DETAILED ACTION
This action is in response to the amendments filed on Aug. 18th, 2026. A summary of this action:
Claims 1-3, 5-7, 9-10 have been presented for examination.
Claims 1-3, 5-7, 9-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process without significantly more.
Claim(s) 1-2, 7, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Zheng, “KBE-based stamping process paths generated for automobile panels”, 2007
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Lockett, Helen L. "A knowledge based manufacturing advisor for CAD." (2005). PhD Dissertation. Cranfield University.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Vandenbrande et al., “Spatial Reasoning for the Automatic Recognition of Machinable Features in Solid Models”, 1993
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Khoshnevis et al., “An integrated process planning system using feature reasoning and space search-based optimization”, 1999
This action is Final
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 .
Response to Arguments/Amendments
Regarding the § 101 Rejection
Maintained.
With respect to prong 1 remarks, these remarks are not addressing the rejection rationale as “wherein the feature recognition technique operates on boundary representation models;” was an additional element and not considered as reciting an abstract idea. See example 47 for its recitation of “using the trained ANN” to clarify.
Furthermore, the claim is simply determining an order of manufacturing operations, such has been long done mentally, e.g. to build the Ford model T, to make the first production light bulbs, etc. These are not computational determinations at this level of generality, but rather mental steps.
With respect to prong 2, the abstract idea itself cannot provide/furnish the improvement. MPEP 2106.04(II)(A)(2): “Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.")” – and the remarks point substantially to the abstract idea itself to provide the practical application, but the abstract idea itself is not a practical application. Simply automating an abstract idea using a generic computer and commonplace software in its ordinary capacity is not a practical application. E.g. see Recentive Analytics in the Aug. 2025 memorandum, footnote 17.
And the claim recites no technological solution, the alleged technological feature is claimed akin to “using the trained ANN” in example 47, and “using a deep neural network (DNN)” in example 48 claim 1, recite in generality for what it is.
Furthermore, these remarks do not even submit anything from the specification to allege the improvement. MPEP § 2106.05(a): “That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement”
With respect to the 2B remarks, regarding BASCOM, the abstract idea itself is not considered in the WURC consideration. See BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88, 127 USPQ2d 1688, 1693-94 (Fed. Cir. 2018) in MPEP § 2106.05(a) to clarify on this point, and see Alice and Mayo as discussed in MPEP § 2106.05(I) and MPEP § 2106.05(d), for a “new abstract idea is still abstract” (Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016); MPEP § 2106.05(I)).
Regarding the § 102/103 Rejection
Maintained.
With respect to the remarks regarding Jones, regarding the turn operations, see the limitation: “wherein the manufacturing operations include at least one of sheet metal
operations, turn operations, injection moulding operations, or machining operations” - the claim only requires one of these operations.
Thus, the turn operation is not required by the claim, so long as the art teaches at least one of the other operations. Further clarification was expressly provided in the rejection and left unaddressed by any express claim amendment. See MPEP § 2111 for In re Prater, for it is improper to import limitations in the claim which have no express basis in the claim, and these remarks are requiring just such an improper importation of features into the claim that have no express requirement in the claim.
With respect to the remarks discussing Jones regarding “rule-based geometric classification…” – such a feature is not recited in the claim. Similar with later remarks on Lian Ding for what is alleged vs what is claimed, features no recited in the claim.
These remarks then further allege features in the specification which have no express basis in the claim. The name of the game is the claim. MPEP § 2103 for In re Hiniker Co., 150 F.3d 1362, 1369, 47 USPQ2d 1523, 1529 (Fed. Cir. 1998).
The remarks then go back to the turn operations, so see above. Not required by the claim.
With respect to the alleged lack of motivation, see the non-final act. at 43.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-3, 5-7, 9-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process without significantly more.
Step 1
Claim 1 is directed towards the statutory category of a process.
Claim 10 is directed towards the statutory category of an apparatus.
Claim 10 is rejected under a similar rationale as representative claim 1.
Step 2A – Prong 1
The claims recite an abstract idea of a mental process. See MPEP § 2106.04(a)(2).
The mental process recited in claim 1 is:
A method for classifying elements of a product, the method comprising: - a mental process with an intended use of a mental observation, e.g. a person mentally observing a product to classify elements of a product, such as by observing a product such as the one depicted in fig. 7, observing that this product includes elements such as a bracket # 708
identifying one or more elements of the product based on the 3D representation in the assembly file; - a mental observation performed as part of the mental process, but for the mere instructions to apply a computer as a tool to perform this step – e.g. observing a product such as the one shown in fig. 7, and identifying the bracket and other elements by observation, wherein a person would readily be able to perform this mental observation with a physical aid, e.g. by looking at a 3D being displayed on a computer screen, or a print-out on paper of such a 3D representation such as depicted in fig. 7, or by using a computer as a tool to perform this step. To clarify on the BRI, see ¶¶ 52-56 wherein the instant disclosure merely describes that the identification occurs but recites no particular steps in how the identification is performed.
determining, using a feature recognition technique, features of the one or more elements…; - a mental observation, but for the mere instructions to apply a computer as a tool to perform this step – e.g. when observing the bracket # 708 in fig. 7, a person observes that the bracket has “holes, slots, and island features” (¶ 56 of the instant disclosure) – to clarify on this example, see figures 7a-7e as discussed in ¶¶ 51-56 of the instant disclosure. With respect to the feature recognition technique, the Examiner notes ¶ 43 of the instant disclosure: “Successively, features of the one or more elements of the product may be determined using a feature recognition technique. The feature recognition technique operates on boundary representation models of products” – i.e. the instant disclosure does not detail what this technique is, only what it operates on – and a person would readily be able to use a computer as a tool or as a physical aid to perform this step, e.g. by using a computer as a physical aid by displaying a CAD/B-rep model on the display of a computer, or by using a computer as a physical aid to printout such a model, and making a visual observation of the displayed/printed version of the model, or by using a computer as a tool to perform this observation. To be clear, the Examiner considers that the “feature recognition technique” as recited in this limitation is part of the mental step of a mental observation as described above as a person is readily able to observe, and thus recognize, features such as discussed above (as the instant disclosure describes with no particularity what this is), and should it be found not to be part of the abstract idea that the recitation of “using a feature recognition technique” would be considered as mere instructions to implement this mental step by using a computer as a tool, as the claim does not recite any particular technological details on how the computer performs this step.
determining a geometric symmetry of each of the identified one or more elements;- a mental series of steps of a mental observation/evaluation/judgment, e.g. a person mentally observing “holes, slots, and island features” (¶ 56 of the instant disclosure), and evaluating/judging whether or not it is symmetrical. For example, a person, such as a carpenter, or a machinist, would readily be able to observe a hole to be drilled in a product, such as in 2D drawings of the product (or a 2D/3D representation of the product on a computer display using the computer as a tool, or a print-out from a computer), or in a photograph of a physical product, and observe if the hole is symmetrical or not; or observe a slot, and observe that it is axi-symmetrical (that is, symmetrical along an axis), etc.
