 determines 1008 one or more values for a second build parameter for each of the geometries. Examples of the second build parameter include, but are not limited to, a power of laser device 14 (shown in FIG. 1) and a scan speed of first scanning device 18. Feedforward control computer device 702 generates 1010 an updated build file 210 for part 28 including the one or more values for the second build parameter.”)];
With respect to claim 9, the combination of Blom et al. and Medalsy et al. discloses the method of claim 8 above, and Blom et al. further discloses “wherein the first component and the second component are constructed from a single build file.” as [Blom et al. (paragraph [0007] “The system includes a plurality of additive manufacturing machines configured to build the part based on a build file, a plurality of sensors configured to monitor building the part, and a manufacturing computer device including at least one processor in communication with at least one memory device. The manufacturing computer device is configured to store a build file for building the part including one or more build parameters and receive a plurality of build information.”, Blom et al. paragraph [0050] “The build file includes build parameters that are used to control one or more components of one or more systems, such as, without limitation, system 10, or to otherwise build parts. The build parameters will depend on the additive manufacturing methods or systems employed and the materials making up the parts.”)];
With respect to claim 10, the combination of Blom et al. and Medalsy et al. discloses the method of claim 7 above, and Blom et al. further discloses “wherein the in-situ measured data is obtained from in-situ sensors recording time resolved mirror positions and laser powers during a build process for the component from the build file.” as [Blom et al. (paragraph [0062] “As described above, sensors 216 monitor the building 212 of part 28 in real-time and transmit the results to computing device 24. Computing device 24 uses the feedback control information to determine whether or not to change any current parameters to correct for potential issues.”, Blom et al. paragraph [0041] “In the exemplary embodiment, first scanning device 18 is a galvanometer scanning device including a mirror 34 operatively coupled to a galvanometer-controlled motor 36 (broadly, an actuator). Motor 36 is configured to move (specifically, rotate) mirror 34 in response to signals received from controller 26, and thereby deflect laser beam 16 across selective portions of build platform 12. Mirror 34 includes any suitable configuration that enables mirror 34 to deflect energy source 16 towards build platform 12.”, Blom et al. paragraph [0065] “In the exemplary embodiment, build file 210 includes the melt pool size as a build parameter. Computer device 24 adjusts the laser power and speed to achieve the desired melt pool size. In the exemplary embodiment, computer device 24 receives sensor information including the melt pool size and adjusts the laser settings to achieve the desired melt pool size.”)];
With respect to claim 11, the combination of Blom et al. and Medalsy et al. discloses the method of claim 7 above, and Blom et al. further discloses “including creating a comparison point field comparing at least one computed process metric from corresponding points from the model-based point field and the at least one measure-based point field.” as [Blom et al. (paragraph [0127] “In the exemplary embodiment, feedforward control computer device 702 compares the plurality of sensor information to the one or more build parameters to determine one or more differences. For example, if the build parameter is the desired melt pool size, then the sensor information shows the actual melt pool size and feedforward control computer device 702 is able to determine the difference between the desired and the actual melt pool size.”, Blom et al. paragraph [0128] “For example, feedforward control computer device 702 compares 1106 the sensor information for four different builds 212 of part 28 on two different systems 10. Feedforward control computer device 702 determines differences for each of the builds based on the corresponding sensor information. Feedforward control computer device 702 compares the various differences to determine which differences show an issue with the build file 210, which differences only occur once (such as a one-time event), and which differences are specific to the system 10. Based on the differences that show an issue with the build file 210, feedforward control computer device 702 determines 1108 one or more adjustments to the one or more build parameters to correct and/or improve manufacture of part 28.”, Blom et al. paragraph [0130] “Feedforward control computer device 702 compares the real-time adjustments from each build to the sensor information for the corresponding build 212. Feedforward control computer device 702 determines the one or more adjustments for the build parameter based on the comparison.”)];
