DETAILED ACTION
Claims 1-20 (filed 08/13/2026) have been considered in this action. Claims 1, 10-11 and 20 have been amended. Claims 2-9 and 12-19 have been presented in the same format as previously presented.
Response to Arguments
Applicant’s arguments, see page 1 paragraph 3, filed 08/13/2026, with respect to objection to the title have been fully considered and are persuasive. The objection of the title has been withdrawn.
Applicant’s arguments, see page 1 paragraph 4, filed 08/13/2026, with respect to rejection of claims 10 and 20 under 35 U.S.C. 112(b) have been fully considered and are persuasive. The rejection of claims 10 and 20 under 35 U.S.C. 112(b) has been withdrawn.
Applicant’s arguments, see page 2 paragraph 1, filed 08/13/2026, with respect to rejection of claims 1-20 under 35 U.S.C. 112(b) for the use of “datum” have been fully considered and are persuasive. The rejection of claims 1-20 under 35 U.S.C. 112(b) has been withdrawn.
Applicant’s arguments, see page 3 paragraph 1, filed 08/13/2026 with respect to the rejection(s) of claim(s) 1-20 under 35 U.S.C. 103 over Sawyer (US 20240354471) in view of Komminani (US 20230342594) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of King et al. (US 20220215133, hereinafter King) which teaches the use of comparison against tolerances of previously manufactured parts for determining manufacturability datum. See below for a mapping of the newly amended features to King.
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) 1-8, 10-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sawyer et al. (US 20240354471, hereinafter Sawyer) in view of Komminani et al. (US 20230342594, hereinafter Komminani) and King et al. (US 20220215133, hereinafter King).
In regards to Claim 1, Sawyer teaches “An apparatus for dimensioning and modifying a part to be manufactured, the apparatus comprising: at least a processor; and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to:” ([0017] Apparatus 100 includes a processor 104. Processor 104 may include any computing device as described in this disclosure, including without limitation a microcontroller, microprocessor, digital signal processor (DSP) and/or system on a chip (SoC) as described in this disclosure [0019] With continued reference to FIG. 1, a memory is communicatively connected to the at least a processor 104) “receive part information for a part to be manufactured, wherein the part information for the part to be manufactured comprises a print of the part to be manufactured” ([0003] The memory containing instructions configuring the at least a processor to receive a computer model comprising a plurality of model-based definitions, wherein the computer model is representative of the part to be manufactured [0023] Still referring to FIG. 1, the computer model 108 may include a plurality of model-based definitions 116. As used in the current disclosure, a “model-based definition” is a geometry and Product Manufacturing Information (PMI), which are annotations within the computer model 108 that is used to define an individual component or elements of the part for manufacture 112.; [0026] Still referring to FIG. 1, model-based definitions 116 may be represented on a print. A print may include an image representing part for manufacture 112 or a component of the part for manufacture 112, a number representing a numerical tolerance of the component, and/or an indicator that identifies the numerical tolerance is associated with the component. Print may also indicate a unit of measurement and/or a scale, which may be included in model-based definitions 116) “extract at least one tolerance datum from the print using a machine-learning process, wherein the at least one tolerance datum comprises semantic information” ([0023] Model-based definitions may further specify the modeled geometry or provide PMI that stipulates certain requirements on how an item must be manufactured. In some embodiments, a processor 104 may be configured to encode model-based definitions 116 onto the computer model. Encoding may include taking information that defines an individual component of the part for manufacture 112 and converting it in to form that may be display into computer model 108. Encoding may additionally include overlaying the defining information within the computer model 108. Defining an individual component or element may include information regarding geometric dimensioning and tolerancing (GD&T) information, component level materials, assembly level bills of materials, engineering configurations, surface finish, weld symbol, engineering history (including references to or embedded change orders and change notices), legal/proprietary notices, manufacturing processes, design intent, semantic data, material specifications, heat treatment specifications, ASTM specification, military specifications (MILSPEC), and the like [0026] Processor 104 may be configured to identify the unit of measurement stated in print and determine that the radius tolerance for the circle is +/−0.0003 inches. In another non-limiting example, the leader may be pointing from a GD&T annotation of a total runout tolerance of 0.03 with respect to one or more features, as shown in FIG. 2. [0027] As used in the current disclosure, a “print” may be a two-dimensional representation of a part for manufacture 112. A print may include any data describing the part for manufacture 112. Print may include semantic information of part for manufacture 112. Print may include geometric dimensioning and tolerancing (GD&T) information; wherein in order to encode such information extracted from a print onto a model, it was extracted from the available semantic data) “determine at least one manufacturability datum…wherein determining the at least one manufacturability datum comprises determining an unmachinable quality of the part to be manufactured as a function of a predetermined range” ([0034] With continued reference to FIG. 1, processor 104 may be configured to identify unmanufacturable qualities of the part. As used in the current disclosure, “unmanufacturable qualities” is any quality of the part to be manufactured 112 causes the part to be determined as unmanufacturable...Processor 104 may be configured to cross-reference the model-based definitions 116 of the part to be manufactured 112 with the manufacturer specifications 124 to identify an unmanufacturable quality of the component. ...A processor 104 may also identify the time that it takes to set-up and machine the component and compare this to the cost to manufacture that component. If either the cost to make the component or the time it would take to make the component are unrealistic the component may be deemed unmanufacturable; [0035] Processor 104 may be configured to output a plurality of different suggestions to improve machinability of the part for manufacture 112. In an embodiment, the corrections may be made as function of the identification of the unmanufacturable qualities of the component. For example, the processor 104 may have identified the component has a tight geometric tolerance which makes the component unmachinable; [0040] A fuzzy set may also be used to show degree of match between fuzzy sets may be used to rank one resource against another. For instance, if both manufacturing specifications 124 and model-based definitions 116 have fuzzy sets, the manufacturability of the part to be manufactured 120 may be identified by having a degree of overlap exceeding a predetermined threshold) “generate at least one correction, wherein the at least one correction is configured to improve machinability of the part to be manufactured” ([0035] With continued reference to FIG. 1, processor 104 may be configured to identify corrections to the part to improve machinability. Corrections to the part may include suggestions to use a different material that is more machinable. In other embodiments, corrections may include suggesting a larger tolerance for a particular feature of the part for manufacture 112. Slight changes to the geometry of the features of the part may also be suggested to improve manufacturability. In embodiments, Processor 104 may be configured to output a plurality of different suggestions to improve machinability of the part for manufacture 112) “create at least one updated tolerance datum as a function of the at least one manufacturability datum;” ([0035] corrections may include suggesting a larger tolerance for a particular feature of the part for manufacture 112. Slight changes to the geometry of the features of the part may also be suggested to improve manufacturability. In embodiments, Processor 104 may be configured to output a plurality of different suggestions to improve machinability of the part for manufacture 112. In an embodiment, the corrections may be made as function of the identification of the unmanufacturable qualities of the component. For example, the processor 104 may have identified the component has a tight geometric tolerance which makes the component unmachinable. The processor 104 may identify geometric tolerance the manufacturer can offer as a function of the manufacturer specifications 124. Then the processor 104 may apply those tolerances to the component as correction to the part for manufacture 112, Part corrections may be displayed within the manufacturing quote) “create an updated print of the part to be manufactured, wherein the updated print of the part to be manufactured incorporates the at least one updated tolerance datum;” ([0026] processor 104 may encode onto the computer model 108 or a print that the dimensions are in inches, and that the scale is “2:1”, include a circle representing an exterior cylindrical surface of part for manufacture 112, and have a leader (typically depicted as an arrow) pointing from “R0.5000+/−0.0003” to the circle. Processor 104 may be configured to insert “+/−” as a symbol representing a tolerance for the preceding number in the amount of the succeeding number. Processor 104 may also be configured to insert a leader pointing from the numbers to the circle, the tolerance for the circle is detailed by the numbers, specifically the radius of the circle. Processor 104 may be configured to identify the unit of measurement stated in print and determine that the radius tolerance for the circle is +/−0.0003 inches. In another non-limiting example, the leader may be pointing from a GD&T annotation of a total runout tolerance of 0.03 with respect to one or more features, as shown in FIG. 