To clarify, a person is readily able to mentally observe/evaluate/judge symmetry in a drawing in 2D, e.g. instant fig. 7b and 7b’ is readily observed that it has a symmetry (the left-half is symmetrical with the right half, in both 2D and 3D views).
and determining manufacturing operations for each of the identified one or more elements based on the corresponding features and the geometric symmetry determined for each of the one or more elements, wherein the manufacturing operations include at least one of sheet metal operations, turn operations, injection moulding operations, or machining operations, wherein the turn operations include an external end profile feature comprising consecutive external element features with monotonically increasing or equal diameters and an internal end profile feature comprising consecutive internal element features with monotonically equal or decreasing diameters…; and wherein the manufacturing operations are determined in a priority order with the sheet metal operation having a highest priority and the machining operation having a least priority. – a series of mental judgements/evaluations performed by the person, such as performed by an engineer when determining how to manufacture a product, such as the one depicted in fig. 7, such as with the aid of pen and paper. For example, when the engineer looks at an element such as the bracket in fig. 7e and sees that there are “holes, slots, and island features” (¶ 56), the engineer would then mentally judge, or evaluate, the element to determine how to manufacture it, such as by judging to use a drill to drill out the holes.
To clarify, the Examiner notes that this limitation is not reciting that the product is manufactured, rather this is merely just determining what manufacturing operations are to be performed to manufacture the product (but the claim does not require that these are performed).
To give a clarifying analogy, the Examiner first notes that the claims require no complexity to the product, so the product may be a simple product such as a basic metal table with four legs. An engineer would readily be able to mentally visualize, or sketch out with pen and paper, a model of such a product, and then mentally judge/evaluate the product to ascertain how to assemble it. For example, suppose that the engineer has access to an inventory of flat sheets of sheet metal, and bolts/nuts/washers, and the like (e.g. an inventory of a storeroom, or by observing what is it a storeroom).
The engineer would first judge/evaluate that they need to perform sheet metal operations such as cutting and bending the sheet metal to create the top of the table, and the legs – and that for the legs to attached to the table that the 4 sides of the table should have a lip to affix the legs to (bend the sheet metal into a box-like shape, with the bottom of the box missing so the legs can attach to the table-top), and that the legs should be bent at 90 degree angles to provide rounded corners. They would then judge, or evaluate, that there needs to be holes drilled into the table as machining operations so as to attach the legs to the table, wherein this step would be judged to be performed after bending/cutting the metal. The engineer then writes out these manufacturing instructions with pen and paper (potentially along with shop drawings to visually depict the process), and provides these to a factory or workshop who then produces the table.
With respect to using the geometric symmetry in such a mental process, to give a clarifying analogy, suppose the table used slots for the legs as the holes, wherein the slots were axi-symmetric (e.g. an oval, or oval-like shape). A person would readily be able to judge/evaluate how to manufacture such a shape, e.g. by judging to drill it out wherein while drilling the drill bit, or the work-piece, is moved so as to drill out the slot (e.g. by judging to use a CNC machine for this process to achieve the final shape). As another example, the person would readily be able to observe that the table is a square table such as in a drawing, observe the symmetry, and then mentally judge/evaluate how the sheet metal should be manufactured in a manner to achieve a square table.
With respect to the turn operations that are mentally judged/evaluated to be used, this is readily able to be mentally determined and has routinely been, e.g. glassblowers mentally judging when and how to turn a vase in a glassblowing furnace, a blacksmith mentally judging when and how to turn a sword as they hammer away at it, etc.
To further clarify on the turning operation, the glassblower analogy is apt. A glassblower blowing a glass bottle is readily able to turn the bottle to create a neck in the glass by tapering (i.e. “monotonically increasing diameters”) the neck at an angle. Or they can blow a straight tube, e.g. a test tube – a test tube would have, for a sizable portion of the tube, substantially monotonically equal diameters on its interior and exterior (i.e. it’s cylindrical and hollow).
Under the broadest reasonable interpretation, these limitations are process steps that cover mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper but for the recitation of a generic computer component. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the "Mental Process" grouping of abstract ideas. A person would readily be able to perform this process either mentally or with the assistance of pen and paper. See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility. In particular, with respect to the physical aids, see example # 45, analysis of claim 1 under step 2A prong 1, including: “Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation, the use of such physical aid does not negate the mental nature of this limitation.”; also see example # 49, analysis of claim 1, under step 2A prong 1: “Moreover, the recited mathematical calculation is simple enough that it can be practically performed in the human mind. Even if most humans would use a physical aid, like a pen and paper or a calculator, to make such calculations, the use of a physical aid would not negate the mental nature of this limitation.”.
As such, the claims recite a mental process.
Step 2A, prong 2
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Claim 10 - A system for classifying elements of a product, the system comprising: a processor; and a memory coupled to the processor, wherein the memory stores programmed instructions executable by the processor for:
identifying one or more elements of the product based on the 3D representation in the assembly file; - the recitation of this identification being based on “the 3D representation in the assembly file” is considered as mere instructions to perform this mental step by using a computer as a tool to implement the abstract idea, akin to “Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017), the steps in the claims described "the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’" 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of "collecting, displaying, and manipulating data." 850 F.3d at 1340; 121 USPQ2d at 1946. In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it". 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims "so result focused, so functional, as to effectively cover any solution to an identified problem")).” As discussed in MPEP § 2106.05(f); wherein in the present claims the claims lack any recitations (i.e. “details”) “as to how the computer performed the” identification claimed, but rather merely that these steps are performed “in the context of” a 3D representation in an assembly file, akin to Intellectual Ventures I v. Capital One Fin. Corp as discussed above
determining, using a feature recognition technique, features of the one or more elements, - as discussed above in prong 1, the use of “feature recognition technique” as recited herein, was considered as part of the abstract idea. Should it not be found to be abstract, then this recitation is merely instructions to implement the abstract idea on a generic computer, akin to the recitation of “using the trained ANN” in the July 2024 101 guidance update from the USPTO, example 47.
wherein the feature recognition technique operates on boundary representation models; - mere instructions to do it on a computer/in a computer environment. See MPEP § 2106.05(f) for Intellectual Ventures as discussed above, i.e. operating on B-rep models is akin to doing it in the “context of XML” without any particular instructions on how the feature recognition is to be performed on B-rep models.
In addition, Claim 1 does not recite the use of a computer, as such it is given its BRI for each limitation recited in claim 1 in view of MPEPE § 2111: “Claim 9 was directed to a process of analyzing data generated by mass spectrographic analysis of a gas. The process comprised selecting the data to be analyzed by subjecting the data to a mathematical manipulation. The examiner made rejections under 35 U.S.C. 101 and 35 U.S.C. 102. In the 35 U.S.C. 102 rejection, the examiner explained that the claim was anticipated by a mental process augmented by pencil and paper markings. The court agreed that the claim was not limited to using a machine to carry out the process since the claim did not explicitly set forth the machine. The court explained that "reading a claim in light of the specification, to thereby interpret limitations explicitly recited in the claim, is a quite different thing from ‘reading limitations of the specification into a claim,’ to thereby narrow the scope of the claim by implicitly adding disclosed limitations which have no express basis in the claim." The court found that applicant was advocating the latter, i.e., the impermissible importation of subject matter from the specification into the claim.”
