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 .
This action is in response to the applicant’s communication filed on 7/6/2026
Claims 1-5, 8-15, and 18-24 are pending
Claims 6-7 and 16-17 are canceled
Response to Arguments
Applicant's arguments filed 7/6/2026 have been fully considered but they are not persuasive. Applicant’s arguments on page 8. Applicant argues that “the portion of Wilson identified by the Office is related to control of an energy delivery device for deposition, not a machining device for machining” and “a person of ordinary skill in the art would not have understood deposition parameters used to control a set of deposition devices, as described by Wilson, as being machining parameters used to control a machining device”. Examiner respectfully disagrees because Applicant considers Wilson individually rather than the teachings of Wilson and Hollander in combination. Hollander teaches the claimed subtractive machining toolpath. Hollander teaches (Fig. 5, Par. [0068] – [0069] “Step 516 generates a difference layer profile for the selected subtractive layer. The difference layer profile specifies the geometry of additively deposited material that needs to be removed using subtractive operations to produce the desired parts' shapes in the selected subtractive layer … Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”). Thus, the rejection does not require Wilson’s energy-delivery toolpath or deposition parameters to themselves constitute the claimed machining toolpath or machining parameters. Wilson teaches identifying differences between the measured build surface and the desired build surface, while Hollander teaches generating a subtractive machining toolpath based on regions of deposited material requiring removal. Further, Wilson’s discussion of “non-flexible or non-adjustable process settings” does not discourage the use of adjustable machining parameters but instead identifies inflexible process settings as a potential source of component defects. Accordingly, Applicant’s arguments do not overcome the combined teachings of Wilson and Hollander.
Applicant’s arguments on page 9. Applicant further argues that “Murakami applies predetermined parameters to geometric categorizations of curvature of a surface, and so would not suggest to a person skilled in the art to select different machining parameters for a portion of a substrate having an identified different “between [] topological data and specification data representative of a set of tolerances of [a] build surface.””. Examiner respectfully disagrees because Applicant considers Murakami individually rather than the teachings of the references as combined. Murakami is relied upon for varying machining feed rate for different portions, not for identifying the claimed differences. Wilson teaches identifying the differences, while Hollander teaches generating subtractive toolpaths for material identified for removal. Murakami teaches (Col. 6, lines 53-55, “the machining feed rate is set for each area and for each shape change point”). Thus, in the combined system, Wilson identifies the differences, Hollander provides the corresponding subtractive machining toolpath, and Murakami provides different machining feed rates for different portions of the machining toolpath. The combination applies Murakami’s known area-specific feed-rate control to Hollander’s subtractive machining toolpaths so that the machining feed rate may be tailored to the portion being machined. Applicant’s arguments that there is no apparent reason for the modification is also not persuasive. The rationale for the modification is set forth in the rejection below. Accordingly, Applicant’s argument is not persuasive.
Applicant’s arguments on pages 9-10. Applicant further argues that “independent claim 11 includes the amended subject matter of independent claim 1, and is patentable for at least the reasons independent claim 1 is patentable. Dependent claims 2-5, 8-10, 12-15, and 18-20 incorporate the requirements of the respective independent claims, and are likewise patentable” and “Applicant has added claims 21-24 to the pending application. The applied references fail to disclose or suggest the subject matter defined by Applicant’s new claims, and would have provided no apparent reason for modification to arrive at the claimed subject matter”. Examiner respectfully disagrees because independent claim 11 recites corresponding limitations to those discussed above with respect to claim 1, and Applicant has not presented a separate substantive argument regarding the dependent claims. Accordingly, these arguments are not persuasive for the reasons discussed above. With respect to newly presented claims 21-24, Applicant’s arguments are not persuasive for the reasons set forth in the respective rejections of claims 21-24 below.
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) 1-5, 8-15, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wilson et al. US 9,886,015 B2 (hereinafter Wilson) in view of Hollander USPGPUB 2021/0197491 A1 (hereinafter Hollander), and further in view of Murakami et al. US 7,070,368 B2 (hereinafter Murakami).