2; wherein because the tolerances are encoded/added to the print, they are considered to make an updated print; [0035] processor 104 may be configured to identify corrections to the part to improve machinability. Corrections to the part may include suggestions to use a different material that is more machinable. In other embodiments, corrections may include suggesting a larger tolerance for a particular feature of the part for manufacture 112. Slight changes to the geometry of the features of the part may also be suggested to improve manufacturability. In embodiments, Processor 104 may be configured to output a plurality of different suggestions to improve machinability of the part for manufacture 112. In an embodiment, the corrections may be made as function of the identification of the unmanufacturable qualities of the component. For example, the processor 104 may have identified the component has a tight geometric tolerance which makes the component unmachinable. The processor 104 may identify geometric tolerance the manufacturer can offer as a function of the manufacturer specifications 124. Then the processor 104 may apply those tolerances to the component as correction to the part for manufacture 112, Part corrections may be displayed within the manufacturing quote) “generate a manufacturing quote based on the at least one updated tolerance datum” ([0035] the processor 104 may have identified the component has a tight geometric tolerance which makes the component unmachinable. The processor 104 may identify geometric tolerance the manufacturer can offer as a function of the manufacturer specifications 124. Then the processor 104 may apply those tolerances to the component as correction to the part for manufacture 112, Part corrections may be displayed within the manufacturing quote) “transmit the manufacturing quote and the updated print to a user interface” ([0035] Part corrections may be displayed within the manufacturing quote. [0044] With continued reference to FIG. 1, processor 104 may be configured to generate a manufacturing quote as a function of the manufacturability of the part to be manufactured 112. As used in the current disclosure, a “manufacturing quote” is a report detailing the dimensions of the part and the manufacturability of the part to be manufactured. A manufacturing quote may also include the geometrical tolerances to go with each feature of the part and the ability of the manufacturer to deliver those geometrical tolerances. A manufacturing quote may include a recommendation of which work materials to use to manufacture the part out of. In some embodiments, a manufacturing quote may include suggested methods of assembly for the part. A manufacturing quote may also include suggestions on the most efficient order of assembly for the part. [0082] Display adapter 952 and display device 936 may be utilized in combination with processor 904 to provide graphical representations of aspects of the present disclosure).
Sawyer fails to teach “determine at least one manufacturability datum by comparing the at least one tolerance datum against a database of previously manufactured parts…; extract at least one tolerance datum from the print using a machine-learning process”. While Sawyer teaches that tolerance datum in the form of tolerances or semantic information are extracted, they fail to explicitly recite that the extraction is performed using machine learning.
Komminani teaches “extract at least one tolerance datum from the print using a machine-learning process” ([0084] The AI-based computing system 104 uses computer vision and graph based deep reinforcement learning agents to learn to distinguish different data on the one or more engineering drawings and extract the dimensional data. Further, the AI-based computing system 104 solves the problem of manually reading the scanned engineering drawings and extracting relevant dimensions for quality checking of manufactured parts. In an embodiment of the present disclosure, the trained dimension recognition based deep reinforcement learning model is trained to get the class of the individual node to distinguish required dimensions from all other dimensions present on the one or more engineering drawings 230. Furthermore, the AI-based computing system 104 automatically extract dimensions and tolerances from the scanned engineering drawings that may be fed into the CMM (Coordinate measurement machines) for quality inspection of manufactured parts. Further, the extracted dimensions and tolerances from the scanned engineering drawings may also be sent to a database for reporting purposes).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system for determining manufacturability and an updated tolerance from the determined manufacturability of a product from extracted data from prints of a part to be manufactured as taught by Sawyer, with the use of machine learning based extraction of dimensions and tolerances from engineering prints/drawings as taught by Komminani because it can be considered taking a known method of using machine learning to extract tolerances from drawings, and using it to improve the method that extracts tolerances from drawings in an unspecified manner in a known way that achieves predictable results.