The following limitations are generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h):
receiving a three-dimensional(3D) representation of a product in an assembly file; identifying one or more elements of the product based on the 3D representation in the assembly file – these are akin to “a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags).” As discussed in MPEP § 2106.05(h) as well as “iv. Specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, FairWarning v. Iatric Sys., 839 F.3d 1089, 1094-95, 120 USPQ2d 1293, 1295 (Fed. Cir. 2016);… x. Requiring that the abstract idea of creating a contractual relationship that guarantees performance of a transaction (a) be performed using a computer that receives and sends information over a network, or (b) be limited to guaranteeing online transactions, because these limitations simply attempted to limit the use of the abstract idea to computer environments, buySAFE Inc. v. Google, Inc., 765 F.3d 1350, 1354, 112 USPQ2d 1093, 1095-96 (Fed. Cir. 2014)”
determining, using a feature recognition technique, features of the one or more elements; - as discussed above in prong 1, the use of “feature recognition technique” as recited herein, was considered as part of the abstract idea. Should it not be found to be abstract, then this recitation is merely generally linking the abstract idea to a particular technological environment, akin to the recitation of “using the trained ANN” in the July 2024 101 guidance update from the USPTO, example 47.
wherein the feature recognition technique operates on boundary representation models; - generally linking to a particular technological environment/field of use
wherein the turn operations include an external end profile feature comprising consecutive external element features with monotonically increasing or equal diameters and an internal end profile feature comprising consecutive internal element features with monotonically equal or decreasing diameters, – should this be found not to be part of the abstract idea, then this is merely generally linking to a particular field of use with a particular product that has said profile features. To clarify, it does not cause a manipulative difference in the order of the manufacturing operations to be determined, but rather simply describes an end result of the geometry resultant from turn operations, i.e. generally linking it to a product with a certain geometry, but otherwise generically claimed.
each formed at an end of the part using respective outer and inner turning operations toward the chuck – generally linking to a particular technological environment wherein there is a “chuck” on a machine performing the turning
The following limitations are adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g):
receiving a three-dimensional(3D) representation of a product in an assembly file; - mere data gathering
A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. See MPEP § 2106.04(d).
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
Step 2B
The claimed invention does not recite any additional elements/limitations that amount to significantly more.
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Claim 10 - A system for classifying elements of a product, the system comprising: a processor; and a memory coupled to the processor, wherein the memory stores programmed instructions executable by the processor for:
identifying one or more elements of the product based on the 3D representation in the assembly file; - the recitation of this identification being based on “the 3D representation in the assembly file” is considered as mere instructions to perform this mental step by using a computer as a tool to implement the abstract idea, akin to “Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017), the steps in the claims described "the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’" 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of "collecting, displaying, and manipulating data." 850 F.3d at 1340; 121 USPQ2d at 1946. In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it". 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims "so result focused, so functional, as to effectively cover any solution to an identified problem")).” As discussed in MPEP § 2106.05(f); wherein in the present claims the claims lack any recitations (i.e. “details”) “as to how the computer performed the” identification claimed, but rather merely that these steps are performed “in the context of” a 3D representation in an assembly file, akin to Intellectual Ventures I v. Capital One Fin. Corp as discussed above
determining, using a feature recognition technique, features of the one or more elements, - as discussed above in prong 1, the use of “feature recognition technique” as recited herein, was considered as part of the abstract idea. Should it not be found to be abstract, then this recitation is merely instructions to implement the abstract idea on a generic computer, akin to the recitation of “using the trained ANN” in the July 2024 101 guidance update from the USPTO, example 47.
wherein the feature recognition technique operates on boundary representation models; - mere instructions to do it on a computer/in a computer environment. See MPEP § 2106.05(f) for Intellectual Ventures as discussed above, i.e. operating on B-rep models is akin to doing it in the “context of XML” without any particular instructions on how the feature recognition is to be performed on B-rep models.
In addition, Claim 1 does not recite the use of a computer, as such it is given its BRI for each limitation recited in claim 1 in view of MPEPE § 2111: “Claim 9 was directed to a process of analyzing data generated by mass spectrographic analysis of a gas. The process comprised selecting the data to be analyzed by subjecting the data to a mathematical manipulation. The examiner made rejections under 35 U.S.C. 101 and 35 U.S.C. 102. In the 35 U.S.C. 102 rejection, the examiner explained that the claim was anticipated by a mental process augmented by pencil and paper markings. The court agreed that the claim was not limited to using a machine to carry out the process since the claim did not explicitly set forth the machine. The court explained that "reading a claim in light of the specification, to thereby interpret limitations explicitly recited in the claim, is a quite different thing from ‘reading limitations of the specification into a claim,’ to thereby narrow the scope of the claim by implicitly adding disclosed limitations which have no express basis in the claim." The court found that applicant was advocating the latter, i.e., the impermissible importation of subject matter from the specification into the claim.”
The following limitations are generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h):
receiving a three-dimensional(3D) representation of a product in an assembly file; identifying one or more elements of the product based on the 3D representation in the assembly file – these are akin to “a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags).” As discussed in MPEP § 2106.05(h) as well as “iv. Specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, FairWarning v. Iatric Sys., 839 F.3d 1089, 1094-95, 120 USPQ2d 1293, 1295 (Fed. Cir. 2016);… x. Requiring that the abstract idea of creating a contractual relationship that guarantees performance of a transaction (a) be performed using a computer that receives and sends information over a network, or (b) be limited to guaranteeing online transactions, because these limitations simply attempted to limit the use of the abstract idea to computer environments, buySAFE Inc. v. Google, Inc., 765 F.3d 1350, 1354, 112 USPQ2d 1093, 1095-96 (Fed. Cir. 2014)”
determining, using a feature recognition technique, features of the one or more elements; - as discussed above in prong 1, the use of “feature recognition technique” as recited herein, was considered as part of the abstract idea. Should it not be found to be abstract, then this recitation is merely generally linking the abstract idea to a particular technological environment, akin to the recitation of “using the trained ANN” in the July 2024 101 guidance update from the USPTO, example 47.
wherein the feature recognition technique operates on boundary representation models; - generally linking to a particular technological environment/field of use
wherein the turn operations include an external end profile feature comprising consecutive external element features with monotonically increasing or equal diameters and an internal end profile feature comprising consecutive internal element features with monotonically equal or decreasing diameters, – should this be found not to be part of the abstract idea, then this is merely generally linking to a particular field of use with a particular product that has said profile features. To clarify, it does not cause a manipulative difference in the order of the manufacturing operations to be determined, but rather simply describes an end result of the geometry resultant from turn operations, i.e. generally linking it to a product with a certain geometry, but otherwise generically claimed.