Regarding claim 1, Wilson teaches an additive manufacturing system (Fig. 1, Col. 4, “system 10 includes a computing device 12, a powder 40 delivery device 14, an energy delivery device 16, a laser imaging device 18, and a stage 20. Computing device 12 is operably connected to powder delivery device 14, energy delivery device 16, laser imaging device 18, and stage 20”), 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 (Col. 2, “control the energy delivery device to deliver energy to a volume of the powder of the material to join at least some of the powder of the material to the first layer of material and form a second layer.” – a melt pool in the build surface of the component would be created when the energy is used to join the powder to form a second layer; Col. 5, “Energy delivery device 16 may include an energy source, such as a laser source, an electron beam source, plasma source, or another source of energy that may be absorbed by the powder to be added to component 22”);
a powder delivery device configured to direct a powder stream toward the melt pool (Col. 4, “Powder delivery device 14 may be configured to deliver material to the location of component 22 being formed. The material then may be heated by energy delivered by energy delivery device 16 to add the material to component 22. In some examples, the material may be supplied by powder delivery device 14 in powder form. – the material being heated forms a melt pool);
one or more sensors comprising at least one topology sensor configured to generate topological data representative of a topology of the build surface (Col. 5, “laser imaging device 18 may be positioned substantially directly above component 22 and may include an interferometer, which provides depth information based on the time from outputting a laser pulse to the sensing of the reflected light. In other examples, laser imaging device 18 may be positioned at an offset with respect to component 22 such that the sensor senses depth information without using an interferometer.”); and
a computing device (Col. 4, “computing device 12”) configured to:
receive the topological data from the at least one topology sensor for a plurality of layers (Col. 2, “storing, by the computing device, the plurality of respective layer images as an image file for the as-built component”; Col. 11, “images are generated layer-by-layer as the component is formed… the images for each respective layer may be aggregated and correlated to produce a fully associative three dimensional model of the as-built component”);
identify differences between the topological data and specification data representative of a set of tolerances of the build surface (Col. 11, “images may be used to determine if the thickness of the most recently added layer is within a defined range … when laser scanning is used to image the component, the resulting image data may be compared to the original computer aided design files to verify geometry of the as-built component to the designed component”);
control the energy delivery device and the powder delivery device to deposit the plurality of layers based on a set of deposition parameters (Col. 8, “computing device 12 may implement closed-loop control of system 10, such as by modifying one or more process parameters based on the determination that the thickness of second layer of material 26 is not in the defined range of thicknesses … modified tool path may trace a path that adjusts for the deviation in the thickness of second layer of material 26 to reduce a likelihood that porosity, cracks, or lack of fusion occurs at the position with the deviation in thickness”).
Wilson does not explicitly teach a machining device configured to machine the build surface;
control the machining device to machine the build surface based on the identified differences, wherein to control the machining device, the computing device is configured to:
generate machining data that includes:
a toolpath;
a first set of machining parameters for portions of the toolpath that do not include the identified differences; and
a second set of machining parameters for portions of the toolpath that include the identified differences, wherein at least one machining parameter of the second set of machining parameters is different from the first set of machining parameters, and wherein the at least one machining parameter includes a change in material removal rate; and
output the machining data to the machining device.
However, the combination of Wilson and Hollander teaches a machining device configured to machine the build surface (Hollander, Par. [0016] “subtractive material removal at part surfaces to maximize detail and dimensional accuracy”; Par. [0023] “System 100 also includes M subtractive toolheads 113, where M is one or more. Each of the subtractive toolheads is capable of removing structural or support material in a spatially-localized region, including a finite thickness in the Z dimension, referred to herein as the subtractive layer thickness.”; Par. [0030] “additional subtractive toolheads may also utilize laser machining or any other subtractive manufacturing tool known in the art, including cutting tools, milling spindles, abrasive grinders, electric discharge machining, waterjet cutting, and plasma cutting”);
control the machining device to machine the build surface based on the identified differences (Hollander, Fig. 5, Par. [0068] – [0069] “Step 516 generates a difference layer profile for the selected subtractive layer. The difference layer profile specifies the geometry of additively deposited material that needs to be removed using subtractive operations to produce the desired parts' shapes in the selected subtractive layer … Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”; Par. [0072] “step 522 schedules the subtractive operations for execution”), wherein to control the machining device, the computing device is configured to (Par. [0100] “computer system suitable for controlling an automated manufacturing system including two independently and simultaneously operating toolheads”):
generate machining data that includes (Hollander, Fig. 5, Par. [0069] “Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”):
a toolpath (Wilson, Col. 8, “computing device 12 may control energy delivery device 16 to modify a tool path traced by the focal point or focal volume of the energy beam output by energy delivery device 16”);
a first set of machining parameters for portions of the toolpath that do not include the identified differences (Col. 8, “path that adjusts for the deviation in the thickness of second layer of material 26 to reduce a likelihood that porosity, cracks, or lack of fusion occurs at the position with the deviation in thickness – the first set of parameters is for the positions that do not deviate in thickness. Adjustments are not made for the non-deviating areas.); and
a second set of machining parameters for portions of the toolpath that include the identified differences (Col. 8, “path that adjusts for the deviation in the thickness of second layer of material 26 to reduce a likelihood that porosity, cracks, or lack of fusion occurs at the position with the deviation in thickness – the second set of parameters is for the positions that deviate in thickness”), wherein at least one machining parameter of the second set of machining parameters is different from the first set of machining parameters (Col. 8, “modifying one or more process parameters based on the determination that the thickness of second layer of material 26 is not in the defined range of thicknesses” - modification implies a different set of parameter being used); and
output the machining data to the machining device (Fig. 5, Par. [0072] “After all of the subtractive layers associated with a selected additive layer have been processed, step 522 schedules the subtractive operations for execution”; Par. [0077] “step 528 outputs a hybrid manufacturing program”).
