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 .
Response to Arguments
2. The Amendment filed on February 13, 2026 has been entered. The examiner acknowledges the amendments to claims 1, 11, 17.
Rejections under 35 U.S.C. § 101: Applicant argues the manufacturing process using the lowest cost manufacturing plan is beyond an abstract idea. The Examiner disagrees noting that the method developed is software and it is implemented on a processor. The plan resulting from simulation is output to the production device. The simulated process never exercised control, but developed functional steps to achieve what is stated in requirements that instantiate the plan. An additional argument states that control is not the legal standard for patentability. The Examiner agrees, noting that in the earlier discussion, the idea of “control” was to illustrate the integration of an additional element or another machine with the invention, and performing an advanced function, a normally reliable indicator of a practical application. In the absence of such integration, the action of the processor running the simulation and providing the manufacturing plan to the 3D printer becomes “extra-solution activity, ” because the printer performs a well-understood, routine and conventional activity in the field. The linking of the judicial exception (development of the plan) to the particular technological environment, (the 3D printer), does not constitute a practical application, (MPEP 2106.04(d) and (h)), which is the standard for the determination of eligibility for a judicial exception implemented on a processor.
Amendments to the claims do not disclose any additional integration of the judicial exception to the technical environment or improvement to the operation of the computer and technical environment and thus the rejections under 35 USC § 101 will not be withdrawn.
Rejections under 35 U.S.C. § 103: Applicant’s amendments added additional hardware (additional elements) to the independent claims and assert a lowest cost manufacturing plan for manufacturing the object using the hybrid manufacturing process. The amendments do not overcome the listed prior art and arguments to the contrary were not compelling. The rejections under 35 U.S.C. § 103 will not be withdrawn.
Claim Rejections – 35 U.S.C. § 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 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter. The claims, 1-20 are directed to a judicial exception (i.e., law of nature, natural phenomenon, abstract idea) without providing significantly more.
Step 1
Step 1 of the subject matter eligibility analysis per MPEP § 2106.03, required the claims to be a process, machine, manufacture or a composition of matter. Claims 1-20 are directed to a process (method), machine (system), and product/article of manufacture, which are statutory categories of invention.
Step 2A
Claims 1-20 are directed to abstract ideas, as explained below.
Prong one of the Step 2A analysis requires identifying the specific limitation(s) in the claim under examination that the examiner believes recites an abstract idea, and determining whether the identified limitation(s) falls within at least one of the groupings of abstract ideas of mathematical concepts, mental processes, and certain methods of organizing human activity.
Step 2A-Prong 1
The claims recite the following limitations that are directed to abstract ideas, which can be summarized as being directed to a method, the abstract idea, of determining how to develop a hybrid manufacturing plan.
Claim 1 discloses a method, comprising: A method of hybrid manufacturing (HM) the method comprising:
obtaining, an initial object definition describing an initial state of a manufacturing plan; (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgment, opinion);
obtaining, and object model describing a target shape of an object to be formed through the manufacturing plan, (following rules or instructions, observation, evaluation, judgment, opinion);
generating, a tree comprising a plurality of nodes and edges, wherein each edge represents a selected manufacturing operation, wherein each node represents a shape of the object resulting from the selected manufacturing operation of a corresponding edge,
and wherein the plurality of nodes comprises a parent node representing the initial object definition, intermediate child nodes representing an intermediate state of the object, and leaf nodes representing the target shape, and wherein the selected manufacturing operation applied at each edge is selected from a plurality of manufacturing operations, including a subtractive manufacturing (SM) operation and an additive manufacturing (AM) operation; (economic principles and practices, calculating costs, following rules or instructions, observation, evaluation, judgment, opinion);
identifying, a lowest cost manufacturing plan comprising a sequence of manufacturing operations of corresponding edges connecting the parent node and one of the leaf nodes; (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgment, opinion, fundamental economic principles), and
using the lowest cost manufacturing plan.