The combination of Sawyer and Komminani fail to teach “determine at least one manufacturability datum by comparing the at least one tolerance datum against a database of previously manufactured parts…;”.
King teaches “determine at least one manufacturability datum by comparing the at least one tolerance datum against a database of previously manufactured parts” ([0051] In one or more embodiments, the computation component 112, and/or associate components of the computation component 112, can compare product features and/or manufacturing details of an initialized manufacturing quote to historical data stored in the one or more data repositories 108 to facilitate one or more of the various features described herein. For example, the computation component 112 can reference the one or more data repositories 108 for information regarding previously manufactured products, CAD models of previously manufactured products, geometry information about previously manufactured products, tolerance requirements tolerances achieved, manufacturing conditions, previously executed manufacturing quotes, previously incurred costs, a combination thereof, and/or the like...the data included in the one or more data repositories 108 can include past costs associated with one or more manufacturing materials, manufacturing facility 130 operations, labor, and/or shipping. In another example, the data included in the one or more data repositories 108 can include one or more references tables regarding manufacturing conditions (e.g., lead times, energy requirements, machining employed, tolerance values achieved) associated with one or more manufacturing processes and/or techniques. [0152] Once the product features are identified, the one or more entities can select (e.g., via the one or more input devices 106 interacting with one or more manufacturing reports 312) specific product features and the tolerance component 1902 can report expected tolerance for the selected features. Alternatively, the tolerance component 1902 can determine expected tolerances for each product features defined in the digital product design. Additionally, the one or more entities can enter (e.g., via the one or more input devices 106 interacting with, for example, the input section 610 of a manufacturability report 312) one or more target tolerance values for one or more designated product features, whereupon the tolerance component 1902 can determine whether the target tolerance values can be achieved. In various embodiments, the determinations of the tolerance component 1902 can be populated into the one or more manufacturability reports 312 via the manufacturability report component 402 (e.g., as text, images, graphs, a combination thereof, and/or the like… the tolerance component 1902 can identify previously manufactured products with similar product features and/or manufacturing processes establish a basis for the tolerance calculation. For instance, the tolerance component 1902 can expect product features of similar size, manufacturing process, and/or manufacturing conditions to achieve similar tolerance values (e.g., within a standard deviation range). Thereby, the tolerance component 1902 can reference, for example, the order data 126 and/or part data 126 of the one or more data repositories 108 to identify previously manufactured products with product features of similar size and/or properties manufactured by similar manufacturing details (e.g., such as manufacturing technique, material selection, and/or manufacturing conditions)) “wherein determining the at least one manufacturability datum comprises determining an unmachinable quality of the part to be manufactured as a function of a predetermined range;” ([0087] In various embodiments, the manufacturability component 508 can further generate one or more recommendations. The recommendations can identify, for example, specific features that should be altered to make the product manufacturable, to avoid potential defects, and/or to achieve desired tolerances. The recommendations can describe, for example, alterations to the one or more manufacturing details and/or digital product design that can enhance compatibility between the digital product design and the one or more manufacturing details. For example, the manufacturability component 508 can generate one or more recommendations based on the generation of one or more warnings associated with one or more of the manufacturability considerations. ...For instance, where the size of a product feature is outside a permissible range associated with the chosen manufacturing process (e.g., as defined by range data within the one or more data repositories 108), the manufacturability component 508 can generate one or more recommendations to alter the product feature size to dimensions within the permissible range and/or alter the manufacturing process to a process associated with a permissible size range that encompasses the given dimensions. For instance, when the size of a product feature is outside a permissible range associated with the chosen manufacturing process (e.g., as defined by range data within the one or more data repositories 108), the manufacturability component 508 can generate one or more recommendations to choose a different manufacturing process and/or material; wherein the various warning as it relates to dimensions outside a manufacturable range are considered unmachinable quality) “create at least one updated tolerance datum as a function of the at least one manufacturability datum;” ([0152] In a further example, the tolerance component 1902 can identify previously manufactured products with similar product features and/or manufacturing