each formed at an end of the part using respective outer and inner turning operations toward the chuck – generally linking to a particular technological environment wherein there is a “chuck” on a machine performing the turning
The following limitations are adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g):
receiving a three-dimensional(3D) representation of a product in an assembly file; - mere data gathering
In addition, the above insignificant extra-solution activities are also considered as well-understood, routine, and conventional activities, as discussed in MPEP § 2106.05(d):
receiving a three-dimensional(3D) representation of a product in an assembly file; - this is considered similar to the example WURC activity as discussed in MPEP § 2106.05(d)(II) of: “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;”
receiving a three-dimensional(3D) representation of a product in an assembly file; identifying one or more elements of the product based on the 3D representation in the assembly file; determining, using a feature recognition technique, features of the one or more elements, wherein the feature recognition technique operates on boundary representation models; - these are considered WURC in view of:
The instant disclosure, ¶ 44, given the generic nature of the feature recognition technique in ¶ 44 and the generic description of the data it operates on, indicating this is well known to POSITA; e.g. in existing modeling tools such as those described in ¶ 4
Vandenbrane et al., “Spatial Reasoning for the Automatic Recognition of Machinable Features in Solid Models”, 1993 – page 1270, col. 1, ¶ 3: “Much has been written on feature recognition for machining-see [20] for a critical discussion of the literature prior to 1989…” – and see § 1 ¶ 1: “FORM features such as holes and slots provide a convenient, high-level language for specifying mechanical parts, and facilitate automatic manufacturing planning and other downstream activities in the life cycle of mechanical products. Form features, or simply features, are informally defined in this paper as regions of an object that are meaningful for a specific activity or application…. In another landmark thesis Henderson showed that volumetric features could be extracted from solid models by searching for certain face and edge patterns in a solid’s boundary representation (BRep), and introduced accessibility considerations [7].”
Joshi, “Feature extraction and feature based design approaches in the development of design interface for process planning”, 1990 – abstract: “The quest for completely automated process planning systems has exposed the lack of techniques capable of automatically understanding the stored CAD models in a manner suitable for process planning. Most current generations of process planning systems have used the ability of humans to translate the part drawing requirements into a form suitable for computer aided process planning. Recently, research advances have been made to improve the understanding of computer stored 3-D part models. The two approaches used are feature recognition and feature based design. This paper presents a state of the art review of feature recognition techniques developed and presents feature based design as an alternative.“ – see § 3 to clarify incl.: “The current generation of CAD systems place emphasis on geometric shapes and designs are created primarily by Boolean operations on a set of primitive solids, and the notion of features does not exist explicitly. The problem of feature extraction involves recognition of the higher level features from the set of lower level entities in the geometric model. Depending on the representation scheme used (CSG or BREP) the lower level entities are primitive solids, faces, edges, vertices.”
Chang et al., “MACHINING PROCESS PLANNING OF PRISMATIC PARTS USING CASE-BASED REASONING AND PAST PROCESS KNOWLEDGE”, 2002 – see the introduction including: “A machining process plan for a part contains a sequence of cutting operations, which includes machine cutting (such as turning and drilling) and non-machine cutting (such as heat treatment). Since the process plan strongly influences the overall cost of the product, the major task of a process planner is to arrange the sequence of machining operations such that a given workpiece can be fabricated inexpensively. Typically, an experienced manufacturer generates a process plan for a new part based on his/her past working experiences or old plans…” then see the section “Feature-Based Representation” starting on page 308, including: “…The representation of a part in terms of features is called a feature model. There are two main approaches to creating a feature model: feature recognition and design by features. Use of the feature recognition approach for building feature models allows the designers to create general geometric models by using conventional CAD systems such as 2-D drafting systems and wireframe modelers. Feature models are then extracted from the geometric models utilizing a feature recognizer. Several distinguished approaches to feature recognition are briefly described below…”
Elinson et al., “Feature-based Similarity Assessment of Solid Models”, 1997, see §§ 1 and 2.1; then see § 2.1.3: “ During last several years, a number of efforts have been made to develop algorithms to examine CAD designs and extract features that correspond to manufacturing operations…”
Ip et al., “Content-Based Classification of CAD Models with Supervised Learning”, 2005, § 1, ¶¶ 1-2: “…There are two basic types of approaches for matching and retrieval of 3D CAD data: (1) feature-based techniques and (2) shape-based techniques. The feature-based techniques [7,18], going back at least as far as the late 1970s [14], extract engineering features e.g. machining features, and form features, from a solid model of a mechanical part for use in database storage, and automated GT coding. Elinson et al. [6] used feature-based reasoning for retrieval of solid models for use in variant process planning. Cicirello and Regli [5] examined how to develop graph-based data structures and create heuristic similarity measures among artifacts; this work was extended in [4] to manufacturing feature-based similarity measurements. McWherter et al. [15] have integrated these ideas with database techniques to enable indexing and clustering of CAD models based on shape and engineering properties.”
Cicirello et al., “Machining Feature-based Comparisons of Mechanical Parts”, 2001 – see the abstract, then see §§ 2-2.1 including: “…Primarily in the areas of manufacturing process planning and solid modeling, past research efforts have developed a variety of techniques for reasoning about geometric and topological information. Much research has been done in the area of automatic feature recognition from three dimensional solid models [22, 33, 24, 25, 461]…”
Cadalyst Videos, “SOLIDWORKS File Structure Explained”, YouTube Video, Jan. 23rd, 2017, URL: www(dot)youtube(dot)com/watch?v=FgMtmNPQYGk – see the 26 second time which depicts that the “Assembly” file is part of the file structure of Solidworks (a commercially available CAD software tool), then see the 1:30-3:30 timeframe which depicts the narrator of the video using a computer as a tool to navigate the assembly file, wherein this visually depicts the tree of the assembly file on the GUI around the 2-2:30 minute timeframe.
Boyd et al., US 2021/0270591, ¶ 21: “SolidWorks part file (.SLDPRT), several SolidWorks part files organized into a single assembly (.SLDASM), 3D assembly file supported by various mechanical design programs (.STP), graphics file saved in a solid modeling format based on the Initial Graphics Exchange Specification (.IGS) and/or the like”; also see ¶ 48
Carek et al., US 2005/0203718A1, ¶¶ 2-4 and 83
Blair et al., US 2006/0041840, fig. 11A, # 1110-20 to 1110-27; fig. 11B # 1110-32, see ¶¶ 186, 188, 190, 192
Usui, US 2021/0174408, ¶¶ 2-3, 21; 27
wherein the turn operations include an external end profile feature comprising consecutive external element features with monotonically increasing or equal diameters and an internal end profile feature comprising consecutive internal element features with monotonically equal or decreasing diameters, each formed at an end of the part using respective outer and inner turning operations toward the chuck - see the instant disclosure, ¶¶ 46-46, for its generically recited description of this step with no particular machine identified for use in the turning operation, but rather merely discusses the desired resulting shape, where it notes that it is “usually machined with a face down process or outer turning operation towards chuck”. For additional evidence, the Examiner notes that the turning operations to produce the desired shape (as claimed) are WURC, e.g. by the use of a lathe with either step or taper turning to have the changing diameters, or straight turning operations to produce constant diameters. See:
Madireddy, Jahnavi. "Importance of Lathe Machine in Engineering Field and its usage." Global Journal of Researches in Engineering: A Mechanical and Mechanics Engineering 14.6 (2014). Introduction: “The lathe, probably one of the earliest machine tools, is one of the most versatile and widely used machine tool, so also known as mother machine tool… Some of the common operations performed on a lathe are facing, turning, drilling, threading, knurling, and boring etc” – then see § I incl.: “The job to be machined is held and rotated in a lathe chuck; a cutting tool is advanced which is stationary against the rotating job. Since the cutting tool material is harder than the work piece, so metal is easily removed from the job.” – then see § III for a visual depiction of the common Lathe Operations , including see (a) and (b); then see § V including subsections (d) and (e): “Step Turning - Is the operation of making different diameters of desired length. The diameters and lengths are measured by means of outside caliper and steel rule respectively [i.e. steps of a staircase, see fig. 4 which shows staircase profiles]…Taper Turning… A taper may be defined as a uniform increase or decrease in diameter of a piece of work measured along its length [given the breadth of the claim limitation]. In a lathe, taper turning means to produce a conical surface by gradual reduction in diameter from a cylindrical work piece.” – and see in § III (a) which shows “Straight turning” to produce equal diameters as the tool progresses (note the arrow for the “Tool” direction) across the metal toward the chuck
As such, the claims are directed towards a mental process without significantly more.