Additional limitations employ the method using a sequence of alternating AM operations and SM operations. (following rules or instructions, observation, evaluation, judgement, opinion- claim 2), applying aggressive or conservative SM/AM operations, (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 3), where an aggressive AM operation deposits material in all parts of the shape plus supporting material (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 4), and the conservative AM operation deposits material where no additional support is required, (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 5), and the aggressive subtraction SM operation includes removing all material outside the shape even if material inside the shape is removed (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 6), and conservative subtraction AM includes removing material outside the shape that can be accessed without removing material inside the shape, (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 7), where computing an estimated cost at a node and determining whether to compute additional child nodes for that node based on the estimated cost and generating additional child nodes until a leaf node has a cost estimate below a threshold, (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 8), where a node represents a partially completed object, the cost includes AM cost of material to be added, SM cost of removing material, and adding AM and SM costs, (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 9), and generating printing instructions for a node and printing a portion of the object (economic principles and practices calculating costs, following rules or instructions, observation, evaluation, judgement, opinion- claim 10).
Each of these claimed limitations employ mental processes involving judgement, observation, evaluation and opinion as well as fundamental economic principles.
Claims 11-20 recite similar abstract ideas as those identified with respect to claims 1-10.
Thus, the concepts set forth in claims 1-20 recite abstract ideas.
Step 2A-Prong 2
As per MPEP § 2106.04, while the claims 1-20 recite additional limitations which are hardware or software elements such as a system including a data storage, a client device, a processing device, a three-dimensional (3D) printer, a computer-aided design (CAD) model, a design model or a point cloud model; and a processing device, these limitations are not sufficient to qualify as a practical application being recited in the claims along with the abstract ideas since these elements are invoked as tools to apply the instructions of the abstract ideas in a specific technological environment. The mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do not integrate an abstract idea into a practical application (MPEP § 2106.05 (f) & (h)).
Evaluated individually, the additional elements do not integrate the identified abstract ideas into a practical application. Evaluating the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
The claims do not amount to a “practical application” of the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, claims 1-20 are directed to abstract ideas.
Step 2B
Claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination, do not amount to significantly more than the abstract idea. Claim 1 additionally discloses manufacturing, at the 3D printer, a three-dimensional (3D) object of the target shape by the HM. This is extra-solution activity to the claim and is well-understood, routine, and conventional in the art. The specification states, “Once the user has a suitable HM process plan 106, the user may begin manufacturing the 3D object accordingly. For those steps involving AM manufacturing, the material addition for that stage of the process may be converted into printing instructions 126 and sent to a 3D printer 128 for printing,” [0035].
The analysis above describes how the claims recite the additional elements beyond those identified above as being directed to an abstract idea, as well as why identified judicial exception(s) are not integrated into a practical application. These findings are hereby incorporated into the analysis of the additional elements when considered both individually and in combination.
For the reasons provided in the analysis in Step 2A, Prong 1, evaluated individually, the additional elements do not amount to significantly more than a judicial exception. Thus, taken alone, the additional elements do not amount to significantly more than a judicial exception.
Evaluating the claim limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. In addition to the factors discussed regarding Step 2A, prong two, there is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely amount to instructions to implement the identified abstract ideas on a computer.
Therefore, since there are no limitations in the claims 1-20 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, the claims are directed to non-statutory subject matter and are rejected under 35 U.S.C. § 101.
Claim Rejections 35 U.S.C. §103
The following is a quotation of 35 U.S.C. § 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 8-20, are rejected under 35 U.S.C. § 103 as being taught by Reinhard,
(EP 3696709 A1), hereafter Reinhard, “Expert Knowledge Framework Driven Hybrid Manufacturing Systems and Methods,” in view of Coffman (US 11698623 B2), hereafter Coffman, “Methods and Apparatus for Machine Learning Prediction of Manufacture Processes.”
