DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claims 1-3, 6-8, 11-14, 17 and 20 are objected to because of the following informalities:
Claim 1, there is no step (d); further, step (e), “said components” and “said completed design work specification” lacks proper antecedent basis;
Claim 2, “said components” lacks proper antecedent basis;
Claim 3, “said manually drawing components” lacks proper antecedent basis;
Claim 6, “said particular component” and “said auto-mode” lacks proper antecedent basis; further, “measure the dimension where said particular component to be connected” does not make grammatical sense;
Claim 7, “said design area” lacks proper antecedent basis; further, “step (b) of receiving …” is inconsistent from claim 1 because in claim 1 step (b) is not a receiving step;
Claim 8, “said design area” lacks proper antecedent basis; further, “step (b) of receiving …” is inconsistent from claim 1 because in claim 1 step (b) is not a receiving step;
Claim 11, “said component codes”, “said connection codes” and “said connector types” lacks proper antecedent basis;
Claim 12, “recurrent neural network” is mislabeled as “(CNN)”; further, “a dataset whereby, wherein…” is grammatically confusing;
Claim 13, “a CNC control module configured to assign … to.” appears to missing words at the end of the claim;
Claim 14, “said design work interface” lacks proper antecedent basis;
Claim 17, “wherein assembly construction module” should be introduced with “a/an”; further, “said component codes”, “said connection codes” and “said connector types” lacks proper antecedent basis; and
Claim 20, “said carrier assembly” lacks proper antecedent basis.
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.
Claims 1-2, 10-13 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Abhinav et al., U.S. Patent Application Publication No. 2023/0195088 A1 (hereinafter: ‘088) in view of Miller, U.S. Patent Application Publication No. 2010/0063608 A1 (hereinafter: ‘608) (Examiner Note: the combination of ‘088+’608 is collectively referred to, hereinafter as ‘088’s combined system).
As per claim 1, ‘088 s’ combined system discloses a computer software program stored in a non-transitory memory device when executed by at least one processing units, said computer software program is operative to perform the following steps (e.g., See ‘088; [0006] – [0007], which collectively disclose the use of a non-transitory storage medium and processor execution):
(a) receiving a design work in a graphic design interface (e.g., See ‘088; [0033] and [0035], which collectively disclose receiving design/model data via a GUI enabled user terminal);
(b) if said design work is not completed, then using a recommendation system based on convolutional neural network (CNN) to complete said design work (e.g., See ‘088; [0048], [0050], [0051], [0065] and [0066], which collectively disclose that when a design is not finished, the system models it as a graph and uses, a graph convolution network to recommend the next connections, and this process is repeated until the design is complete); and
(c) using recurrent neural network (RNN) to create step-by-step assembly instructions for said completed design work so as every connection of said design work is fulfilled (e.g., See ‘088; [0027], [0049] and [0064], which collectively disclose using an RNN to generate step by step assembly instructions, until all required connections are satisfied).
Further, although ‘088 discloses system components communicating via a network with respect to CAD based component data (e.g., See ‘088; [0034]), ‘088 does not specifically disclose assigning either said components or said completed design work specification to be realized by at least one array of computerized numerical control (CNC) machining tool in an array of CNC machining tools via a network.
‘608 appears to adequately disclose these features (e.g., See ‘608; [0020] and [0031] – [0032], which collectively disclose part programs being sent over Ethernet, Internet, or wireless links, and an operator assigning a selected program to run one or more CNC machine tools, including multiple tools at the same time or one after the other).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate the teachings of ‘608 into ‘088 for the purpose of starting machining sooner by transmitting part program instructions to one or more CNC machines over a network, thereby reducing the need for manual transfers, cutting delays and improving production speed and reliability.
As per claim 2, ‘088’s combined system further discloses manually designing each of said components of said design work using a computer aided engineering (CAE) module (e.g., See ‘088; [0029] and [0033], which collectively disclose a user entering a CAD style engineering model of a product through a computer interface).
As per claim 10, ‘088’s combined system further discloses classifying said design work, using feature filters in said CNN to detect said missing components, and using an association algorithm to recommend said missing components (e.g., See ‘088; [0051], [0065] and [0066], which collectively disclose using convolution-derived features to predict or recommend the next component or connection to add).