Wilson and Hollander are analogous art because they are from the same field of endeavor and contain functional similarities. They both relate to additive manufacturing using model data.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive manufacturing system, as taught by Wilson, and incorporate a subtractive toolhead to remove material from part surfaces based on identified geometry differences, as taught by Hollander.
One of ordinary skill in the art would have been motivated to improve “detail and dimensional accuracy” as suggested by Hollander (Par. [0016]).
Wilson and Hollander do not explicitly teach wherein the at least one machining parameter includes a change in material removal rate.
However, Murakami teaches wherein the at least one machining parameter includes a change in material removal rate (Col. 2, “setting a machining feed rate for each area with reference to a predetermined parameter corresponding to an attribute of the each sectionalized area, and machining the workpiece based upon the set machining feed rate.” – feed rate is interpreted as a material removal rate).
Wilson, Hollander, and Murakami are analogous art because they are from the same field of endeavor. They all relate to manufacturing.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive manufacturing system, as taught by Wilson and Hollander, and incorporate a machining feed rate parameter, as taught by Murakami.
One of ordinary skill in the art would have been motivated to improve machining efficiency as suggested by Murakami (Col. 2).
Regarding claim 2, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above.
Hollander further teaches wherein the computing device is configured to identify at least one of the identified differences as a defect corresponding to a different density (Fig. 5, Par. [0055] – [0056], “Step 502 receives model data defining the part or parts to be manufactured … model data includes manufacturing data such as specifications of dimensional tolerances, specifications of the number or thickness of subtractive layers … manufacturing parameters for these operations, such as a material deposition density”; Par. [0068] “The difference layer profile specifies the geometry of additively deposited material that needs to be removed using subtractive operations to produce the desired parts’ shapes” – material that needs to be removed due to differing from desired parameters is interpreted as a defect).
Regarding claim 3, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches wherein the plurality of layers includes a plurality of intermediate layers (Col. 11, “images are generated layer-by-layer as the component is formed” – As multiple layers are built, the previously imaged layers become intermediate layers) and
wherein at least one difference of the identified differences is identified in an intermediate layer of the plurality of intermediate layers (Col. 11, “images may be used to determine if the thickness of the most recently added layer is within a defined range” – As more layers a built, the most recently added layer becomes an intermediate layer).
Regarding claim 4, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches, wherein the computing device is further configured to generate model data that includes the identified differences (Col. 11, “The record of the as-build component may include image data including a plurality of images (e.g., one image for each layer used to form the component). The record of the as-built component may be stored by computing device 12 or another computing device, and may be a reference if a defect is discovered during subsequent component testing or during use of the component or if the component is damaged during use of the component … the images for each respective layer may be aggregated and correlated to produce a fully associative three dimensional model of the as-built component; Col. 5, “laser imaging device 18 may produce images that are traceable to a standard, such as a National Institute of Standards and Technology (NIST) standard. This may facilitate use of the images to indicate both integrity of component 22 and dimensional conformity of the as-built component 22 to the digital model on which component 22 is based.”).
