DETAILED ACTION
1. Claims 1-20 have been presented for examination.
Notice of Pre-AIA or AIA Status
2. 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
3. Applicant's arguments filed 10/30/25 have been fully considered but they are not persuasive.
i) Following Applicants amendments the previously presented claim objection for claim 9 is WITHDRAWN.
ii) Following Applicants arguments the previously presented 101 rejection is WITHDRAWN.
iii) Following Applicants amendments the previously presented 112 rejection is WITHDRAWN.
iv) Applicants argue that the prior art Gergov does not teach “simulating including computing a part thickness distribution of the part based on the mesh model” but rather parameters are merely inputted. The Examiner notes that in view of the broadest reasonable interpretation of the claims the use of the part thickness value reads on the claim as presented in at least two ways. First, the part thickness value is part dependent which would require a determination/computation based on the type of part as recited in the cited sections of Gergov. Second, the prior art explicitly notes in at least the previously cited paragraph 21 and 54 that data parameter values are either acquired as input, real time measurements, or mathematically calculated. See citation of Gergov. “[0021] Prior systems have attempted to optimize filling time and cooling time by relying on table data that relates a given measurement to adjustments in the speed of the driving mechanism or to other adjustments. In the presently disclosed system, real data is acquired from real time measurements and additional parameters are mathematically calculated. The real time measurements and calculated parameters are used to adjust the speed of the driving mechanism on the fly.” “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part.” “[0054] The model solution domain is then defined and discretized by any of a variety of methods, such as by finite element analysis in which a finite element model is produced by generating a finite element mesh based on the solid model in step 420. The mesh consists of a plurality of contiguous solid elements defined by shared nodes.” “[0055] With the resultant finite element model or other discretized solution domain defined, a user specifies boundary conditions in step 430 for the analysis. The boundary conditions include the parameters 210 as well as the calculated parameters discussed above.” As such the prior art rejection is MAINTAINED.
v) In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). As cited in the previous office action and noted by Applicants Jiang teaches a “flow front” which in combination with the teachings of Gergov read on the argued limitations “computing velocity and temperature at a of the material over the part thickness distribution computed and determining advancement of the based on the velocity and temperature computed.” Applicants present a conclusory statement that the combination of references do not teach the argued limitations. Applicant's arguments amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Specifically no arguments have been presented to address either the combination, motivation, or the citations of Gergov. “[0056] Once the boundary conditions have been entered, the multi-physics FEA executes the instructions in accordance with the simulation model to first calculate or solve relevant filling phase process variables in step 440. As discussed above, such variables can include fluidity, mold cavity fill time, pressure, shear rate, stress, velocity, viscosity, and temperature.” “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity.”) As such the prior art rejection is MAINTAINED.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) 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.
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 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.
4. Claim(s) 1-9, and 11-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 20190105826, hereafter Gergov, in view of Jiang, Shunliang, et al. "An implicit control-volume finite element method and its time step strategies for injection molding simulation." Computers & Chemical Engineering 31.11 (2007): 1407-1418, hereafter Jiang.
Regarding Claim 1: Gergov discloses A computer-implemented method for determining behavior of an injection molding process, the method comprising:
simulating in real-time, via at least one processor, a filling stage of an injection molding process that fills a part cavity of a part with material over a filling time, the simulating based on a boundary integration method and a mesh model, the mesh model representing the part cavity, the simulating including computing a part thickness distribution of the part based on the mesh model, (Gergov. “[0021] Prior systems have attempted to optimize filling time and cooling time by relying on table data that relates a given measurement to adjustments in the speed of the driving mechanism or to other adjustments. In the presently disclosed system, real data is acquired from real time measurements and additional parameters are mathematically calculated. The real time measurements and calculated parameters are used to adjust the speed of the driving mechanism on the fly.” “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part.” “[0054] The model solution domain is then defined and discretized by any of a variety of methods, such as by finite element analysis in which a finite element model is produced by generating a finite element mesh based on the solid model in step 420. The mesh consists of a plurality of contiguous solid elements defined by shared nodes.” “[0055] With the resultant finite element model or other discretized solution domain defined, a user specifies boundary conditions in step 430 for the analysis. The boundary conditions include the parameters 210 as well as the calculated parameters discussed above.”)