As per claim 11, ‘088’s combined system further discloses using said component codes, said connection codes, memory spaces configured to store said components and said connector types, geometrical shapes of said components and connector types to produce said step-by-step assembly instructions for said design work (e.g., See ‘088; [0006], [0044], [0047] and [0049], which collectively disclose memory storing component or connection representations, including geometry based features, that are used by the recurrent process to output step by step assembly instructions).
As per claim 12, the rejection of claim 1, from above, and the rational of that rejection, is incorporated herein and applied to claim 12.
As per claim 13, ‘088’s combined system further discloses that the CNC module further comprises:
an auto-mode module configured to fit components into a partially complete design work (e.g., See ‘088; [0048], [0049] and [0065], collectively disclosing an incomplete design that is automatically completed in a step wise manner by adding the next component and its associated connections);
a recommendation system using deep learning algorithms configured to recommend missing components, connectors, and/or an entirety of said design work based on inputs of a user (e.g., See ‘088; [0033], [0051], [0065] and [0066], which collectively disclose using the user inputs and the convolution derived features to recommend the missing components or connections needed to complete the design);
an assembling instruction module using said deep learning algorithms to provide step-by-step assembling instructions of said design work (e.g., See ‘088; [0049] and [0051], which collectively disclose using deep learning to generate step by step assembly connection instructions); and
a CNC control module configured to assign said components of said design work to (e.g., See ‘608; [0031] and [0032], which collectively disclose assigning machining programs to specific CNC machines).
As per claim 16, ‘088’s combined system further discloses that the recommendation system further comprises a convolutional neural network (CNN) classifying said design work (e.g., See ‘088; [0051] and [0066]]), using feature filters in said CNN to detect said missing components (e.g., See ‘088; [0051], [0065] - [0066], which collectively disclose using the convolution filters and classification to detect which parts are missing), and using association algorithm to recommend said missing components (e.g., See ‘088; [0065] and [0066]).
As per claim 17, ‘088’s combined system further discloses that the assembly construction module further comprises a recurrent neural network (RNN) configured to use said component codes, said connection codes, memory spaces configured to store said components and said connector types, geometrical shapes of said components and connector types to produce said step-by-step assembly instructions for said design work (e.g., See ‘088; [0044], [0047], [0049] and [0064], which collectively disclose stored connection codes and geometrical features used by the RNN to output step by step assembly instructions).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over ‘088’s combined system, as applied to claim 2, from above, and further in view of Liu et al., U.S. Patent Application Publication No. 2002/0145213 A1 (hereinafter: ‘213) (collectively referred to hereinafter: ‘088’s combined system + ‘213).
As per claim 3, although ‘088’s combined system discloses providing component connections or face orientation information (e.g., See ‘088; [0044], [0046] and [0047]), ‘088’s combined system does not specifically disclose providing “material” and “color” parameters for each component.
‘213 discloses these missing features (e.g., See ‘213; [0026], which discloses design data to include dimensions, materials, and color patterns.”).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate the teachings of ‘213 into ‘088’s combined system for the purpose of adding richer design parameters, including material and color information, so that the system can improve component and connection determinations, and thereby reduce manufacturing mistakes and rework.
Claims 4-6 are rejected under 35 U.S.C. 103 as being unpatentable over ‘088’s combined system + ‘213, as applied to claim 3, from above, and further in view of Amadon et al., U.S. Patent Application Publication No. 2019/0042667 A1 (hereinafter: ‘667) (collectively referred to hereinafter: ‘088’s combined system + ‘213 + ‘667).
As per claim 4, although ‘088’s combined system + ‘213 discloses using labeled component nodes and labeled connection types as identification codes and connection codes that assist the recurrent model when mapping out the step-by-step assembly instructions (e.g., See ‘088; [0043], [0044], [0049] and [0064]), ‘088’s combined system + ’213 does not specifically disclose a distinct assigning step for these labels).