Regarding claim 5, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Hollander further teaches wherein, to control the machining device, the computing device (Par. [0100] “computer system suitable for controlling an automated manufacturing system including two independently and simultaneously operating toolheads”) is configured to generate the machining data based on the model data (Fig. 5, Par. [0069] “Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”).
Regarding claim 8, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches wherein the computing device (Col. 7, “computing device 12”) is configured to, for an intermediate layer of the plurality of intermediate layers (Col. 11, “layer-by-layer as the component is formed” – multiple layers mean multiple intermediate layers):
identify the at least one difference for the intermediate layer (Col. 7, “determining, by
computing device 12, based at least in part on the second layer image, whether a thickness of second layer of material 26 is in a defined range of thicknesses (34)”);
control the device based on the at least one difference (Col. 10, “if computing device 12 determines that the powder does include powder defects (the "YES" branch of decision block 44), computing device 12 may perform a predetermined action (46)”); and
control the energy delivery device and the powder delivery device to deposit a subsequent layer on the intermediate layer (Col. 8, “In examples in which the predetermined action includes modifying one or more process parameters based on the determination that the thickness of second layer of material 26 is not in the defined range of thicknesses, the technique may continue by adding a subsequent layer”).
Wilson does not explicitly teach controlling the machining device to machine the build surface.
However, Hollander teaches controlling the machining device to machine the build surface (Fig. 2, Par. [0039] “Step 220 performs subtractive material removal to create fine surface details in the selected subtractive region”).
Regarding claim 9, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches wherein the computing device is further configured to:
evaluate whether at least one difference exceeds a machinability threshold (Col. 7, “determining, by computing device 12, based at least in part on the second layer image, whether a thickness of second layer of material 26 is in a defined range of thicknesses (34)” – defined range of thickness is interpreted as a machinability threshold as the thickness is compared to the defined range); and
in response to the at least one difference exceeding the machinability threshold, controlling the machining device to machine the build surface (Fig. 2, Col. 8, “responsive to determining that the thickness of second layer of material 26 is not in the defined range of thicknesses (the "NO" branch of decision block 34), the technique of FIG. 2 include performing, by computing device 12, a predetermined action (36).” – the predetermined action would be machining the build surface as taught by Hollander.).
Regarding claim 10, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches wherein the at least one topology sensor is configured to measure a topology of material added to the melt pool (Col. 5, “laser imaging device 18 may be positioned substantially directly above component 22 and may include an interferometer, which provides depth information based on the time from outputting a laser pulse to the sensing of the reflected light. In other examples, laser imaging device 18 may be positioned at an offset with respect to component 22 such that the sensor senses depth information without using an interferometer.”; Col. 11, “the images for each respective layer may be aggregated and correlated to produce a fully associative three dimensional model of the as-built component” – depth information and forming a three dimensional model are interpreted as measuring a topology of material.).
Regarding claim 11, Wilson teaches a method for additive manufacturing, comprising:
receiving, by a computing device, topological data for a plurality of layers from one or more sensors of an additive manufacturing system, wherein the topological data is representative of a topology of a build surface of each layer of the plurality of layers (Col. 5, “laser imaging device 18 may be positioned substantially directly above component 22 and may include an interferometer, which provides depth information based on the time from outputting a laser pulse to the sensing of the reflected light. In other examples, laser imaging device 18 may be positioned at an offset with respect to component 22 such that the sensor senses depth information without using an interferometer.”; Col. 2, “storing, by the computing device, the plurality of respective layer images as an image file for the as-built component”; Col. 11, “images are generated layer-by-layer as the component is formed… the images for each respective layer may be aggregated and correlated to produce a fully associative three dimensional model of the as-built component”);
identifying, by the computing device, differences between the topological data and specification data representative of a set of tolerances of the build surface (Col. 11, “images may be used to determine if the thickness of the most recently added layer is within a defined range … when laser scanning is used to image the component, the resulting image data may be compared to the original computer aided design files to verify geometry of the as-built component to the designed component”);
controlling, by the computing device and based on a set of deposition parameters, an energy delivery device to deliver energy to the build surface to form a melt pool and a powder delivery device to direct a powder stream toward the melt pool (Col. 7, “computing device 12 may control the relative position of powder delivery device 14 and stage 20 to direct powder at
or on to surface 28. Computing device 12 also may control energy delivery device 16 (e.g., an energy delivery head) to direct energy to a volume of the powder adjacent to or on surface 28 to join at least some of the powder to first layer of material 24”; Col. 8, “computing device 21 may implement closed-loop control of system 10, such as by modifying one or more process parameters”).