the boundary integration method including computing velocity and temperature at a of the material over the part thickness distribution computed and determining advancement of the based on the velocity and temperature computed; and (Gergov. “[0056] Once the boundary conditions have been entered, the multi-physics FEA executes the instructions in accordance with the simulation model to first calculate or solve relevant filling phase process variables in step 440. As discussed above, such variables can include fluidity, mold cavity fill time, pressure, shear rate, stress, velocity, viscosity, and temperature.” “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity.”)
outputting, via the processor, at least one indication of behavior of the injection molding process determined based on the simulating, the simulating transpiring in real- time relative to the filling time. (Gergov. “[0059] Once the simulation reaches the stage in the analysis where it is determined that the mold cavity has been filled, the computer executes the instructions in accordance with the simulation model to next calculate or solve relevant packing phase process variables for the nodes in step 450. Such variables can include the mass properties of the component produced in accordance with the simulation model such as density and volumetric shrinkage, in addition to fluidity, packing time, pressure, shear rate, stress, velocity, viscosity, and temperature. [0060] During the simulation, data is recorded at each of the sensor locations. Such data recordation may be referred to as data capture by the virtual sensors in the solid model. Specifically, the pressure, volume, and temperature are recorded at the sensor locations during the simulation, so that pressure, volume, and temperature curves can be created. The pressure, volume, and temperature curves can represent the change of pressure, volume, and temperature over time or the change of pressure, volume, and temperature per unit of displacement of the injection material.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Regarding Claim 2: Gergov discloses The computer-implemented method of Claim 1, wherein the boundary integration method further includes employing a representation of a moving boundary of the and wherein the representation of the moving boundary is a one-dimensional (1D) element. (Gergov. “[0046] FIG. 3 is graph 300 illustrating changes to molding parameters over time during an injection molding process using the injection molding device 100.” Examiner Note: the molding parameters track the location of the injection over time and the line on the graph represents the 1D element as claimed, see [0051] “As can be seen in the simulation illustrated in FIG. 3, the melt pressure 340 initially spikes as the injection material passes from the large diameter portion 130 to the reduced diameter portion 140 of the gate 120.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Regarding Claim 3: Gergov discloses The computer-implemented method of Claim 1, wherein the boundary integration method further includes computing an incremental pressure drop and wherein determining the advancement includes employing the incremental pressure drop computed. (Gergov. “[0033] As the injection material passes through the main passageway 150, the arms 160, and the exit nozzles 170, the injection material experiences additional shears and changes in pressure, further affecting the flow rate of the injection material. Likewise, as the injection material experiences further shears and changes in pressure as it flows through the molds 110.” “[0049] The hydraulic injection pressure 320 then drops as the injection material begins to pass through the main passageway 150, then increases again as the injection material passes through arms 160 and the exit nozzles 170. The hydraulic injection pressure 320 then decreases as the molds 110 fill. As can be seen in this graph 300, the hydraulic injection pressure 320 dropped at different rates during different simulations, based on changes to other parameters.”)
Regarding Claim 4: Gergov discloses The computer-implemented method of Claim 1, wherein determining the advancement of the includes determining, on a time-step-by-time-step basis, advancement of a moving boundary of the of the material within the part cavity represented by the mesh model, the simulating including advancing, on the time-step-by-time step basis, the moving boundary based on the advancement determined for the moving boundary. (Gergov. “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity. Volumetric solvers require the solution of second order differential equations: ∫∫.sub.0.sup.nf(x,y)d(x). By using such volumetric solvers, one is able to identify when a stopping point is reached.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Regarding Claim 5: Gergov discloses The computer-implemented method of Claim 4, wherein the boundary integration method is based on a one-dimensional (1D) boundary-integration equation set of partial differential equations (PDEs) and wherein determining the advancement of the moving boundary includes solving, by the at least one processor, the 1D boundary-integration equation set of PDEs. (Gergov. “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity. Volumetric solvers require the solution of second order differential equations: ∫∫.sub.0.sup.nf(x,y)d(x). By using such volumetric solvers, one is able to identify when a stopping point is reached.”)