‘667 discloses these missing features (e.g., See ‘667; [0022] and [0023], which collectively disclose the use of connector properties that identify valid connection conditions and guide how parts are automatically positioned and assembled).
As per claim 5, although ‘088’s combined system + ‘213 discloses determining connections between components (e.g., See ‘088; [0027]), ‘088’s combined system + ‘213 does not specifically disclose calculating missing connectors that best fit a component and its linking components.
‘667 discloses these features (e.g., See ‘667; [0018], [0019] and [0024], which collectively disclose automatically selecting and fitting the correct connectors when connectors are missing based on feature matching).
As per claim 6, although ‘088’s combined system + ‘213 discloses component geometry (e.g., See ‘088; [0026]), ‘088’s combined system + ‘213 does not disclose auto-measuring a missing dimension, assigning that dimension, and inserting the component to the linking components.
‘667 discloses these features (e.g., See ‘667; [0019] and [0024], which collectively disclose automatically determining needed sizes, positioning parts with connectors and inserting parts to correctly perform assembly steps).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate the teachings of ‘667 into ‘088’s combined system + ‘213 for the purpose of automating connector selection, sizing, and part fitting, thereby speeding assembly design, reducing manual trial and error, and reducing mismatched connectors and dimensioning mistakes.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over ‘088’s combined system, as applied to claim 1, from above, and further in view of Amadon et al., U.S. Patent Application Publication No. 2019/0042667 A1 (hereinafter: ‘667) (collectively referred to hereinafter: ‘088’s combined system + ‘667).
As per claim 7, although ‘088’s combined system discloses receiving and providing component CAD models, ‘088’s combined system does not disclose importing components in a design area from a database.
‘667 discloses these features (e.g., See ‘667; [0029], [0060] and [0063] – [0065], which collectively disclose importing component CAD models from a database and inserting them into a design workspace).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate the teachings of ‘667 into ‘088s’ combined system for the purpose of speeding up design by reusing stored parts, reducing redrawing and mistakes, keeping consistent component versions, and letting designers quickly pull needed parts from shared storage.
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over ‘088’s combined system, as applied to claim 1, from above, and further in view of FEKETE et al., U.S. Patent Application Publication No. 2014/0132633 A1 (hereinafter: ‘633) (collectively referred to hereinafter: ‘088s combined system + ‘633).
As per claim 8, even though ‘088’s combined system discloses receiving component modeling information via a GUI, ‘088’s combined system does not disclose importing images of components into the design area from a social media.
‘633 discloses this feature (e.g., See ‘633; [0118], [0134] and [0135], which collectively disclose selecting furnishing images in a tray and importing 3rd party item images from social media linked content servers).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate the teachings of ‘633 into ‘088’s combined system for the purpose of letting users quickly pull real world component images from social media sources into the design workspace, thereby expanding available parts, saving time, and making designs easier to start and complete.
As per claim 9, although ‘088’s combined system discloses using convolutional networks (e.g., See ‘088; [0051] and [0066]), ‘088’s combined system does not disclose using the CNN to recognize imported component images and converting those images into design work.
‘633 discloses this feature (e.g., See ‘633; [0134] - [0135], which collectively disclose importing 3rd party item images via content servers and converting them into stored design objects for later use in the design process).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to apply ‘088’s combined system’s convolutional network recognition to the imported images of ‘633 before conversion so that the overall system can easily identity the items being converted into the design objects.
Claims 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over ‘088’s combined system, as applied to claim 13, from above, and further in view of FEKETE et al., U.S. Patent Application Publication No. 2014/0132633 A1 (hereinafter: ‘633) (collectively referred to hereinafter: ‘088s combined system + ‘633).
As per claim 14, although ‘088’s combined system discloses the use of a user interface, ‘088’s combined system does not specifically disclose an application control module configured to generate and manage said design work interface. Further, although ‘088’s combined system discloses the use of network-based communications, ‘088’s combined system does not specifically disclose managing communication between users who are connected to the computer system via the network.
‘633 discloses the missing features (e.g., See ‘633; [0037] – [0038], [0045] and [0052], which collectively disclose a platform that generates the design pages and controls how users share designs and communicate through the network).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate the teachings of ‘633 into ‘088’s combined system for the purpose of enabling collaboration and sharing, so that multiple users can cooperatively design, review changes, and coordinate faster over the networked design platform.