processes establish a basis for the tolerance calculation. For instance, the tolerance component 1902 can expect product features of similar size, manufacturing process, and/or manufacturing conditions to achieve similar tolerance values (e.g., within a standard deviation range). Thereby, the tolerance component 1902 can reference, for example, the order data 126 and/or part data 126 of the one or more data repositories 108 to identify previously manufactured products with product features of similar size and/or properties manufactured by similar manufacturing details (e.g., such as manufacturing technique, material selection, and/or manufacturing conditions). [0154] In one or more embodiments, the tolerance component 1902 can update one or more tolerance calculations in response to an alteration to one or more of the manufacturing details. Further, in various embodiments, the tolerance component 1902 can prepare multiple tolerance determinations, each with regards to a respective manufacturing detail or combination of manufacturing details, to compare the effect of one or more alterations to the manufacturing details on the tolerances of the manufactured product.).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the invention to have taken the known features of King in which a manufacturability datum is determined from comparison against previously manufactured parts, and which further determines a warning when unmachinable conditions are expected and is able to update the tolerance on the basis of these warnings, with the manufacturing design system that determines a manufacturability according to a model as taught by Sawyer, because both Sawyer and King can be considered in the related field of producing a quote for a model of an object to be manufactured, and providing various data on the manufacturability of said model to a user to improve the user’s experience. By using the comparison of past tolerances for determining manufacturability and using updated tolerances to provide a plurality of manufacturing quotes for a plurality of the same product with different tolerances, a user would gain the obvious benefit of improved product design at a lower cost while taking into consideration the capabilities of different manufacturing processes. By combining these elements, it can be considered taking the known features of King in which tolerances of past manufactured parts are used in a comparison against a designed part’s model so that determinations on the manufacturability and checking that the dimensions are within ranges, and using these features to improve the product design and quoting system of Sawyer in a known way that achieves predictable results.
In regards to Claim 11, a method is claimed with corresponding steps to those performed by the apparatus of claim 1. Accordingly, claim 11 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 1.
In regards to Claim 2, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 1 above. Sawyer further teaches “The apparatus of claim 1, wherein the manufacturing quote comprises one or more of the at least one updated tolerance datum and the manufacturability datum” ([0044] A manufacturing quote may also include the geometrical tolerances to go with each feature of the part and the ability of the manufacturer to deliver those geometrical tolerances. A manufacturing quote may include a recommendation of which work materials to use to manufacture the part out of. In some embodiments, a manufacturing quote may include suggested methods of assembly for the part. A manufacturing quote may also include suggestions on the most efficient order of assembly for the part. Manufacturing quotes may also denote that the part is unable to be manufactured due to issues regarding manufacturing specifications 124 and model-based definitions 116. Additionally, a manufacturing quote may make suggestions on corrections to an unmachinable part in order to make it manufacturable. These suggestions may include increasing the tolerances for various features, or changing the material of the part, using other machining tools. In an embodiment, a manufacturing quote may be generated using a domain specific language).
In regards to Claim 12, a method is claimed with corresponding steps to those performed by the apparatus of claim 2. Accordingly, claim 12 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 2.
In regards to Claim 3, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 1 above. Sawyer further teaches “The apparatus of claim 1, wherein the manufacturing quote comprises a recommendation of which work materials to use to manufacture the part” ([0044] A manufacturing quote may also include the geometrical tolerances to go with each feature of the part and the ability of the manufacturer to deliver those geometrical tolerances. A manufacturing quote may include a recommendation of which work materials to use to manufacture the part out of. In some embodiments, a manufacturing quote may include suggested methods of assembly for the part. A manufacturing quote may also include suggestions on the most efficient order of assembly for the part. Manufacturing quotes may also denote that the part is unable to be manufactured due to issues regarding manufacturing specifications 124 and model-based definitions 116. Additionally, a manufacturing quote may make suggestions on corrections to an unmachinable part in order to make it manufacturable. These suggestions may include increasing the tolerances for various features, or changing the material of the part, using other machining tools. In an embodiment, a manufacturing quote may be generated using a domain specific language).