Regarding Claim 1, Claim 1 discloses a method, Reinhard teaches A method of hybrid manufacturing (HM) in a system [Abstract] and a three-dimensional (3D) printer, the method comprising: (hybrid manufacturing and planning and corresponding systems (700) and computer-readable mediums, [Abstract], storage 726 can store any data, instructions, or code useful or necessary for performing processes, [0056], the update rules can be received by the system such as by being received from a user, loaded from a database, received from another device or process, or otherwise, [0031], and in FIG.7, I/O adapter722 can be connected to communicate with or control manufacturing hardware 728, which can include additive-manufacturing equipment such as 3D printing devices, sensors, imagers, systems, and other AM tools, materials, and machines, and can include subtractive manufacturing equipment, [0057]),
obtaining, at the data storage, an initial object definition describing an initial state of a
manufacturing plan; (CAD model 102 and primitive decomposition 104 can be stored in and instantiated against a machining ontology 112 which exists in a persistent database 114, [0018], and Figure 2 illustrates an example of a workpiece state as graph-based workpiece representation 200 in accordance with disclosed embodiments. This figure represents a desired workpiece final state for a given workpiece geometry, [0026]),
obtaining, at the client device, an object model describing a target shape of an object to be formed through the manufacturing plan, wherein the object model comprises at least one of a computer-aided design (CAD) model or a point cloud model; (The system receives a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process (602). "Receiving," as used herein, can include receiving via an interaction with a user, loading from storage, receiving from another device or process, or otherwise, [0046], receiving, by a data processing system, a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process, Reinhard, [0003]); and the modelled workpiece can include geometric primitives which can be combined to form the whole part, their topological relationships, and descriptive attributes for each component primitive, [0012], and (receiving (602), by the data processing system(700), a computer-aided-design (CAD) model (750), [Abstract]),
generating, by the processing device, a tree comprising a plurality of nodes and edges,
wherein each edge represents a selected manufacturing operation, wherein each node represents a shape of the object resulting from the selected manufacturing operation of a corresponding edge, and wherein the plurality of nodes comprises a parent node representing the initial object definition, intermediate child nodes representing an intermediate state of the object, and leaf nodes representing the target shape, and wherein the selected manufacturing operation applied at each edge is selected from a plurality of manufacturing operations, including a subtractive manufacturing (SM) operation and an additive manufacturing (AM) operation; (Operations 116, that describe how each available tool acts on each geometric primitive in order to manufacture the workpiece 130, are fed into a reasoning engine 118. Reasoning engine 118 evaluates geometric relationships between proposed or possible operations to produce a partitioned solutions tree 122, [0021], and FIG. 1), the virtual workpiece is stored as a graph-based representation including a plurality of nodes and edges, each node representing a surface. In some embodiments, the operations define how each virtual tool can act on the virtual workpiece, [0004] and an "operation," in this context, defines a transformation of the workpiece from one state to another, [0020], the system instantiates a virtual workpiece (604). The virtual workpiece corresponds to a physical workpiece from which the part to be manufactured can be physically manufactured. The virtual workpiece can be stored as a graph-based representation including a plurality of nodes and edges as described herein, [0047], an attributed adjacency graph (AAG) gives a topological description of geometric primitives. Each of these geometric primitives is stored as a node in a graph, and attributes describing those primitives are attached to the nodes. The AAG approach encodes the most relevant geometrical information in a way that it can be queried and understood by purely graph-based reasoning, [0025], (Figure 2 illustrates an example of a workpiece state as graph-based workpiece representation 200 in accordance with disclosed embodiments. This figure represents a desired workpiece final state for a given workpiece geometry, Reinhard, [0026], in some embodiments, the operations include both additive-manufacturing operations and subtractive-manufacturing operations, [0004]),
identifying, as the manufacturing plan by the processing device, a lowest cost
manufacturing plan comprising a sequence of manufacturing operations of corresponding edges; and
manufacturing, at the 3D printer, a three-dimensional (3D) object of the target shape by the HM using the lowest cost manufacturing plan, (The system identifies possible manufacturing solutions according to the search (612), [0051], disclosed embodiments include systems and methods for automated computer-aided process planning (CAPP) for hybrid manufacturing that can identify non-trivial, qualitatively distinct, and cost-optimal combinations of additive manufacturing/subtractive manufacturing techniques to produce a physical product from a workpiece, where the workpiece can be modified using additive-manufacturing operations in some portions and performing subtractive manufacturing operations on some portions, [0014], The system receives a computer-aided-design
(CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process (602). "Receiving," as used herein, can include receiving via an interaction with a user, loading from storage, receiving from another device or process, or otherwise, [0046], a virtual workpiece (604). The virtual workpiece corresponds to a physical
workpiece from which the part to be manufactured can 55 be physically manufactured. The virtual workpiece can be stored as a graph-based representation including a plurality of nodes and edges as described herein, [0047], Reinhard does not teach connecting the parent and one of the leaf nodes, embodiments also include physically manufacturing the part from a physical workpiece according to the selected manufacturing plan; [0004], which can include additive-manufacturing equipment such as 3D printing devices, [0057], disclosed embodiments include systems and methods for automated computer-aided process planning (CAPP) for hybrid manufacturing that can identify non-trivial, qualitatively distinct, and cost-optimal combinations of additive manufacturing/subtractive manufacturing techniques to produce a physical product from a workpiece, where the workpiece can be modified using additive-manufacturing operations in some portions and performing subtractive manufacturing operations on some portions, Reinhard, [0014].