Wilson does not explicitly teach controlling, by the computing device, a machining device to machine the build surface based on the identified differences, wherein to control the machining device, the computing device is configured to:
generate machining data that includes:
a toolpath;
a first set of machining parameters for portions of the toolpath that do not include the identified differences; and
a second set of machining parameters for portions of the toolpath that include the identified differences, wherein at least one machining parameter of the second set of machining parameters is different from the first set of machining parameters, and wherein the at least one machining parameter includes a change in material removal rate; and
output the machining data to the machining device.
However, the combination of Wilson and Hollander teaches a machining device configured to machine the build surface (Hollander, Par. [0016] “subtractive material removal at part surfaces to maximize detail and dimensional accuracy”; Par. [0023] “System 100 also includes M subtractive toolheads 113, where M is one or more. Each of the subtractive toolheads is capable of removing structural or support material in a spatially-localized region, including a finite thickness in the Z dimension, referred to herein as the subtractive layer thickness.”; Par. [0030] “additional subtractive toolheads may also utilize laser machining or any other subtractive manufacturing tool known in the art, including cutting tools, milling spindles, abrasive grinders, electric discharge machining, waterjet cutting, and plasma cutting”);
control the machining device to machine the build surface based on the identified differences (Hollander, Fig. 5, Par. [0068] – [0069] “Step 516 generates a difference layer profile for the selected subtractive layer. The difference layer profile specifies the geometry of additively deposited material that needs to be removed using subtractive operations to produce the desired parts' shapes in the selected subtractive layer … Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”; Par. [0072] “step 522 schedules the subtractive operations for execution”), wherein to control the machining device, the computing device is configured to (Par. [0100] “computer system suitable for controlling an automated manufacturing system including two independently and simultaneously operating toolheads”):
generate machining data that includes (Hollander, Fig. 5, Par. [0069] “Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”):
a toolpath (Wilson, Col. 8, “computing device 12 may control energy delivery device 16 to modify a tool path traced by the focal point or focal volume of the energy beam output by energy delivery device 16”);
a first set of machining parameters for portions of the toolpath that do not include the identified differences (Col. 8, “path that adjusts for the deviation in the thickness of second layer of material 26 to reduce a likelihood that porosity, cracks, or lack of fusion occurs at the position with the deviation in thickness – the first set of parameters is for the positions that do not deviate in thickness. Adjustments are not made for the non-deviating areas.); and
a second set of machining parameters for portions of the toolpath that include the identified differences (Col. 8, “path that adjusts for the deviation in the thickness of second layer of material 26 to reduce a likelihood that porosity, cracks, or lack of fusion occurs at the position with the deviation in thickness – the second set of parameters is for the positions that deviate in thickness”), wherein at least one machining parameter of the second set of machining parameters is different from the first set of machining parameters (Col. 8, “modifying one or more process parameters based on the determination that the thickness of second layer of material 26 is not in the defined range of thicknesses” - modification implies a different set of parameter being used); and
output the machining data to the machining device (Fig. 5, Par. [0072] “After all of the subtractive layers associated with a selected additive layer have been processed, step 522 schedules the subtractive operations for execution”; Par. [0077] “step 528 outputs a hybrid manufacturing program”).
Wilson and Hollander are analogous art because they are from the same field of endeavor and contain functional similarities. They both relate to additive manufacturing using model data.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive manufacturing system, as taught by Wilson, and incorporate a subtractive toolhead to remove material from part surfaces based on identified geometry differences, as taught by Hollander.
One of ordinary skill in the art would have been motivated to improve “detail and dimensional accuracy” as suggested by Hollander (Par. [0016]).
Wilson and Hollander do not explicitly teach wherein the at least one machining parameter includes a change in material removal rate.
However, Murakami teaches wherein the at least one machining parameter includes a change in material removal rate (Col. 2, “setting a machining feed rate for each area with reference to a predetermined parameter corresponding to an attribute of the each sectionalized area, and machining the workpiece based upon the set machining feed rate.” – feed rate is interpreted as a material removal rate).
Wilson, Hollander, and Murakami are analogous art because they are from the same field of endeavor. They all relate to manufacturing.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive manufacturing system, as taught by Wilson and Hollander, and incorporate a machining feed rate parameter, as taught by Murakami.