In regards to Claim 13, a method is claimed with corresponding steps to those performed by the apparatus of claim 3. Accordingly, claim 13 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 3.
In regards to Claim 4, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 1 above. Sawyer further teaches “The apparatus of claim 1, wherein the manufacturing quote comprises an order of assembly for the part.” ([0044] A manufacturing quote may also include the geometrical tolerances to go with each feature of the part and the ability of the manufacturer to deliver those geometrical tolerances. A manufacturing quote may include a recommendation of which work materials to use to manufacture the part out of. In some embodiments, a manufacturing quote may include suggested methods of assembly for the part. A manufacturing quote may also include suggestions on the most efficient order of assembly for the part. Manufacturing quotes may also denote that the part is unable to be manufactured due to issues regarding manufacturing specifications 124 and model-based definitions 116. Additionally, a manufacturing quote may make suggestions on corrections to an unmachinable part in order to make it manufacturable. These suggestions may include increasing the tolerances for various features, or changing the material of the part, using other machining tools. In an embodiment, a manufacturing quote may be generated using a domain specific language).
In regards to Claim 14, a method is claimed with corresponding steps to those performed by the apparatus of claim 4. Accordingly, claim 14 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 4.
In regards to Claim 5, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 1 above. Sawyer further teaches “The apparatus of claim 1, wherein the memory contains instructions further configuring the at least a processor to construct an updated representative part model of the part to be manufactured as a function of the at least one updated tolerance datum” ([0023] a processor 104 may be configured to encode model-based definitions 116 onto the computer model. Encoding may include taking information that defines an individual component of the part for manufacture 112 and converting it in to form that may be display into computer model 108. Encoding may additionally include overlaying the defining information within the computer model 108. Defining an individual component or element may include information regarding geometric dimensioning and tolerancing (GD&T) information, component level materials, assembly level bills of materials, engineering configurations, surface finish, weld symbol, engineering history (including references to or embedded change orders and change notices), legal/proprietary notices, manufacturing processes, design intent, semantic data, material specifications, heat treatment specifications, ASTM specification, military specifications (MILSPEC), and the like. [0044] processor 104 may encode onto the computer model 108 or a print that the dimensions are in inches, and that the scale is “2:1”, include a circle representing an exterior cylindrical surface of part for manufacture 112, and have a leader (typically depicted as an arrow) pointing from “R0.5000+/−0.0003” to the circle. Processor 104 may be configured to insert “+/−” as a symbol representing a tolerance for the preceding number in the amount of the succeeding number. Processor 104 may also be configured to insert a leader pointing from the numbers to the circle, the tolerance for the circle is detailed by the numbers, specifically the radius of the circle. Processor 104 may be configured to identify the unit of measurement stated in print and determine that the radius tolerance for the circle is +/−0.0003 inches. In another non-limiting example, the leader may be pointing from a GD&T annotation of a total runout tolerance of 0.03 with respect to one or more features, as shown in FIG. 2).
In regards to Claim 15, a method is claimed with corresponding steps to those performed by the apparatus of claim 5. Accordingly, claim 15 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 5.
In regards to Claim 6, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 5 above. Sawyer further teaches “The apparatus of claim 5, wherein the updated representative part model comprises a plurality of sides, wherein each of the plurality of sides comprises a view of the updated representative part model from a plane orthogonal to an axis passing through an origin of the updated representative part model” ([0021] Still referring to FIG. 1, computer model 108 may include a plurality of sides of part for manufacture 112. Each side of the plurality of sides, as used in this disclosure, may be a view of computer model 108 from a plane orthogonal to an axis passing through an origin of computer model 108. Views may also include various types of projections, auxiliary views, cross sections, and the like).
In regards to Claim 16, a method is claimed with corresponding steps to those performed by the apparatus of claim 6. Accordingly, claim 16 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 6.