Coffman teaches connecting the parent node and one of the leaf nodes, (a collection of tree structures as the one shown in FIG. 8 are executed [20: 36-37], and assume a number of decision trees to grow is t, then for each decision tree (at 901) select a training data subset n as shown at 903 from the training set TS (e.g., bagged subset of samples or bootstrap sample). The conditional statement at 905 determines whether a stop condition holds at each node of a growing decision tree. The stopping condition depends on the selected training data subset n. Some examples of the condition evaluated at 905 include the number of training samples at the node, if a maximum depth is reached or other suitable conditions, [21: 15-24], if such a condition is satisfied, the current node becomes a leaf node and a prediction error for the decision tree is calculated at 907, [21:25-27]),
Before the earliest effective filing date of this application, it would have been obvious to one of ordinary skill in the art to have modified Reinhard with the teachings of Coffman in the field of hybrid manufacturing with the motivation to ensure completed additive and subtractive operations getting from the connecting parent nodes and leaf nodes, signifying transforming the design into the next intermediate shape.
It would have been obvious to one of ordinary skill in the art before the earliest filing date of this application to include the features taught by Coffman in the method of Reinhard since the claimed invention is a combination of known technologies and the combination of each element would have performed its original function and would have predictable results in delivering the required intermediate (or final) shape. (When a maximum depth is reached or other suitable condition is satisfied, the current node becomes a leaf node and a prediction error for the decision tree is calculated at 907, [21:23-27]).
Regarding claim 2, The method of claim 1, wherein the lowest cost manufacturing plan comprises a sequence of alternating AM operations and SM operations, Reinhard teaches, (disclosed embodiments include systems and methods for automated computer-aided process planning (CAPP) for hybrid manufacturing that can identify non-trivial, qualitatively distinct, and cost-optimal combinations of additive manufacturing/subtractive manufacturing techniques to produce a physical product from a workpiece, where the workpiece can be modified using additive-manufacturing operations in some portions and performing subtractive manufacturing operations on some portions, [0014]).
Regarding claim 3, the method of claim 1, wherein the plurality of manufacturing operations comprises an aggressive addition AM operation, a conservative addition AM operation, an aggressive subtraction SM operation, and a conservative subtraction SM operation, Reinhard teaches, (some embodiments also include physically manufacturing the part from a physical workpiece according to the selected manufacturing plan. In some embodiments, the virtual workpiece is stored as a graph-based representation including a plurality of nodes and edges, each node representing a surface. In some embodiments, the operations define how each virtual tool can act on the virtual workpiece. In some embodiments, the operations include both additive-manufacturing operations and subtractive-manufacturing operations. In some embodiments, each operation includes a region, a modifier, and a tool. In some embodiments, the data processing system performs hierarchical abstraction to partition the search into a plurality of domains. In some embodiments, the data processing system applies update rules or transformations to modify a state of the virtual workpiece. In some embodiments, the search is performed using an A* algorithm, [0004]. The declaration of addition and subtraction operations as “aggressive” or “conservative” would be a design choice with no benefit to the utility of the invention, as aggressive addition as defined in the specification as deposit[Ing] material in the target shape plus supporting material needed to support the deposited material, while conservative addition would not require support material. Similarly, aggressive subtraction removes all extra material outside of the target shape, while conservative subtraction removes material outside of the target shape only if it can be accessed without removing material inside of the target shape. It is a design choice to label the addition and subtraction processes in these ways and it would be obvious for one of ordinary skill in the art to rearrange parts of the invention, in this case adding or removing material as needed based on the design in order to reach the final design shape, (MPEP 2144.04 I, 2144.04 VI (C)).