One of ordinary skill in the art would have been motivated to improve machining efficiency as suggested by Murakami (Col. 2).
However, Hollander teaches controlling, by the computing device, a machining device to machine the build surface based on the identified differences (Par. [0016] “subtractive material removal at part surfaces to maximize detail and dimensional accuracy”; Par. [0023] “System 100 also includes M subtractive toolheads 113, where M is one or more. Each of the subtractive toolheads is capable of removing structural or support material in a spatially-localized region, including a finite thickness in the Z dimension, referred to herein as the subtractive layer thickness.”; Par. [0030] “additional subtractive toolheads may also utilize laser machining or any other subtractive manufacturing tool known in the art, including cutting tools, milling spindles, abrasive grinders, electric discharge machining, waterjet cutting, and plasma cutting”).
Wilson and Hollander are analogous art because they are from the same field of endeavor and contain functional similarities. They both relate to additive manufacturing using model data.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive manufacturing system, as taught by Wilson, and incorporate a subtractive toolhead to remove material from part surfaces based on identified geometry differences, as taught by Hollander.
One of ordinary skill in the art would have been motivated to improve “detail and dimensional accuracy” as suggested by Hollander (Par. [0016]).
Regarding claim 12, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Hollander further teaches identifying at least one of the identified differences as a defect corresponding to a different density (Fig. 5, Par. [0055] – [0056], “Step 502 receives model data defining the part or parts to be manufactured … model data includes manufacturing data such as specifications of dimensional tolerances, specifications of the number or thickness of subtractive layers … manufacturing parameters for these operations, such as a material deposition density”; Par. [0068] “The difference layer profile specifies the geometry of additively deposited material that needs to be removed using subtractive operations to produce the desired parts’ shapes” - material that needs to be removed due to differing from desired parameters is interpreted as a defect).
Regarding claim 13, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches wherein the plurality of layers includes a plurality of intermediate layers (Col. 11, “images are generated layer-by-layer as the component is formed” – As multiple layers are built, the previously imaged layers become intermediate layers), and
wherein at least one difference of the identified differences is identified in an intermediate layer of the plurality of intermediate layers (Col. 11, “images may be used to determine if the thickness of the most recently added layer is within a defined range” – As more layers a built, the most recently added layer becomes an intermediate layer).
Regarding claim 14, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches generating as-deposited model data that includes the identified differences (Col. 3, “a metrology technique, such as laser imaging, may be utilized to image the as-deposited powder “; Col. 11, “The record of the as-build component may include image data including a plurality of images (e.g., one image for each layer used to form the component). The record of the as-built component may be stored by computing device 12 or another computing device, and may be a reference if a defect is discovered during subsequent component testing or during use of the component or if the component is damaged during use of the component … the images for each respective layer may be aggregated and correlated to produce a fully associative three dimensional model of the as-built component; Col. 5, “laser imaging device 18 may produce images that are traceable to a standard, such as a National Institute of Standards and Technology (NIST) standard. This may facilitate use of the images to indicate both integrity of component 22 and dimensional conformity of the as-built component 22 to the digital model on which component 22 is based.”).
Regarding claim 15, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Holland further teaches wherein controlling the machining device (Par. [0100] “computer system suitable for controlling an automated manufacturing system including two independently and simultaneously operating toolheads”) includes:
generating machining data based on the as-deposited model data (Fig. 5, Par. [0068] “Step 516 generates a difference layer profile for the selected subtractive layer. The difference layer profile specifies the geometry of additively deposited material that needs to be removed using subtractive operations to produce the desired parts' shapes in the selected subtractive layer.”; Par. [0069] “Step 518 generates subtractive toolpaths based on the difference layer profile for the selected subtractive layer”).
Regarding claim 18, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches for an intermediate layer (Col. 11, “layer-by-layer as the component is formed” – multiple layers mean multiple intermediate layers):
identifying the at least one difference for the intermediate layer (Col. 7, “determining, by computing device 12, based at least in part on the second layer image, whether a thickness of second layer of material 26 is in a defined range of thicknesses (34)”);
controlling the device based on the at least one difference (Col. 10, “if computing device 12 determines that the powder does include powder defects (the "YES" branch of decision block 44), computing device 12 may perform a predetermined action (46)”); and
controlling the energy delivery device and the powder delivery device to deposit a subsequent layer on the intermediate layer (Col. 8, “In examples in which the predetermined action includes modifying one or more process parameters based on the determination that the thickness of second layer of material 26 is not in the defined range of thicknesses, the technique may continue by adding a subsequent layer.”).