Regarding Claim 6: Gergov does not explicitly recite The computer-implemented method of Claim 4, wherein the moving boundary includes a plurality of boundary elements, wherein determining the advancement of the moving boundary includes employing element layers of the mesh model to guide advancement of the plurality of boundary elements, and wherein the boundary integration method further includes: employing, on the time-step-by-time-step basis, a time increment that prevents a boundary element of the plurality of boundary elements from advancing more than two element layers of the element layers of the mesh model within the time increment.
However Jiang recites The computer-implemented method of Claim 4, wherein the moving boundary includes a plurality of boundary elements, wherein determining the advancement of the moving boundary includes employing element layers of the mesh model to guide advancement of the plurality of boundary elements, and wherein the boundary integration method further includes: employing, on the time-step-by-time-step basis, a time increment that prevents a boundary element of the plurality of boundary elements from advancing more than two element layers of the element layers of the mesh model within the time increment. (Jiang. Abstract, “The time steps of implicit algorithm were controlled by injection ratio and local mesh information of flow front to achieve “one time step, one element-layer” for filling simulation; the sub-time steps of computing temperatures were calculated for each node according to local courant number, and the thermal simulation was conducted by the filled order of nodes.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the “one time step, one element-layer” rule of Jiang for the filling simulation of Gergov since the rule allows for the “the injection simulation could generate the credible results since no elemental layer was skipped.” (Jiang. Page 1411, top right)
Regarding Claim 7: Gergov discloses The computer-implemented method of Claim 1, wherein the at least one indication of behavior of the injection molding process includes a filling pattern of the filling stage. (Gergov. “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part. Part parameters 210a may also include the final temperature at which the part is removed from the mold 110. The final temperature may be selected by the operator, or otherwise determined as the temperature at which the part maintains its shape.”)
Regarding Claim 8: Gergov discloses The computer-implemented method of Claim 1, wherein the at least one indication of behavior of the injection molding process includes a graphical representation of the filling stage of the part cavity over time, and wherein outputting the at least one indication includes displaying the graphical representation on a display screen of a computer device. (Gergov. “[0046] FIG. 3 is graph 300 illustrating changes to molding parameters over time during an injection molding process using the injection molding device 100.” Examiner Note: the molding parameters track the location of the injection over time and the line on the graph represents the 1D element as claimed, see [0051] “As can be seen in the simulation illustrated in FIG. 3, the melt pressure 340 initially spikes as the injection material passes from the large diameter portion 130 to the reduced diameter portion 140 of the gate 120.”)
Regarding Claim 9: Gergov discloses The computer-implemented method of Claim 1, wherein the material is a polymer (Gergov “[0019] In some examples, the injection material may be an expanding crosslinking polymer (e.g., ethylene-vinyl acetate or “EVA”, “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part.”) and wherein the mesh model is a surface mesh model of the part cavity. (Gergov “[0054] The model solution domain is then defined and discretized by any of a variety of methods, such as by finite element analysis in which a finite element model is produced by generating a finite element mesh based on the solid model in step 420. The mesh consists of a plurality of contiguous solid elements defined by shared nodes.” Examiner Note: the contiguous solid elements would appear to read on the surface mesh aspect of the claims)
Gergov does not explicitly disclose a mid-plane mesh model.
However Jiang recites a mid-plane mesh model. (Jiang, Page 1412, “2.3.2. Non-uniform temperature distribution of flow front During mold filling, melts at the flow front move from the mid-plane toward the mold wall, this phenomenon is referred as the fountain flow.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the mid-plane mesh aspect of Jiang for the filling simulation of Gergov since the aspect of a mid-plane is an aspect of a known phenomenon of “fountain flow” in a filling simulation. (Jiang, Page 1412, Section 2.3.2)
Regarding Claim 11: Gergov discloses A computer-based system for determining behavior of an injection molding process, the computer-based system comprising:
at least one memory; (Gergov. “[0022] FIG. 2 is a schematic drawing showing the inputs and outputs of a modeling and molding system 200. In one embodiment, computerized models of the injection molding device 100 and molds 110 are built, and computerized simulations of the injection molding process are run to find optimal results in various conditions. The computerized simulations may also be used iteratively to adjust the initial parameters to further optimize the injection molding process.”)