As per claim 15, ‘088’s combined system + ‘633 further discloses providing machine codes for each of the components (e.g., See ‘608; [0004] which discloses machine codes (G/M codes) and [0038] which discloses program editing and selecting). Additionally, the ‘088s’ combined system + ‘633 discloses a design work aid (EDA) module configured to enable said users to manually design said design work (e.g., See ‘088; [0033], disclosing a GUI for providing modeling information for components).
Claims 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over ‘088’s combined system, as applied to claims 12, 16 and 17, respectively, from above, and further in view of NGUYEN, U.S. Patent Application Publication No. 2021/0405607 A1 (hereinafter: ‘607) (collectively referred to hereinafter: ‘088s combined system + ‘607).
As per claim 18, ‘088’s combined system + ‘607 discloses that the array of Machine cutting (MC) tools comprises omni-direction Machine cutting (MC) tools (e.g., although ‘608 discloses an array of CNC machines ([0006])), ‘608 does not disclose that the tools are omni direction machine cutting tools; ‘607 discloses this feature; See ‘607; [0044]), each comprising:
a first base having a top side, a bottom side, a width, and a length having a proximate end and a distal end, wherein said length spans along a Y-axis of a 3-dimension (3D) Cartesian orthogonal coordinate system further having a X-axis and a Z-axis (e.g., See ‘607; [0043]);
a second base vertically erected in said Z-axis and on said top surface at said distal end and perpendicular to said first base (e.g., See ‘607; [0043]);
a tool head support assembly having a tool head, connected to and move a tool head in an omni direction (e.g., See ‘607; [0044]); and
a plurality of rotatable clamps configured to independently hold, release, and move a workpiece along said Y-axis and independently rotate a workpiece 360° around said Y- axis (e.g., See ‘607; [0045]).
As per claim 19, ‘088’s combined system + ‘607 further discloses that the tool head support assembly (e.g., See ‘607; [0044] and [0046]) further comprises:
(a) a first linear movement in said Z axis (e.g., See ‘607; [0047] and [0049]);
(b) a second linearly movement in said X axis (e.g., See ‘607; [0047] and [0049]);
(c) a first rotational movement in 360° around said Z axis (e.g., see ‘607; [0044] and [0050]; and
(d) a second rotational movement in 360° around said Y-axis (e.g., see ‘607; [0044] and [0050]).
As per claim 20, ‘088s combined system + ‘607 further discloses that each of said plurality of rotatable clamps (e.g., See ‘607; [0051]) further comprises:
a transport assembly configured to move linearly along said Y-axis (e.g., See ‘607; [0052]);
a rotation assembly, mechanically coupled to said carrier assembly, configured to rotate 360° around said Y-axis (e.g., See ‘607; [0059]); and
a clamping assembly, mechanically coupled to said rotation assembly, configured to clamp said workpiece from four directions (e.g., See ‘607; [0051] and [0060]).
References Considered but Not Relied Upon
The following references were considered but were not relied upon with respect to any prior art rejections:
(1) US 12,265,764 B2, which discloses an AI model that turns requirements into a multi part 3D CAD assembly and outputs the finished design;
(2) US 7,079,990 B2, which discloses that after a user creates a feature, the system auto-picks a matching library part based on design attributes and geometry;
(3) US 2016/0098494 A1, which discloses multiple users editing the same CAD model while analysis tool update and share results as changes are made;
(4) US 2019/0026956 A1, which discloses neural networks estimating depth from photos and building a 3D model of the captures scene for later editing and use;
(5) US 2021/0397142 A1, which discloses reinforcement learning helping to generate machining toolpaths from CAD models, the aim being to remove stock material efficiently without collisions occurring; and
(6) US 5,388,051 A, which discloses a host computer sending machining data to many NC machine tools using per tool processing units.
Conclusion
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/RONALD D HARTMAN JR/Primary Patent Examiner, Art Unit 2119 January 23, 2026;
/RDH/