Wilson does not explicitly teach controlling the machining device to machine the build surface.
However, Hollander teaches controlling the machining device to machine the build surface (Fig. 2, Par. [0039] “Step 220 performs subtractive material removal to create fine surface details in the selected subtractive region”).
Regarding claim 19, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches evaluating whether at least one difference exceeds a machinability threshold (Col. 7, “determining, by computing device 12, based at least in part on the second layer image, whether a thickness of second layer of material 26 is in a defined range of thicknesses (34)” – defined range of thickness is interpreted as a machinability threshold as the thickness is compared to the defined range; and
in response to the at least one difference exceeding the machinability threshold, controlling the machining device to machine the build surface (Fig. 2, Col. 8, “responsive to determining that the thickness of second layer of material 26 is not in the defined range of thicknesses (the "NO" branch of decision block 34), the technique of FIG. 2 include performing, by computing device 12, a predetermined action (36).” – the predetermined action would be machining the build surface as taught by Hollander.).
Regarding claim 20, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above
Wilson further teaches wherein the at least one topology sensor is configured to measure a topology of material added to the melt pool (Col. 5, “laser imaging device 18 may be positioned substantially directly above component 22 and may include an interferometer, which provides depth information based on the time from outputting a laser pulse to the sensing of the reflected light. In other examples, laser imaging device 18 may be positioned at an offset with respect to component 22 such that the sensor senses depth information without using an interferometer.”; Col. 11, “the images for each respective layer may be aggregated and correlated to produce a fully associative three dimensional model of the as-built component” – depth information and forming a three dimensional model are interpreted as measuring a topology of material.).
Claim(s) 21 are rejected under 35 U.S.C. 103 as being unpatentable over Wilson et al. US 9,886,015 B2 (hereinafter Wilson) in view of Hollander USPGPUB 2021/0197491 A1 (hereinafter Hollander) and Murakami et al. US 7,070,368 B2 (hereinafter Murakami), and further in view of Aubin et al. USPGPUB 2020/0171620 A1 (hereinafter Aubin).
Regarding claim 21, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above.
Wilson, Hollander, and Murakmai do not explicitly teach wherein the at least one machining parameter different between the first set of machining parameters and the second set of machining parameters further includes a speed of an abrasive surface, an angle of a cutting surface, or a feature size of an abrasive surface.
However, Aubin teaches wherein the at least one machining parameter different between the first set of machining parameters and the second set of machining parameters further includes a speed of an abrasive surface, an angle of a cutting surface, or a feature size of an abrasive surface (Fig. 5, Par. [0066], “the plurality of sanding parameters 126 includes an abrasive-surface velocity 136. The abrasive surface velocity 136 is a velocity of the abrasive surface 120 relative to the sanding tool 102”; Par. [0067], “the abrasive-surface velocity 136 is one of the variable sanding parameters 150. In such an example, the abrasive-surface velocity 136 is one of the sanding parameters 126 that are monitored to determine the actual material removal rate 160 and selectively controlled to achieve the model material removal rate 124 during the sanding operation. For example, the sanding tool 102 may be a variable speed sander. As such, the abrasive-surface velocity 136 is selectively controllable and is adjustable by changing the speed setting of the sander.”).
Wilson, Hollander, Murakami, and Aubin are analogous art because they are from the same field of endeavor and contain functional similarities. They all relate to manufacturing and machining processes involving controlled removal of material from a workpiece.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive and subtractive manufacturing system, as taught by Wilson, Hollander, and Murakami, and incorporate controlling a speed of an abrasive surface as a machining parameter, as taught by Aubin.
One of ordinary skill in the art would have been motivated to improve control of the material removal rate during abrasive machining by controlling the abrasive-surface velocity as suggested by Aubin (Par. [0067]).
Claim(s) 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Wilson et al. US 9,886,015 B2 (hereinafter Wilson) in view of Hollander USPGPUB 2021/0197491 A1 (hereinafter Hollander) and Murakami et al. US 7,070,368 B2 (hereinafter Murakami), and further in view of Nishiwaki et al. USPGPUB 2022/0226935 A1 (hereinafter Nishiwaki).
Regarding claim 22, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above.