Regarding the dependent claims
Claim 2 is considered as further limiting the mental process, and is rejected under a similar rationale as the identifying limitation recited in claim 1. For example, a person may readily mentally observe a 3D representation of the product, such as by observing a real-world 3D prototype of the product on a workbench, or by mentally visualizing a desired product to be manufactured, and during the observation observing certain elements of the product (e.g. mentally visualize a common door hinge, and observe where holes need to be drilled during manufacture for later mounting the hinge to a door frame). A person may readily use physical aids in this process, e.g. a display of a computer displaying the 3D representation to conduct the observation on, or a print-out (or a series of print-outs) from a computer, or by observing a series of 2D drawings/pictures/photos depicting various angles/viewpoints of the product, and then mentally visualizing in their own mind what that product would look like in 3D based on observing the 2D drawings, and perform a mental observation of the mental visualization so as to perform the identification
Claims 3, 5-7 are further limiting the mental process by limiting what the mental judgements/evaluations include, e.g. limiting the machining operations to include “holes, pockets, slots, and islands” (claim 6) because the product has such features (e.g. the bracket as discussed above, as shown in fig. 7e, as described in ¶ 56). Should these be found not to be abstract, then the Examiner submits that these would be generally linking to a particular field of use, as they merely provide a general listing of manufacturing operations which may be determined
Claim 9 recites an insignificant extra-solution activity akin to “a final step of storing data to a process that only recites computing the area of a space” as discussed in MPEP § 2106.05(g).
In addition, this is also considered as well-understood, routine, and conventional activities, as discussed in MPEP § 2106.05(d)(II): “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;”
The recitation of “for later execution by different units of a manufacturing plant for manufacturing the product” is considered, under the BRI, as an intended result of the storing (MPEP 2111.04(I)) as the limitation does not require the performance of the “later execution”, but rather is describing the intended result of storing the data. Should it be found that this step is required (i.e. that the claim requires the execution to be performed, rather than just being an intended result), then the later execution would be considered as both an insignificant extra-solution activity of an insignificant application akin to “i. Cutting hair after first determining the hair style, In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) (non-precedential); and ii. Printing or downloading generated menus, Ameranth, 842 F.3d at 1241-42, 120 USPQ2d at 1854-55” and as part of the mere instructions to apply the exception recited in a high degree of generality, wherein this is also considered as well-understood, routine, and conventional in view of:
Vandenbrane et al., “Spatial Reasoning for the Automatic Recognition of Machinable Features in Solid Models”, 1993 – page 1270, col. 1, ¶ 3: “Much has been written on feature recognition for machining-see [20] for a critical discussion of the literature prior to 1989…” – and see § 1 ¶ 1: “FORM features such as holes and slots provide a convenient, high-level language for specifying mechanical parts, and facilitate automatic manufacturing planning and other downstream activities in the life cycle of mechanical products. Form features, or simply features, are informally defined in this paper as regions of an object that are meaningful for a specific activity or application.”
Joshi, “Feature extraction and feature based design approaches in the development of design interface for process planning”, 1990 – abstract: “The quest for completely automated process planning systems has exposed the lack of techniques capable of automatically understanding the stored CAD models in a manner suitable for process planning. Most current generations of process planning systems have used the ability of humans to translate the part drawing requirements into a form suitable for computer aided process planning. Recently, research advances have been made to improve the understanding of computer stored 3-D part models. The two approaches used are feature recognition and feature based design. This paper presents a state of the art review of feature recognition techniques developed and presents feature based design as an alternative.“ – see § 3 to clarify
Chang et al., “MACHINING PROCESS PLANNING OF PRISMATIC PARTS USING CASE-BASED REASONING AND PAST PROCESS KNOWLEDGE”, 2002 – see the introduction including: “A machining process plan for a part contains a sequence of cutting operations, which includes machine cutting (such as turning and drilling) and non-machine cutting (such as heat treatment). Since the process plan strongly influences the overall cost of the product, the major task of a process planner is to arrange the sequence of machining operations such that a given workpiece can be fabricated inexpensively. Typically, an experienced manufacturer generates a process plan for a new part based on his/her past working experiences or old plans…” then see the section “Feature-Based Representation” starting on page 308, including: “…The representation of a part in terms of features is called a feature model. There are two main approaches to creating a feature model: feature recognition and design by features. Use of the feature recognition approach for building feature models allows the designers to create general geometric models by using conventional CAD systems such as 2-D drafting systems and wireframe modelers. Feature models are then extracted from the geometric models utilizing a feature recognizer. Several distinguished approaches to feature recognition are briefly described below…”
Elinson et al., “Feature-based Similarity Assessment of Solid Models”, 1997, see §§ 1 and 2.1; then see § 2.1.3: “ During last several years, a number of efforts have been made to develop algorithms to examine CAD designs and extract features that correspond to manufacturing operations…”
Ip et al., “Content-Based Classification of CAD Models with Supervised Learning”, 2005, § 1, ¶¶ 1-2: “…There are two basic types of approaches for matching and retrieval of 3D CAD data: (1) feature-based techniques and (2) shape-based techniques. The feature-based techniques [7,18], going back at least as far as the late 1970s [14], extract engineering features e.g. machining features, and form features, from a solid model of a mechanical part for use in database storage, and automated GT coding. Elinson et al. [6] used feature-based reasoning for retrieval of solid models for use in variant process planning. Cicirello and Regli [5] examined how to develop graph-based data structures and create heuristic similarity measures among artifacts; this work was extended in [4] to manufacturing feature-based similarity measurements. McWherter et al. [15] have integrated these ideas with database techniques to enable indexing and clustering of CAD models based on shape and engineering properties.”
Cicirello et al., “Machining Feature-based Comparisons of Mechanical Parts”, 2001 – see the abstract, then see §§ 2-2.1 including: “…Primarily in the areas of manufacturing process planning and solid modeling, past research efforts have developed a variety of techniques for reasoning about geometric and topological information. Much research has been done in the area of automatic feature recognition from three dimensional solid models [22, 33, 24, 25, 461]…”
As such, the claims are directed towards a mental process without significantly more.
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.