and at least one processor coupled to the at least one memory, the at least one processor configured to: (Gergov. “[0022] FIG. 2 is a schematic drawing showing the inputs and outputs of a modeling and molding system 200. In one embodiment, computerized models of the injection molding device 100 and molds 110 are built, and computerized simulations of the injection molding process are run to find optimal results in various conditions. The computerized simulations may also be used iteratively to adjust the initial parameters to further optimize the injection molding process.”)
perform a computer simulation, in real-time, the computer simulation including simulating a filling stage of an injection molding process that fills a part cavity of a part with material over a filling time, the simulating based on a boundary integration method and a mesh model, the mesh model stored in the at least one memory and representing the part cavity, the simulating including computing a part thickness distribution of the mesh model, (Gergov. “[0021] Prior systems have attempted to optimize filling time and cooling time by relying on table data that relates a given measurement to adjustments in the speed of the driving mechanism or to other adjustments. In the presently disclosed system, real data is acquired from real time measurements and additional parameters are mathematically calculated. The real time measurements and calculated parameters are used to adjust the speed of the driving mechanism on the fly.” “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part.” “[0054] The model solution domain is then defined and discretized by any of a variety of methods, such as by finite element analysis in which a finite element model is produced by generating a finite element mesh based on the solid model in step 420. The mesh consists of a plurality of contiguous solid elements defined by shared nodes.” “[0055] With the resultant finite element model or other discretized solution domain defined, a user specifies boundary conditions in step 430 for the analysis. The boundary conditions include the parameters 210 as well as the calculated parameters discussed above.”)
the boundary integration method including computing velocity and temperature at a of the material over the part thickness distribution computed and determining advancement of the based on the velocity and temperature computed; and (Gergov. “[0056] Once the boundary conditions have been entered, the multi-physics FEA executes the instructions in accordance with the simulation model to first calculate or solve relevant filling phase process variables in step 440. As discussed above, such variables can include fluidity, mold cavity fill time, pressure, shear rate, stress, velocity, viscosity, and temperature.” “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity.”)
output at least one indication of behavior of the injection molding process determined based on the simulating, the simulating transpiring in real-time relative to the filling time. (Gergov. “[0059] Once the simulation reaches the stage in the analysis where it is determined that the mold cavity has been filled, the computer executes the instructions in accordance with the simulation model to next calculate or solve relevant packing phase process variables for the nodes in step 450. Such variables can include the mass properties of the component produced in accordance with the simulation model such as density and volumetric shrinkage, in addition to fluidity, packing time, pressure, shear rate, stress, velocity, viscosity, and temperature. [0060] During the simulation, data is recorded at each of the sensor locations. Such data recordation may be referred to as data capture by the virtual sensors in the solid model. Specifically, the pressure, volume, and temperature are recorded at the sensor locations during the simulation, so that pressure, volume, and temperature curves can be created. The pressure, volume, and temperature curves can represent the change of pressure, volume, and temperature over time or the change of pressure, volume, and temperature per unit of displacement of the injection material.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Regarding Claim 12: Gergov discloses The computer-based system of Claim 11, wherein the boundary integration method further includes employing a representation of a moving boundary of the and wherein the representation of the moving boundary is a one-dimensional (1D) element. (Gergov. “[0046] FIG. 3 is graph 300 illustrating changes to molding parameters over time during an injection molding process using the injection molding device 100.” Examiner Note: the molding parameters track the location of the injection over time and the line on the graph represents the 1D element as claimed, see [0051] “As can be seen in the simulation illustrated in FIG. 3, the melt pressure 340 initially spikes as the injection material passes from the large diameter portion 130 to the reduced diameter portion 140 of the gate 120.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Regarding Claim 13: Gergov discloses The computer-based system of Claim 11, wherein the boundary integration method further includes computing an incremental pressure drop and wherein determining the advancement includes employing the incremental pressure drop computed. (Gergov. “[0033] As the injection material passes through the main passageway 150, the arms 160, and the exit nozzles 170, the injection material experiences additional shears and changes in pressure, further affecting the flow rate of the injection material. Likewise, as the injection material experiences further shears and changes in pressure as it flows through the molds 110.” “[0049] The hydraulic injection pressure 320 then drops as the injection material begins to pass through the main passageway 150, then increases again as the injection material passes through arms 160 and the exit nozzles 170. The hydraulic injection pressure 320 then decreases as the molds 110 fill. As can be seen in this graph 300, the hydraulic injection pressure 320 dropped at different rates during different simulations, based on changes to other parameters.”)