Regarding Claim 8, The method of claim 1, comprising computing an estimated cost at a specific node, Reinhard teaches, (the workpiece state represents the state of a virtual workpiece during the manufacture planning processes described herein, which will eventually correspond to the state(s) of the physical workpiece 130 during physical manufacturing operations. The system modifies the workpiece state by applying operations, which are defined by entries comprising region, modifier, and tool.
The region entry defines the node upon which the modifier operates, which the tool physically interacts with during the manufacturing operation. For 3D operations, this can mean removing or adding material in that region, but the region is also relevant to 2D operations because the tool must passthrough the enclosed space in order to act on adjacent faces.
The modifier entry defines a generic description of how to update the dynamic properties associated with that region. For instance, the modifier of an operation may specify that material should be removed in the specified region for subtractive operations such as milling.
The tool entry defines or contains links to descriptive information such as constraints to the size or shape of a region or the nominal cost of using the tool (e.g., time per unit volume), [0034-0037]) of the plurality of nodes and determining whether to compute additional child nodes for that specific node based on the estimated cost, Reinhard does not teach, Coffman teaches, (the axioms generated by the machine learning models 501 can be specific to one or more of an additive manufacturing machine, subtractive manufacturing machine, casting manufacturing machine, injection molding manufacturing machine, hybrid manufacturing machine and other suitable fabrication technologies, [15:65 - 16:3], and knowledge aggregator/reasoning engine 509 receives as input one or more axioms generated by predictive machine learning models 501, and generates predictions associated with the manufacture of a physical object. In some instances, predictions can be based on the axioms generated by two or more machine learning models by combining the axioms using an average function, median, or other suitable type of descriptive statistical function. In other instances, axioms generated by different learning models can be evaluated through a function, such that an axiom or a set of axioms showing lower error levels and/or highest confidence values are selected from a set of candidate axioms. In other further instances, one or more axioms generated by machine learning models 501 can serve as input to a reasoning engine. Rules in the reasoning engine can be expressed in data structures denoting symbolic logic propositions, terms, and/or relations to support the reasoning of predictive engine 217. In yet some further instances, predictions can be generated through sets of linear and non-linear functions. For example, a predicted cost associated with the manufacture of a physical object can be calculated by engine 509 as a function of axioms indicating a number of CNC operations used to manufacture an object, setup time, and cycle time multiplied by machine rate (including fixed costs, operating costs and/or labor costs) and further multiplied by a quantity of objects requested to be manufactured, [16:14-39] and FIGs. 5, 8, and 9).
Reinhard and Coffman are both considered to be analogous to the claimed invention because they are both in the field of hybrid design for manufacturing. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine cost calculation of Reinhard with the cost optimization by machine learning axion of Coffman to produce reliable objective manufacture appraisal and prediction tools capable to operate in near real-time can significantly contribute to the overhead of manufacture of products, [Coffman 1:53-55].
Regarding claim 9, The method of claim 8, wherein the specific node represents a partially completed object, wherein computing the estimated cost comprises:
computing an estimated AM cost of the material to be added to portions of the target shape that are unfilled;
computing an estimated SM cost of removing portions outside the target shape that have material deposited; and
adding the estimated AM cost the estimated SM cost, Reinhard teaches, (systems and methods for automated computer-aided process planning (CAPP) for hybrid manufacturing that can identify non-trivial, qualitatively distinct, and cost optimal combinations of additive manufacturing/subtractive manufacturing techniques to produce a physical product from a workpiece, where the workpiece can be modified using additive-manufacturing operations in some portions and performing subtractive manufacturing operations on some portions. Disclosed embodiment can employ a graph-based representation and update rules. Manufacturing operations are encoded as graph transformations which modify the workpiece state. A complete manufacturing plan can be obtained, for example, by using an A* search guided by supplied cost and heuristic functions.