With respect to claim 12, the combination of Blom et al. and Medalsy et al. discloses the method of claim 7 above, and Blom et al. further discloses “wherein the in-situ measured data is obtained from in-situ sensors recording time resolved position and heat source intensity during a build process for the component from the build file.” as [Blom et al. (paragraph [0062] “As described above, sensors 216 monitor the building 212 of part 28 in real-time and transmit the results to computing device 24. Computing device 24 uses the feedback control information to determine whether or not to change any current parameters to correct for potential issues.”, Blom et al. paragraph [0039] “Device 14 is configured to generate energy source 16 of sufficient energy to at least partially heat or melt the build material of build platform 12.”, Blom et al. paragraph [0041] “First scanning device 18 is configured to direct energy source 16 across selective portions of build platform 12 to create part 28. In the exemplary embodiment, first scanning device 18 is a galvanometer scanning device including a mirror 34 operatively coupled to a galvanometer-controlled motor 36 (broadly, an actuator).”)];
With respect to claim 13, the combination of Blom et al. and Medalsy et al. discloses the method of claim 1 above, and Blom et al. further discloses “wherein the at least one process metric computed includes a melt pool dimension determined from using a value computed for a thermal rise as a substrate temperature.” as [Blom et al. (paragraph [0046] “Further, because the type of EM radiation 40 emitted by melt pool 22 depends on the temperature of melt pool 22, optical system 20 is capable of monitoring and measuring both a size and a temperature of melt pool 22.”, Blom et al. paragraph [0049] “The calibration model includes, without limitation, an expected or desired melt pool size and temperature under a given set of operating conditions (e.g., a power of laser device 14) of system 10. In the exemplary embodiment, the melt pool size includes one or more dimensions of the melt pool, such as, but not limited to, length, width, depth, area, and volume. In the exemplary embodiment, the melt pool temperature profile represents the temperature of the melt pool at certain points in the melt pool, such as the center. In other embodiments, the melt pool temperature profile represents a measured temperature from samples of the melt pool or from a function of the 2D/3D temperature distribution profile.”)];
With respect to claim 14, the combination of Blom et al. and Medalsy et al. discloses the method of claim 1 above, and Blom et al. further discloses “wherein the process metrics provide instantaneous point-in-time data regarding the additive manufacturing process for the component.” as [Blom et al. (paragraph [0043] “Optical system 20 is configured to detect electromagnetic radiation generated by melt pool 22 and transmit information about melt pool 22 to computing device 24. In the exemplary embodiment, optical system 20 includes an optical detector 38 configured to detect electromagnetic radiation 40 (also referred to as “EM radiation”) generated by melt pool 22, and a second scanning device 42 configured to direct electromagnetic radiation 40 generated by melt pool 22 to optical detector 38.”, Blom et al. paragraph [0057] “In yet another embodiment, controller 26 controls the position, movement, and scan speed of first mirror 46 and second mirror 50 based on the position of melt pool 22. The location of melt pool 22 at a given time during the build process is determined, for example, based upon the position of mirror 34.”, The examiner considers the melt pool size to be the process metric, since a process metric can be the melt pool size (dimensions), see paragraphs [0033] and [0034] of the specification)];
With respect to claim 15, Blom et al. discloses “A non-transitory computer-readable storage medium embodying programmed instructions which, when executed by a processor, are operable for performing a method” as [Blom et al. (paragraph [0028] “In the embodiments described herein, memory may include, but is not limited to, a computer-readable medium, such as a random access memory (RAM), and a computer-readable non-volatile medium, such as flash memory.”, Blom et al. paragraph [0030] “As used herein, the term “non-transitory computer-readable media” is intended to be representative of any tangible computer-based device implemented in any method or technology for short-term and long-term storage of information, such as, computer-readable instructions, data structures, program modules and sub-modules, or other data in any device. Therefore, the methods described herein may be encoded as executable instructions embodied in a tangible, non-transitory, computer readable medium, including, without limitation, a storage device and/or a memory device. Such instructions, when executed by a processor, cause the processor to perform at least a portion of the methods described herein.”)];
The other limitations recite the same substantive limitations as claim 1 above and are rejected using the same teachings.
With respect to claims 16-20, the claims recite the same substantive limitations as claims 2-6 above and are rejected using the same teachings.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The relevance of Rezayat (U.S. PGPub 2015/0142152) is additive manufacturing or "3D" printing systems with enhanced CAD capabilities.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD E COTHRAN whose telephone number is (571)270-5594. The examiner can normally be reached 9AM -5:30PM EST M-F.
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/BERNARD E COTHRAN/Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188
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