Regarding Claim 14: Gergov discloses The computer-based system of Claim 11, wherein determining the advancement of the includes determining, on a time-step-by-time-step basis, advancement of a moving boundary of the of the material within the part cavity represented by the mesh model, the simulating including advancing, on the time-step-by-time step basis, the moving boundary based on the advancement determined for the moving boundary. (Gergov. “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity. Volumetric solvers require the solution of second order differential equations: ∫∫.sub.0.sup.nf(x,y)d(x). By using such volumetric solvers, one is able to identify when a stopping point is reached.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Regarding Claim 15: Gergov discloses The computer-based system of Claim 14, wherein the boundary integration method is based on a one-dimensional (1D) boundary-integration equation set of partial differential equations (PDEs) and wherein determining the advancement of the moving boundary includes solving, by the at least one processor, the 1D boundary-integration equation set of PDEs. (Gergov. “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity. Volumetric solvers require the solution of second order differential equations: ∫∫.sub.0.sup.nf(x,y)d(x). By using such volumetric solvers, one is able to identify when a stopping point is reached.”)
Regarding Claim 16: Gergov does not explicitly recite The computer-based system of Claim 14, wherein the moving boundary includes a plurality of boundary elements, wherein determining the advancement of the moving boundary includes employing element layers of the mesh model to guide advancement of the plurality of boundary elements, and wherein the boundary integration method further includes: employing, on the time-step-by-time-step basis, a time increment that prevents a boundary element of the plurality of boundary elements from advancing more than two element layers of the mesh model within the time increment.
However Jiang recites The computer-based system of Claim 14, wherein the moving boundary includes a plurality of boundary elements, wherein determining the advancement of the moving boundary includes employing element layers of the mesh model to guide advancement of the plurality of boundary elements, and wherein the boundary integration method further includes: employing, on the time-step-by-time-step basis, a time increment that prevents a boundary element of the plurality of boundary elements from advancing more than two element layers of the mesh model within the time increment. (Jiang. Abstract, “The time steps of implicit algorithm were controlled by injection ratio and local mesh information of flow front to achieve “one time step, one element-layer” for filling simulation; the sub-time steps of computing temperatures were calculated for each node according to local courant number, and the thermal simulation was conducted by the filled order of nodes.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the “one time step, one element-layer” rule of Jiang for the filling simulation of Gergov since the rule allows for the “the injection simulation could generate the credible results since no elemental layer was skipped.” (Jiang. Page 1411, top right)
Regarding Claim 17: Gergov discloses The computer-based system of Claim 11, wherein the at least one indication of behavior of the injection molding process includes a filling pattern of the filling stage. (Gergov. “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part. Part parameters 210a may also include the final temperature at which the part is removed from the mold 110. The final temperature may be selected by the operator, or otherwise determined as the temperature at which the part maintains its shape.”)
Regarding Claim 18: Gergov discloses The computer-based system of Claim 11, wherein the at least one indication of behavior of the injection molding process includes a graphical representation of the filling stage of the part cavity over time, and wherein outputting the at least one indication includes displaying the graphical representation on a display screen of a computer device. (Gergov. “[0046] FIG. 3 is graph 300 illustrating changes to molding parameters over time during an injection molding process using the injection molding device 100.” Examiner Note: the molding parameters track the location of the injection over time and the line on the graph represents the 1D element as claimed, see [0051] “As can be seen in the simulation illustrated in FIG. 3, the melt pressure 340 initially spikes as the injection material passes from the large diameter portion 130 to the reduced diameter portion 140 of the gate 120.”)