Regarding claim 10, The method of claim 1 comprising:
generating 3D printing instructions corresponding to one of the manufacturing operations described by one of the nodes;
sending the 3D printing instructions to a 3D printer; and printing a portion of the object, Reinhard teaches, (The system can physically manufacture a physical part from a physical workpiece according to the selected manufacturing plan (616). The manufactured part can correspond to the CAD model. Figure 7 illustrates a block diagram of a data processing system 700 in which an embodiment can be implemented, [ ] The data processing system depicted includes a processor 702connected to a level two cache/bridge 704, which is connected in turn to a local system bus 706. Local system bus 706 may be, for example, a peripheral component interconnect (PCI) architecture bus.
Also connected to local system bus in the depicted example are a main memory 708 and a graphics adapter 710. The graphics adapter 710 may be connected to display 711.
Other peripherals, such as local area network (LAN) / Wide Area Network / Wireless (e.g., WiFi) adapter 712, may also be connected to local system bus 706. Expansion bus interface 714 connects local system bus 706 to input/output (I/O) bus 716. [ ] Also connected to I/O bus 716 in the example shown is [ ] I/O adapter722 can be connected to communicate with or control manufacturing hardware 728, which can include additive-manufacturing equipment such as 3D printing devices, sensors, imagers, systems, and other AM tools, materials, and machines, and can include subtractive manufacturing equipment such as mills, drills, or other SM tools, materials, and machines, and can include other devices or hardware described herein, see FIG. 7, [0061, 0064]).
Claims 11-20 are rejected for reasons corresponding to those cited for claims 1-10. In these claims, the addition of software generating a manufacturing plan, a processing device, an apparatus comprising a memory, a processing device coupled to the memory, the apparatus configured to send instructions to a 3D printer, and a non-transitory computer-readable storage medium, do not change the rationale for the rejections under 35 U.S.C. § 103 or the referenced prior art. (Reinhard teaches the data processing system depicted includes a processor 702, [0054], a main memory 708, [0054], I/O adapter722 can be connected to communicate with or control manufacturing hardware 728 [0057], which can include additive-manufacturing equipment such as 3D printing devices, [0057], a non-transitory computer-readable medium (726), [claim 11], and a manufacturing plan (762), [0004], from the possible manufacturing solutions (760), [0003] and Reinhard, FIG. 7.)
Claims 4 and 5 are rejected under 35 U.S.C. § 103 as being taught by Reinhard, (EP
3696709 A1), hereafter Reinhard, “Expert Knowledge Framework Driven Hybrid Manufacturing Systems and Methods,” in view of Coffman (US 11698623 B2), hereafter Coffman, “Methods and Apparatus for Machine Learning Prediction of Manufacture Processes,” in further view of Lin, (US 20210094102 A1), hereafter Lin, “Apparatus and Process of Additive Manufacturing.”
Regarding claim 4, the method of claim 3, wherein the aggressive addition AM operation, Reinhard teaches, (additive manufacturing systems such as 3D printing have been developed, which build the workpiece by adding material in the desired shapes, [0002]), comprises depositing material in all parts of the target shape plus any support material needed to support the deposited material, Reinhard does not teach, Lin teaches, (an apparatus for additive manufacturing and a method thereof of a part of an article from a first material comprising particles having a first composition. A second material, comprising particles having a second composition, different from the first composition, provides a support material, arrangeable to support the build material during, for example, intermediate stages of additive manufacturing. The second material may be thus used to provide a support structure during additive manufacturing of the part of the article and/or of the article. Since the first composition and the second composition are different, their respective properties may be selected according to their respective uses, thereby facilitating removal of the second material, such as the support structure, while reducing consumption of the first material, [0152]).
Reinhard and Lin are both considered to be analogous to the claimed invention because they are both in the field of hybrid design for manufacturing. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the additive manufacturability of Reinhard with the application of a second material as an external support structure approach of Lin thereby facilitating removal of the second material, such as the support structure, while reducing consumption of the first material, [0004].
Regarding claim 5, the method of claim 3, wherein the conservative addition AM operation comprises depositing material in any part of the target shape, Reinhard teaches (additive manufacturing systems such as 3D printing have been developed, which build the workpiece by adding material in the desired shapes, [0002]), that would not require support material, Reinhard does not teach, Lin teaches (support structures may be required to support, at intermediate stages of additive manufacturing, [0003]), while the required use of support materials in an AM operation would be a design choice, just as the required exclusion of support materials in an AM operation, with no benefit to the utility of the invention. It would be a design choice to determine the need for support structure in an AM operation and it would be obvious to one of ordinary skill in the art to rearrange parts of an invention, in this case deciding to use or not use support structures to ensure proper manufacturing. (MPEP 2144.04 I, 2144.04 VI (C)).