Claim(s) 1-2, 7, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton
Regarding Claim 1
Jones teaches: A method for classifying elements of a product, the method comprising: receiving a three-dimensional (3D) representation of a product in an assembly file; (Jones, abstract: “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models. FR technology is used for automating the extraction of data from CAD product models and uses wire-frame geometry extracted from an IGES neutral file format… Native CAD files are converted to IGES neutral files to provide geometry data marshalling to remove variations in user modelling practice, and to provide a consistent starting point for FR operations” – to clarify, see § 1.5.1, and § 4, then see fig. 77 on page 144, as described: “The original CAD product model is converted to an IGES wire-frame model and curve group manipulation is carried out using the ICAD™ system.” Wherein fig. 77 visually shows that the 3D “CAD Product Model” was received for this process, wherein this would have been a “CAD file” (example of an assembly file, when this term is given its BRI in view of ¶ 60 of the instant disclosure: “At block 802, an assembly file including details of a product is opened in a 3D modeler tool.”)
identifying one or more elements of the product based on the 3D representation in the assembly file; determining, using a feature recognition technique, features of the one or more elements, wherein the feature recognition technique operates on boundary representation models; (Jones, as was discussed above, including the abstract: “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models. FR technology is used for automating the extraction of data from CAD product models and uses wire-frame geometry extracted from an IGES neutral file format…” and §§ 1.5.1 and 4, and page 144 with fig. 7
Then see fig. 49 on page 105, which teaches that this identifies elements of a product by “Identify Closed Planar Curve Groups” and then recognizes features by “Group Curve Geometry into features” – as described on page 105: “Planar groups of curves are rebuilt from the IGES curves, and feature recognition algorithms analyze the curve groups for patterns matching geometric shapes (features) of interest.” – see chapter 6 to clarify with visual examples such as fig. 87 as described on page 166: “When assessed with the combined FR algorithms from Chapter 4, the cleat in Figure 87 returns the following features: 1. Extrusion; 2. Sheet-metal Fold; and 3. Through Hole (x2)”
To further clarify, page 47: “A feature is collection of geometry that has engineering significance for design or manufacture. Products are comprised of multiple features, as in Figure 10… Feature recognition is a process for identifying and extracting features from a geometric CAD product model. This feature information comprises geometry and design intent in relation to the functional, manufacturing and assembly requirements of that geometry. These requirements may be seen in the type of features of a product and their relationship to one another. By automating the extraction of design features from a CAD model, feature recognition has a favourable effect on lead-time of downstream engineering processes like manufacturing planning and analysis” and then see fig. 11
To clarify on the B-rep Jones, page 184 “The IGES neutral CAD format was used to create a wire-frame model from an arbitrary native CAD model of a product. The neutral format eliminates FR related issues that include: 1. Variations in model type (wire-frame, surface or solid); 2. User modeling practice; 3. Geometry structure used by the native CAD software (CSG or B-rep modeling); and” – i.e. the feature recognition method of Jones is operating on B-rep models, as it is applied to a “native CAD model” which includes being a “B-rep model” [B-rep is boundary representation])
determining a geometric symmetry of each of the identified one or more elements; (Jones, as discussed above including page 105 and fig. 49, then see the section “Reducing Wire-frame CAD Model Curves to Planar Closed Groups” starting on page 108, including: “…Once features have been identified, their specific surface detail may be analysed further for manufacturing specific information… The following sequence of steps describes the process for finding closed groups of curves from the collection of curves contained in the neutral CAD file, like that shown in Figure 50. The steps reference the numerically notated curves in Figure 50. The flowchart of operations for the same process is contained in Appendix A, Figure 98.” – wherein fig. 50 visually depicts that a 2D representation of the elements was generated for the “Planar Closed Curve Groups”
then see Jones, § 4.1.2: “For these reasons, the author elected to leverage the speed and simplicity of the AAG approach, and combine this with rule-based reasoning to identify specific geometry not suited to AAG (drafts for casting type manufacturing operations, bodies of revolution, etc).” as taken in view of Jones § 8.3, starting on page 192, including: ‘When combined with thickness and transition information, feature recognition could no longer have problems with interacting features using the mid-plane approach. Symmetric removal features (like through holes) have a mid-plane boundary surface [note the word “plane”, i.e. in 2D] lying on the surface containing the body of material supporting the aperture, the produces an uncomplicated interaction. Non-symmetric removal features have a boundary mid-plane surface that should not lie on any other surface, but could be tested for interaction with the body of the product by analysing approach vectors of each component. The mid-plane FR approach is not as suitable for non-specific products as other methods like AAG, however it may prove to be a useful addition to the work presented here to deal with the problem of feature interaction and reduce computer resource requirements.” – as such, it would have been obvious to have used the “mid-plane FR approach” which would have determined geometric symmetry, wherein POSITA would have been motivated to do so because “The mid-plane FR approach is not as suitable for non-specific products as other methods like AAG, however it may prove to be a useful addition to the work presented here to deal with the problem of feature interaction and reduce computer resource requirements”
determining manufacturing operations for each of the identified one or more elements based on the corresponding features and the geometric symmetry determined for each of the one or more elements, (Jones, as was discussed above including the abstract and §§ 4.1.2 and 8.3, then see chapter 5, page 143, ¶ 1: “This chapter introduces the software, knowledge sources and a Decision Support System (DSS) that comprises the Design Advisor used to identify a manufacturing process from a product model” and the see fig. 77 on page 144 to summarize, and then see fig. 85 on page 161: “The intersection of feature case data and the list of manufacturing processes by material provides the output of a list of approaches suitable for the product. The sequence of operations is shown in Figure 85….” Wherein the caption of fig. 85 is “Selecting Manufacturing Process by Feature Type”, and page 161 ¶ 2 clarifies: “In addition to isolating manufacturing processes by their ability to form a particular feature, the feature volume and process method to create that volume is also an important attribute in selecting one process over another”
wherein the manufacturing operations include at least one of sheet metal operations, … injection moulding operations, or machining operations (Jones, chapter 5 as discussed above, then see fig. 86 and page 163: “A selection of manufacturing processes from Machining, Sheet-metal, Casting and Forging operations are separated by cases relating production number and tolerance to preferred options.”
Examiner notes that “turn operations” and “injection moulding operations” are not required by the BRI of the claim, as the claim requires “at least one” of the elements in the list, and then only further requires that the sheet metal operation has a highest priority, and the machining operation has a least priority, i.e. the claim does not require the turn or injection molding operation, so long as the art teaches at least the sheet metal and machining operations with the priority order of those two as expressed in the claim
Jones does not explicitly teach:
…turn operations….wherein the turn operations include an external end profile feature comprising consecutive external element features with monotonically increasing or equal diameters and an internal end profile feature comprising consecutive internal element features with monotonically equal or decreasing diameters, each formed at an end of the part using respective outer and inner turning operations toward the chuck; - however, this is not required under the BRI (see note above)
and wherein the manufacturing operations are determined in a priority order with the sheet metal operation having a highest priority and the machining operation having a least priority.