In regards to Claim 7, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 1 above. Sawyer further teaches “The apparatus of claim 1, wherein the memory contains instructions further configuring the at least a processor to transmit, to the user interface, a recommended parameter modification” ([0035] With continued reference to FIG. 1, processor 104 may be configured to identify corrections to the part to improve machinability. Corrections to the part may include suggestions to use a different material that is more machinable. In other embodiments, corrections may include suggesting a larger tolerance for a particular feature of the part for manufacture 112. Slight changes to the geometry of the features of the part may also be suggested to improve manufacturability. In embodiments, Processor 104 may be configured to output a plurality of different suggestions to improve machinability of the part for manufacture 112. In an embodiment, the corrections may be made as function of the identification of the unmanufacturable qualities of the component. For example, the processor 104 may have identified the component has a tight geometric tolerance which makes the component unmachinable. The processor 104 may identify geometric tolerance the manufacturer can offer as a function of the manufacturer specifications 124. Then the processor 104 may apply those tolerances to the component as correction to the part for manufacture 112, Part corrections may be displayed within the manufacturing quote).
In regards to Claim 17, a method is claimed with corresponding steps to those performed by the apparatus of claim 7. Accordingly, claim 17 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 7.
In regards to Claim 8, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 7 above. Sawyer further teaches “The apparatus of claim 7, wherein the recommended parameter modification comprises one or more rationales” ([0034] With continued reference to FIG. 1, processor 104 may be configured to identify unmanufacturable qualities of the part. As used in the current disclosure, “unmanufacturable qualities” is any quality of the part to be manufactured 112 causes the part to be determined as unmanufacturable. In a non-limiting example, unmachinable qualities may include work material considerations, time, cost, the tools that are currently available, set-up and load time for the part to be manufactured, and the like. Processor 104 may be configured to cross-reference the model-based definitions 116 of the part to be manufactured 112 with the manufacturer specifications 124 to identify an unmanufacturable quality of the component. For example, a part to be manufactured 112 may include component that requires the manufacturer to machine the part out of metals that are notoriously difficult to work with, which may be reflected within the model-based definitions 116 for the part to be manufactured 112. Continuing with the example, the manufacturer specifications 124 may denote that the manufacturer cannot work with this particular metal thus making the component unmanufacturable. A processor 104 may also identify the time that it takes to set-up and machine the component and compare this to the cost to manufacture that component. If either the cost to make the component or the time it would take to make the component are unrealistic the component may be deemed unmanufacturable. The unmachinable qualities of the part may be displayed within the manufacturing quote or on the User device; wherein the rationale is that the metal is difficult to work with or that the manufacturer does not work with this particular metal when a different metal is suggested/recommended).
In regards to Claim 18, a method is claimed with corresponding steps to those performed by the apparatus of claim 8. Accordingly, claim 18 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 8.
In regards to Claim 10, the combination of Sawyer, Komminani and King teach the apparatus for dimensioning and modifying a part as incorporated by claim 1 above. Sawyer further teaches “The apparatus of claim 1, wherein the at least one updated tolerance datum comprises an annotation in the print” ([0023] Still referring to FIG. 1, the computer model 108 may include a plurality of model-based definitions 116. As used in the current disclosure, a “model-based definition” is a geometry and Product Manufacturing Information (PMI), which are annotations within the computer model 108 that is used to define an individual component or elements of the part for manufacture 112. Model-based definitions may further specify the modeled geometry or provide PMI that stipulates certain requirements on how an item must be manufactured. In some embodiments, a processor 104 may be configured to encode model-based definitions 116 onto the computer model. Encoding may include taking information that defines an individual component of the part for manufacture 112 and converting it in to form that may be display into computer model 108. Encoding may additionally include overlaying the defining information within the computer model 108. Defining an individual component or element may include information regarding geometric dimensioning and tolerancing (GD&T) information).
In regards to Claim 20, a method is claimed with corresponding steps to those performed by the apparatus of claim 10. Accordingly, claim 20 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani and King using a similar analysis as that applied to claim 10.