Reinhard and Lin are both considered to be analogous to the claimed invention because they are both in the field of hybrid design for manufacturing. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the additive manufacturability of Reinhard with the 'addition and subtraction rapid prototyping technology' of the present invention adopts a technical scheme of 'layered printing, same layer processing', layered printing for additive manufacturing, the same layer processing is reduced material manufacturing of Chen, so that the advantages of 3D printing technology and CNC material reduction manufacturing technology are combined, and the new technology has the advantages of rapid processing and high processing precision. 1, 1%-5% loss rate, low consumption; 2, can process the inside of the workpiece; 3, reduce tool interference by more than 90%; 4, make 3D printing additive manufacturing process can use higher layer thickness without losing its Precision, [Chen - 0009].
Claims 6 and 7 are rejected under 35 U.S.C. § 103 as being taught by Reinhard, (EP
3696709 A1), hereafter Reinhard, “Expert Knowledge Framework Driven Hybrid Manufacturing Systems and Methods,” in view of Coffman (US 11698623 B2), hereafter Coffman, “Methods and Apparatus for Machine Learning Prediction of Manufacture Processes.” in further view of Chen (WO 2017177454 A1), hereafter Chen, “Process for 3D Printing by Additive/Subtractive Method and 3D Printing System.”
Regarding claim 6, The method of claim 3, wherein the aggressive subtraction SM operation comprises removing Reinhard teaches (traditionally, machine manufacturing systems have concentrated on subtractive manufacturing, where a "blank" or other workpiece is machined to remove portions, such as by milling, drilling, etc., to shape the workpiece, [0002]), all material outside of the target shape even if material inside of the target shape is removed. Reinhard does not teach, Chen teaches, (the addition and subtraction process of the present invention is different from the existing manufacturing process of the prior additive manufacturing and the post-CNC reduction manufacturing. [ ] The addition and subtraction process of the invention adopts CNC five-axis mechanical material reduction processing, has little or no interference, and is easy to process the inside of the product, realizes internal and external processing of the product, and enables 3D printed products, the inside thereof, the outside maintains high precision, [0038]).
Reinhard and Chen are both considered to be analogous to the claimed invention because they are both in the field of hybrid design for manufacturing. It would have been obvious to one of ordinary skill in the art before the effective filing date to hybrid manufacturing planning techniques of Reinhard with the additive/subtractive method of Lin to accomplishes a huge leap in terms of the processing efficiency, processing precision and processing speed, and [ ] with a very high economic value, Chen Abstract].
Regarding claim 7, the method of claim 3, wherein the conservative subtraction AM operation comprises removing any material, Reinhard teaches (subtractive manufacturing, where a "blank" or other workpiece is machined to remove portions, [0002]), outside of the target shape that can be accessed without removing material inside of the target shape, Reinhard does not teach, Chen teaches, (the invention can realize the CNC material reduction processing under the hot state, and can also realize the CNC material reduction processing after cooling, and is selected according to actual needs, [ ] and the addition and subtraction process of the invention adopts CNC five-axis mechanical material reduction processing [ ], the outside maintains high precision. [0038].
Reinhard and Chen are both considered to be analogous to the claimed invention because they are both in the field of hybrid design for manufacturing. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the subtractive manufacturability of Reinhard with the additive/subtractive method of Lin to accomplishes a huge leap in terms of the processing efficiency, processing precision and processing speed, and [ ] with a very high economic value, Chen Abstract].
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as
set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to
applicant's disclosure or directed to the state of the art is listed on the enclosed PTO-892.
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to MICHAEL BOROWSKI whose telephone number is (703)756-1822. The examiner can normally be reached M-F 8-4:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O’Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at (866) 217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call (800) 786-9199 (IN USA OR CANADA) or (571) 272-1000.
/MB/
Patent Examiner, Art Unit 3624
/MEHMET YESILDAG/Primary Examiner, Art Unit 3624
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