DETAILED ACTION
Claims 1-20 (filed 02/27/2024) have been considered in this action. Claims 1-20 are newly filed.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: METHODS AND APPARATUSES FOR DIMENSIONING AND MODIFYING A PART TO BE MANUFACTURED BY UPDATING TOLERANCE DATUM AS A FUNCTION OF MANUFACTURABILITY.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10 and 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 10 and 20 recite the limitation "the tolerance datum" in their respective limitations. There is insufficient antecedent basis for this limitation in the claim. For the sake of compact prosecution the examiner shall consider this phrase to refer to “the at least one tolerance datum” or “at least one updated tolerance datum”.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Where applicant acts as his or her own lexicographer to specifically define a term of a claim contrary to its ordinary meaning, the written description must clearly redefine the claim term and set forth the uncommon definition so as to put one reasonably skilled in the art on notice that the applicant intended to so redefine that claim term. Process Control Corp. v. HydReclaim Corp., 190 F.3d 1350, 1357, 52 USPQ2d 1029, 1033 (Fed. Cir. 1999). The term “tolerance datum” in claims 1 and 11 is used by the claim to mean “data that reflects tolerance and semantic data and is open-ended in meaning” while the accepted meaning is “a single piece of data reflecting tolerance.” The term is indefinite because the specification does not clearly redefine the term. PHOSITA would understand that the plain-meaning definition of datum is the singular form of data, meaning a single piece of data is a datum. In order for a datum to reflect a single piece of information, it can by its very nature only reflect tolerance when said datum is called tolerance datum, as would be understood by PHOSITA because it is in the term itself what that datum is reflecting (i.e. tolerance). However, the claim attempts to improperly redefine the plain-language meaning of this term without ever explicitly redefining that tolerance datum can include other forms of data, including at the least semantic information. In other words, it is contradictory to refer to tolerance datum as comprising anything other than tolerance information as would be suggested and well-understood from its plain meaning by the explicit use of the singular form, datum. For the sake of compact prosecution, the examiner shall consider that tolerance datum is only required to optionally reflect one type of data as datum, tolerance or semantic.
Claims 2-10 and 12-20 are dependent upon claims 1 and 11, and thus inherit the rejection of claims 1 and 11 under 35 U.S.C. 112(b).
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).
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 “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.
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 and Komminani using a similar analysis as that applied to claim 1.
In regards to Claim 2, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 2.
In regards to Claim 3, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 3.
In regards to Claim 4, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 4.
In regards to Claim 5, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 5.
In regards to Claim 6, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 6.
In regards to Claim 7, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 7.
In regards to Claim 8, the combination of Sawyer and Komminani 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 and Komminani using a similar analysis as that applied to claim 8.
In regards to Claim 10, the combination of Sawyer and Komminani 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 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 and Komminani 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 and Komminani 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 and Komminani 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 and Kimmonani 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 and Komminani using a similar analysis as that applied to claim 9.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Kettay et al. (US 20230084639) – teaches a method for extracting from 3D models necessary information to create 2D prints/drawings for engineering and manufacturing purposes
Phinney et al. (US 11132473) – teaches a method for designing parts that modifies tolerances in response to a manufacturing complexity/manufacturability
Schwartz et al. (US 20210223756) – teaches a method for determining a manufacturing quote from data extracted from 2D prints/drawings of the part to be manufactured
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN M SKRZYCKI whose telephone number is (571)272-0933. The examiner can normally be reached M-Th 7:30-3:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ken Lo can be reached at 571-272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JONATHAN MICHAEL SKRZYCKI/Examiner, Art Unit 2116
Prosecution Insights