Regarding Claim 20: Gergov discloses A non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by at least one processor, causes the at least one processor to:
perform a computer simulation, in real-time, the computer simulation including simulating a filling stage of an injection molding process that fills a part cavity of a part with material over a filling time, the simulating based on a boundary integration method and a mesh model, the mesh model stored in the at least one memory and representing the part cavity, the simulating including computing a part thickness distribution of the mesh model, (Gergov. “[0021] Prior systems have attempted to optimize filling time and cooling time by relying on table data that relates a given measurement to adjustments in the speed of the driving mechanism or to other adjustments. In the presently disclosed system, real data is acquired from real time measurements and additional parameters are mathematically calculated. The real time measurements and calculated parameters are used to adjust the speed of the driving mechanism on the fly.” “[0027] Part parameters 210a include the estimated weight of the part, the heat transfer area of the part, nominal wall thickness, other part geometries, surface finish, and the minimum and maximum wall thickness of the part.” “[0054] The model solution domain is then defined and discretized by any of a variety of methods, such as by finite element analysis in which a finite element model is produced by generating a finite element mesh based on the solid model in step 420. The mesh consists of a plurality of contiguous solid elements defined by shared nodes.” “[0055] With the resultant finite element model or other discretized solution domain defined, a user specifies boundary conditions in step 430 for the analysis. The boundary conditions include the parameters 210 as well as the calculated parameters discussed above.”)
the boundary integration method including computing velocity and temperature at a of the material over the part thickness distribution computed and determining advancement of the based on the velocity and temperature computed; and (Gergov. “[0056] Once the boundary conditions have been entered, the multi-physics FEA executes the instructions in accordance with the simulation model to first calculate or solve relevant filling phase process variables in step 440. As discussed above, such variables can include fluidity, mold cavity fill time, pressure, shear rate, stress, velocity, viscosity, and temperature.” “[0057] In this system, the multi-physics FEA is able to create melt characterization in real time using solvers. Notably, the system calculates volume as a function of time (V(t)) rather than simply measuring volume. The system characterizes melt from the beginning to the end of the process to examine the relationship between volume and flow. In one embodiment, the system employs volumetric solvers to calculate the volume filled in the cavity.”)
output, via the processor, at least one indication of behavior of the injection molding process determined based on the simulating, the simulating transpiring in real- time relative to the filling time. (Gergov. “[0059] Once the simulation reaches the stage in the analysis where it is determined that the mold cavity has been filled, the computer executes the instructions in accordance with the simulation model to next calculate or solve relevant packing phase process variables for the nodes in step 450. Such variables can include the mass properties of the component produced in accordance with the simulation model such as density and volumetric shrinkage, in addition to fluidity, packing time, pressure, shear rate, stress, velocity, viscosity, and temperature. [0060] During the simulation, data is recorded at each of the sensor locations. Such data recordation may be referred to as data capture by the virtual sensors in the solid model. Specifically, the pressure, volume, and temperature are recorded at the sensor locations during the simulation, so that pressure, volume, and temperature curves can be created. The pressure, volume, and temperature curves can represent the change of pressure, volume, and temperature over time or the change of pressure, volume, and temperature per unit of displacement of the injection material.”)
Gergov does not explicitly disclose the aspect of a flow front.
However Jiang recites a flow front calculation (Jiang. Page 1407, right column, 1st full paragraph)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the flow front aspect of Jiang in the filling simulation of Gregov since it is necessary in order to “accurately predict some phenomena” in “flow fields in complex geometries.” (Jiang. Page 1407, right column, 1st full paragraph) This applies to all instances of “flow front” in the claims.