Wilson, Hollander, and Murakami do not explicitly teach wherein the computing device is configured to categorize the identified differences into a type of defect, and
wherein the computing device selects the second set of machining parameters based on the categorized type of defect.
However, Nishiwaki teaches wherein the computing device is configured to categorize the identified differences into a type of defect (Par. [0047], “in a case in which multiple types of machining defect, i.e., multiple machining defect modes, are expected, and the machining determination unit 5 is to determine which machining defect mode has occurred”; Par. [0047], “the machining determination unit 5 outputs, as the determination result, for example, information indicating one of defect mode #1, defect mode #2, ... , defect mode #n, and no machining defect”), and
wherein the computing device selects the second set of machining parameters based on the categorized type of defect (Par. [0058], “when the machining determination unit 5 outputs a determination result that is a machining defect mode, the condition search unit 6 may determine the control parameter to be used in the search, based on the machining defect mode, and instruct the test machining condition generation unit 9 to generate a machining condition including the determined control parameter whose value has been modified.”).
Wilson, Hollander, Murakami, and Nishiwaki are analogous art because they are from the same field of endeavor. They all relate to manufacturing and machining systems using controlled machining parameters.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive and subtractive manufacturing system, as taught by Wilson, Hollander, and Murakami, and incorporate categorizing identified differences into a type of defect and selecting the second set of machining parameters based on the categorized type of defect, as taught by Nishiwaki.
One of ordinary skill in the art would have been motivated to improve the efficiency of determining suitable machining conditions when a machining defect is detected, as suggested by Nishiwaki (Par. [0058]).
Regarding claim 23, the combination of Wilson, Hollander, Murakami, and Nishiwaki teaches all the limitations of the base claims as outlined above.
Wilson further teaches wherein the categorized type of defect indicates an unfused powder defect or a warping defect (Col. 4, lines 17-20, “wherein the categorized type of defect indicates an unfused powder defect or a warping defect” – in the combined system, the lack of fusion defect taught by Wilson would constitute one of the defect types categorized according to Nishiwaki’s machining defect mode teachings.).
Regarding claim 24, the combination of Wilson, Hollander, and Murakami teaches all the limitations of the base claims as outlined above.
Wilson, Hollander, and Murakami do not explicitly teach categorizing the identified differences into a type of defect, wherein the second set of machining parameters is selected based on the categorized type of defect.
However, Nishiwaki teaches categorizing the identified differences into a type of defect (Par. [0047], “in a case in which multiple types of machining defect, i.e., multiple machining defect modes, are expected, and the machining determination unit 5 is to determine which machining defect mode has occurred”; Par. [0047], “the machining determination unit 5 outputs, as the determination result, for example, information indicating one of defect mode #1, defect mode #2, ... , defect mode #n, and no machining defect”), wherein the second set of machining parameters is selected based on the categorized type of defect (Par. [0058], “when the machining determination unit 5 outputs a determination result that is a machining defect mode, the condition search unit 6 may determine the control parameter to be used in the search, based on the machining defect mode, and instruct the test machining condition generation unit 9 to generate a machining condition including the determined control parameter whose value has been modified.”).
Wilson, Hollander, Murakami, and Nishiwaki are analogous art because they are from the same field of endeavor. They all relate to manufacturing and machining systems using controlled machining parameters.
Therefore, at the time of effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the above additive and subtractive manufacturing system, as taught by Wilson, Hollander, and Murakami, and incorporate categorizing identified differences into a type of defect and selecting the second set of machining parameters based on the categorized type of defect, as taught by Nishiwaki.
One of ordinary skill in the art would have been motivated to improve the efficiency of determining suitable machining conditions when a machining defect is detected, as suggested by Nishiwaki (Par. [0058]).
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
DehghanNiri et al. [USPGPUB 2018/0099333 A1] teaches obtaining, in real time
during a 3D manufacturing build process in which at least one structure is built by the 3D manufacturing apparatus, a topographical scan of an area of a build platform on which the at least one structure is built.
Matusik et al. [US 10,456,984 B2] teaches a scanning system to monitor an additively manufactured object as it is being fabricated and adapting the geometric shape and material composition of the subsequent layers based on the scan data.
Conclusion
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/PETER XU/ Examiner, Art Unit 2119
/MOHAMMAD ALI/ Supervisory Patent Examiner, Art Unit 2119
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