Jones, in view of Lian Ding, teaches: and wherein the manufacturing operations are determined in a priority order with the sheet metal operation having a highest priority and the machining operation having a least priority. (Jones, page 35, # 3: “Creating a sequence of activities to have the selected machines create the product described by the geometry of its CAD model” as clarified by the paragraph split between pages 38-39: “The purpose of CAPP is to create a sequence of instructions that will result in the geometry of the product model. To do this, shapes within the part have to be recognized as features in order to generate manufacturing instructions based on the capability of individual manufacturing processes”
also see Jones, chapter 5 as discussed above, then see fig. 86 and page 163: “A selection of manufacturing processes from Machining, Sheet-metal, Casting and Forging operations are separated by cases relating production number and tolerance to preferred options.”, see pages 99-100 in Jones for visual examples in fig. 47 and 48
As taken in view of Lian Ding, chapter 7, as summarized on page 163, including: “…This chapter determines the process sequence required to produce the component with the objective of optimizing machining cost and time, while satisfying the precedence constraints. As described in Chapter 6, process sequencing i based on the operation selection made at a previous stage….” – then see § 7.2.1 starting on page 183 including: “1) Precedence constraints •A parent feature should be processed before its child features. Parent and child features have been defined in Chapter 4.•Rough machining operations should be done before finish machining operations… Primary surfaces should be machined prior to secondary surfaces. Primary surfaces are usually defined as surfaces with high accuracy or having higher impact on the design specifications, such as a datum plane. The rest of the surfaces are regarded as secondary surfaces, e.g. a threaded hole… Planes should be machined prior to holes and slots….” - to further clarify, see page 152 last paragraph: “Here, a feature precedence list specifying the order of all features of a component is built by considering the feature relationships and design intention.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Jones on “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models…” with the teachings from Lian Ding on “a feature-based CAD/CAM integration methodology. Artificial intelligent techniques such as neural networks, heuristic algorithms, genetic algorithms and fuzzy logics are used to tackle problems” wherein this includes “Generation of a suitable process plan covering selection of machining operations, grouping of machining operations and process sequencing. A hybrid feature-based CAPP has been developed using neural network, genetic algorithm and fuzzy evaluating techniques.” (Lian Ding, abstract)
The motivation to combine would have been that Lian Ding provided: “A suitable process planning database containing six libraries. A management module has been developed with an open and flexible structure, making the CAPP system adaptive to dynamic environments…A precedence algorithm to identify feature precedence relations based on the precedence constraints. Simplification has been made by considering the design intention…A strategy for optimal process sequencing. The most important characteristic is the multi-objective fitness function designed to consider minimum manufacturing cost, shortest manufacturing time and the best satisfaction of process sequence rules, which pervious research does not consider simultaneously….The application of the analytical hierarchical process (AHP) to evaluating the satisfaction degree of process sequence rules for process sequencing. AHP not only transfers the manufacturing sequence constraint problems into a numerical solution, but also makes the evaluation more adaptive…A method to allocate the relative weights for the three main evaluating factors for process sequencing, using intelligent neural network and fuzzy technique. The method can adapt the relative weights for the evaluating factors according to various component, customer and production requirements, offering greater flexibility.” (Lian Ding, pages 253-254)
Regarding Claim 2
Jones teaches: The method as claimed in claim 1, wherein the one or more elements of the product are identified from the three-dimensional representation of the product. (Jones, see the examples in chapter 6 including fig. 87 which shows that the FR algorithms were applied to 3D models)
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Regarding Claim 7
Jones teaches: The method as claimed in claim 6, wherein the holes are one of counter-bore holes, counter-sunk holes, counter-drill holes, taper holes, and simple holes, the pockets are blind pockets or through pockets, and the slots are blind slots or through slots. (Jones, page 180 table 14 teaches that “Holes”, “pocket”, “Slot” were features for the machining operations –page 166 gives examples of “Through hole” [examples of simple holes], and § 3.2.1 discusses that a hole is “A circular entity, either straight or tapered.”
As to the pockets - Jones, page 92: “A pocket is a depression of uniform depth made completely within the boundary of a parent solid” which is a blind pocket (instant fig. 6a)
As to the slots- see Jones, fig. 38 which shows a through slot
Regarding Claim 10.
Claim 10 is rejected under a similar rationale as claim 1 above, wherein Jones teaches: A system for classifying elements of a product, the system comprising: a processor; and a memory coupled to the processor, wherein the memory stores programmed instructions executable by the processor for: (Jones, abstract: “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models. FR technology is used for automating the extraction of data from CAD product models and uses wire-frame geometry extracted from an IGES neutral file format…”)
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Zheng, “KBE-based stamping process paths generated for automobile panels”, 2007
Regarding Claim 3
Jones teaches: The method as claimed in claim 1, wherein the sheet metal operations include walls, bends, cut-outs, flanges, …. (Jones, § 3.2.5 teaches “Sheet-metal features: bends, folds” (title) wherein this is visually depicted to include a “Flange Feature” and a “Double Bend” – in addition, § 3.2.4 shows an “Extrusion Feature” which is an example of a wall, and § 3.2.3 teaches “Casting/Forging Features” wherein “Drafts are commonly used for casting and forging operations, to encourage removal of the part from a die or mould [the removal is an example of a cut-out]. They are complex to produce with good surface finish on 3 axis machining processes.”
Jones, in view of Lian Ding above does not explicitly teach: …stamps
Jones, in view of Lian Ding, and in further view of Zheng teaches …stamps (Zheng, abstract: “…Relevant appropriate operations features have been assigned to stamping features of a product based on feature-operation criteria, parameters of the stamping feature and their correlativity…” and § 3.2: “The stamping CAPP system for automobile panels based on the intelligent master model above consists of several stages such as stamping features extraction from product data, operation features reasoning from stamping features to form a process information model, process planning to get the sequence of operations and relevant tools, detail design for workpieces, simulation for detail design, and finally the process plans and 3D die-face model generation which is shown in Fig. 2.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Jones, as was modified above, on “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models…” with the teachings from Zheng on, as described in the § 3.2:“ The stamping CAPP system for automobile panels based on the intelligent master model above consists of several stages such as stamping features extraction from product data, operation features reasoning from stamping features to form a process information model, process planning to get the sequence of operations and relevant tools, detail design for workpieces, simulation for detail design, and finally the process plans and 3D die-face model generation which is shown in Fig. 2”.
The motivation to combine would have been “…Thus, knowledge based engineering (KBE) is applied to advance the stamping CAPP system for automobile panels, and even to improve the competitiveness for the automobile industry. This paper is particularly concerned with the construction involved with developing a CAPP system based on KBE” (Zheng, page 664, col. 1, ¶ 3).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Lockett, Helen L. "A knowledge based manufacturing advisor for CAD." (2005). PhD Dissertation. Cranfield University.
Regarding Claim 5
Jones, in view of Lian Ding, does not explicitly teach: The method as claimed in claim 1, wherein the injection moulding operations include ribs and boss.