Claim(s) 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Sawyer, Komminani and King as applied to claims 1 and 10 above, and further in view of Knapp et al. (US 20220203637, hereinafter Knapp).
In regards to Claim 9, the combination of Sawyer, Komminani and King teaches the apparatus for dimensioning and modifying a part as incorporated by claim 1 above.
Sawyer further teaches “The apparatus of claim 1, wherein the memory contains instructions further configuring the at least a processor to create the at least one updated tolerance datum using a machine-learning model trained with a training set” ([0035] In an embodiment, the corrections may be made as function of the identification of the unmanufacturable qualities of the component. For example, the processor 104 may have identified the component has a tight geometric tolerance which makes the component unmachinable. The processor 104 may identify geometric tolerance the manufacturer can offer as a function of the manufacturer specifications 124. Then the processor 104 may apply those tolerances to the component as correction to the part for manufacture 112; [0036] With continued reference to FIG. 1, processor 104 may determine manufacturability of the part to be manufactured 120 using a manufacturability machine learning model. As used in the current disclosure, a “manufacturability machine learning model” is a mathematical and/or algorithmic representation of a relationship between inputs and outputs…. Inputs to the to the manufacturability machine learning model may include model-based definitions 116, manufacturing specifications 124, examples of manufacturability of a part for manufacturer 112, examples of a manufacturability score, and the like. The output of the manufacturability machine learning model may include a prediction of the manufacturability of a part for manufacturer 112 and a manufacturability score. Manufacturability machine learning model may by trained using manufacturability training data…. Manufacturability training data may be stored in a database, such as a training data database, or remote data storage device, or a user input or device. In an embodiment, a manufacturability training data may be iteratively updated with the input and output results of the manufacturability machine learning model. Updated manufacturability training data may then be used to retrain manufacturability machine learning model using a feedback loop.; wherein manufacturability is used to determine the tolerance corrections, which is based on a machine learning model).
Sawyer, Komminani and King fail to teach “wherein the training set comprises past corrections and updated tolerance datum”.
Knapp teaches “wherein the training set comprises past corrections and updated tolerance datum” ([0024] The metrics data structure 132 can include, store, or maintain various metrics used to determine the tolerance of the splice. The metrics can refer to one or more functions to derive at least a splice deviation, splice tolerance, slope derivative, slope stability, or other functions related to dataset analysis, such as shown in FIGS. 4 and 5. ...The metrics data structure 132 can be updated or manipulated by the data processing system 110. [0052] The machine learning engine 120 can train one or more models stored in the model data structure 134 based on, for example, a degree to which splices, prior to manufacturing the splices into a tire, deviate from a predetermine splice point. The deviation can refer to a delta difference between the tolerance of the splice and an ideal tolerance value corresponding to the splices. The degree of tolerance can refer to various parameters, such as temperature, pressure, orientation, or position of the tire during manufacturing or assembly process. The machine learning engine 120 can further train the one or more models based on at least one result of the previous splice).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system which determines a manufacturability of a part using machine learning which is then used to suggest corrections to tolerance datum for improving manufacturability using training data as taught by Sawyer, with the use of past corrections and updated tolerance data in the training data as taught by Knapp, because it would gain the obvious benefit of learning from past correction and updated tolerance data in order to make future improvements. This is suggested by Sawyer when stating that the training can be a feedback loop that incorporates improvements into the model so the model becomes more and more accurate ([0036]). By combining these elements. It can be considered taking the known use of training data that contains past tolerance and corrections to manufacturing, and using it to improve the training data of Sawyer that determines a manufacturability for suggesting corrections to tolerances in a known way that achieves predictable results.
In regards to Claim 19, a method is claimed with corresponding steps to those performed by the apparatus of claim 9. Accordingly, claim 19 is rejected under 35 U.S.C. 103 in view of Sawyer, Komminani King and Knapp using a similar analysis as that applied to claim 9.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JONATHAN MICHAEL SKRZYCKI/Examiner, Art Unit 2116
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