Jones, in view of Lian Ding and in further view of Lockett teaches: The method as claimed in claim 1, wherein the injection moulding operations include ribs and boss. (Jones, chapter 5, page 143, ¶ 1: “This chapter introduces the software, knowledge sources and a Decision Support System (DSS) that comprises the Design Advisor used to identify a manufacturing process from a product model” and the see fig. 77 on page 144 to summarize, and then see fig. 85 on page 161: “The intersection of feature case data and the list of manufacturing processes by material provides the output of a list of approaches suitable for the product. The sequence of operations is shown in Figure 85….” Wherein the caption of fig. 85 is “Selecting Manufacturing Process by Feature Type”
As taken in view of Lockett, abstract: “This thesis presents a knowledge based manufacturing advisor for Computer Aided Design. The aim of the project has been to develop techniques that can help designers to evaluate the manufacturability of moulded parts during the design process. One of the major achievements in the research has been the development of a novel feature recognition approach to allow moulding features to be recognized from a CAD model.”, and pages 1-2 the paragraph split between the pages: “The project is focused on plastic injection moulding, and metal casting which have been selected for study because they make significant demands on the designer, and represent a group of processes from which a designer may need to”
Then see § 3.4.2 on pages 38-39: “Some common features types that are important for moulded parts are: • Ribs and buttresses – used to provide strength or stiffness to the part • Bosses – used as mounting and reinforcing points • Holes – to allow access or fastening • Wall Junctions – may affect mould filling or mould cooling behaviour””
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Jones, as was modified above, on “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models…” with the teachings from Lockett on “This thesis presents a knowledge based manufacturing advisor for Computer Aided Design. The aim of the project has been to develop techniques that can help designers to evaluate the manufacturability of moulded parts during the design process. One of the major achievements in the research has been the development of a novel feature recognition approach to allow moulding features to be recognized from a CAD model.” (Lockett, abstract)
The motivation to combine would have been “…The aim of the project has been to develop techniques that can help designers to evaluate the manufacturability of moulded parts during the design process…Existing feature recognition techniques are not appropriate for moulded parts and a new feature recognition approach has been developed that uses a mid-surface abstraction from the CAD solid model as the basis for feature recognition.” (Lockett, abstract)
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Vandenbrande et al., “Spatial Reasoning for the Automatic Recognition of Machinable Features in Solid Models”, 1993
Regarding Claim 6
Jones, in view of Lian Ding teaches: The method as claimed in claim 1, wherein the machining operations include holes, pockets, slots, … (Jones, page 180 table 14 teaches that “Holes”, “pocket”, “Slot” were features for the machining operations)
Jones, in view of Lian Ding does not explicitly teach: …and islands.
Jones, in view of Lian Ding and in further view of Vandenbrande teaches: …and islands. (Jones, page 180 as was discussed above, in view of Vandenbrande, abstract: “The generation of correct and efficient plans for machining mechanical components requires the identification of features such as holes, slots and pockets, which are associated with distinctive manufacturing processes…” then see page 1276, col. 1, ¶ 1: “A pocket may have “islands”, and must be semi infinitely accessible along the sweep direction”; page 1280, col. 2, ¶ 4: “In Fig. 20, the connected component of the volume that has a face coincident with the original hint is retained. Enlarging the pocket floor has several advantages. It connects it with other segments that may have been separated by depressions in the part, as shown in this example. Reconnecting the two portions of the pocket allows them to be machined in the same machining operation. It is also beneficial for detecting protrusions, even if the protrusion sticks out from depressions within the pocket floor. Our example shows a protrusion which is considered an island, surrounded by an optional region, similar to a moat. Feature finders that are purely based on edge/face adjacency relationships (e.g., [9]) typically have problems with such situations, especially if a protrusion sticks out from multiply embedded depressions.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Jones, as was modified above, on “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models…” with the teachings from Vandenbrande on “The generation of correct and efficient plans for machining mechanical components requires the identification of features such as holes, slots and pockets, which are associated with distinctive manufacturing processes” (Vandenbrande, abstract)
The motivation to combine would have been “…It is also beneficial for detecting protrusions, even if the protrusion sticks out from depressions within the pocket floor. Our example shows a protrusion which is considered an island, surrounded by an optional region, similar to a moat (Vandenbrande, page 1280 as cited above); for an additional motivation to combine see the paragraph and bulleted list between pages 1270 to 1271, including: “…The research reported here is motivated by these deficiencies, and is a significant step towards overcoming them”
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jones, “Automated feature recognition system for supporting engineering activities downstream of conceptual design.”, 2007, PhD Dissertation, UNSW, in view of Lian Ding, “Feature technology and its applications in computer integrated manufacturing”, 2003, PhD Dissertation, University of Luton and in further view of Khoshnevis et al., “An integrated process planning system using feature reasoning and space search-based optimization”, 1999
Regarding Claim 9
Jones, in view of Lian Ding, does not explicitly teach: The method as claimed in claim 1, wherein details of the features are stored for later execution by different units of a manufacturing plant for manufacturing the product.
Jones, in view of Lian Ding and in further view of Khoshnevis teaches: The method as claimed in claim 1, wherein details of the features are stored for later execution by different units of a manufacturing plant for manufacturing the product. (Jones, § 3.3.2: “The XML data format is discussed in Section 4.1.12 and has been used to transfer feature information between FR and manufacturing applications.”
As taken in view of Khoshnevis, abstract: “In this paper we describe the architecture of a new integrated process planning system, called 31-PP, which is comprised of three modules: feature completion, process selection, and process sequencing. We have applied a knowledge-based approach to feature completion and process selection, and the space search algorithm for process sequencing. The resulting process planning system provides for both upstream and downstream integration of CAPP with CAD and scheduling systems, respectively” then see page 602, col. 2 ¶ 2: “An existence of an intermediate feature is the most natural way of storing all necessary data for further processing (e.g., NC programming) for intermediate process. Separation of multiple processes for the considered feature allows a more flexible way later in the process sequencing. The only limitation imposed in this phase is the requirement that the intermediate feature is to be machined before the final one. All other considerations are left for process sequencing.”
Then see § 3.5 ¶ 2: “On the downstream side the process planner is connected to four modules: fixture planner, tool path generator, NC code verifier, and scheduler. Process activities for a single machine (i.e., operations) are passed to a fixture planner that designs fixtures to hold the part during these operations. As a result of fixture design there may be a need to modify the process plan or to select a different alternative. The tool path generator uses the operation and fixture data to create tool paths for each tool used in an operation. It performs additional collision checks to verify if the process plan is implementable. Next, in the NC code verification module, all of the previous information pieces are combined together and the machining operation is simulated with an animated 3D picture of the process (we use a commercial software for this purpose). This module serves as a final quality verification of the created process plan”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Jones, as was modified above, on “…A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models…” with the teachings from Khoshnevis on “In this paper we describe the architecture of a new integrated process planning system, called 31-PP, which is comprised of three modules: feature completion, process selection, and process sequencing. We have applied a knowledge-based approach to feature completion and process selection, and the space search algorithm for process sequencing. The resulting process planning system provides for both upstream and downstream integration of CAPP with CAD and scheduling systems, respectively” (Khoshnevis, abstract)
The motivation to combine would have been “…In this section the specific procedures that are used to solve the problems of process selection, process sequencing, and knowledge representation are described.)…” (Khoshnevis, § 2; see § 1 for a description of the particular problems being addressed); for an additional motivation to combine see § 6 including: “The system described in this paper demonstrates a feasible and attractive approach for design and implementation of a process planning system that can be integrated with design, manufacturing, resource management, and several other related modules within a computer integrated manufacturing system. The selected configuration and the choices of algorithms and procedures have provided for acceptable system response times that make the system suitable in real-time applications such as concurrent engineering and dynamic scheduling…
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Phinney et al., US 2019/0065629. Abstract, and cf. 3 along with accompanying description.
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/David A Hopkins/Primary Examiner, Art Unit 2188