Allowable Subject Matter
5. Claims 10 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim 10 recites: The computer-implemented method of Claim 1, wherein the mesh model representing the part cavity is a discretized surface representation of a geometry of the part cavity, wherein determining the advancement of the flow front includes determining, on a time- step-by-time-step basis, advancement of a moving boundary of the flow front of the material, wherein the moving boundary includes a plurality of flow front nodes and wherein, at each time step of determining the advancement of the moving boundary includes:(a) computing the part thickness distribution from the discretized surface representation of the geometry of the part cavity; (b) determining process parameters, the process parameters including flow rate distribution and time steps based on input process conditions; (c) computing an average thickness distribution of the flow front and an average fluidity of the flow front; (d) computing an average advancing speed of the flow front; (e) computing an average temperature of the flow front; (f) computing a temperature-and-shear-rate dependent integration for fluidity on each flow front node of the plurality of flow front nodes; (g) computing a flow front nodal speed for each flow front node of the plurality of flow front nodes, wherein computing the flow front nodal speed includes employing a speed ratio; (h) advancing the moving boundary of the flow front according to each flow front nodal speed computed, the advancing being within the discretized surface representation of the geometry of the part cavity, the advancing producing an advanced flow front location; (i) computing pressure and temperature distributions according to the advanced flow front location produced and, based on the pressure and temperature distributions computed, determining whether an injection-molding-machine related pressure limit has been reached or a whole flow front temperature has dropped below a polymer freezing- point temperature, wherein the material is a polymer with the polymer freezing-point temperature, and determining whether the part cavity has been filled, completely; and (j) ending the simulating in an event the injection-molding-machine related pressure limit is determined to have been reached, the whole flow front temperature is determined to have dropped below the polymer freezing-point temperature, or the part cavity is determined to have been filled, completely, and, in an event the simulating is not ended, repeating (b)-(j) for a next time step.
Claim 19 recites: The computer-based system of Claim 11, wherein the mesh model representing the part cavity is a discretized surface representation of a geometry of the part cavity, wherein determining the advancement of the flow front includes determining, on a time-step-by- time-step basis, advancement of a moving boundary of the flow front of the material, wherein the moving boundary includes a plurality of flow front nodes and wherein, at each time step of determining the advancement of the moving boundary includes:(a) computing the part thickness distribution from the discretized surface representation of the geometry of the part cavity; (b) determining process parameters, the process parameters including flow rate distribution and time steps based on input process conditions; (c) computing an average thickness distribution of the flow front and an average fluidity of the flow front; (d) computing an average advancing speed of the flow front; (e) computing an average temperature of the flow front; (f) computing a temperature-and-shear-rate dependent integration for fluidity on each flow front node of the plurality of flow front nodes; (g) computing a flow front nodal speed for each flow front node of the plurality of flow front nodes, wherein computing the flow front nodal speed includes employing a speed ratio and the average advancing speed; (h) advancing the moving boundary of the flow front according to each flow front nodal speed computed, the advancing being within the discretized surface representation of the geometry of the part cavity, the advancing producing an advanced flow front location; (i) computing pressure and temperature distributions according to the advanced flow front location produced and, based on the pressure and temperature distributions computed, determining whether an injection-molding-machine related pressure limit has been reached or a whole flow front temperature has dropped below a polymer freezing- point temperature, wherein the material is a polymer with the polymer freezing-point temperature, and determining whether the part cavity has been filled, completely; and (j) ending the computer simulation in an event the injection-molding-machine related pressure limit is determined to have been reached, the whole flow front temperature is determined to have dropped below the polymer freezing-point temperature, or the part cavity is determined to have been filled, completely, and, in an event the simulating is not ended, repeating (b)-(j) for a next time step.
The closest prior art of record in addition to the prior art cited in the rejection above includes:
i) Chang, Rong‐yeu, and Wen‐hsien Yang. "Numerical simulation of mold filling in injection molding using a three‐dimensional finite volume approach." International Journal for Numerical Methods in Fluids 37.2 (2001): 125-148 which teaches the simulating in an injection molding system.
ii) U.S. Patent No. 10703030 which teaches a simulated injection molding system.
iii) Hua, Shaozhen, et al. "Simulation of jetting in injection molding using a finite volume method." Polymers 8.5 (2016): 172 which teaches the simulation of an injection molding system.
However, the closest prior art of record does not explicitly teach of render obvious the limitations above,
particularly in combination with the other limitations within the claims. The dependent claims are allowable for at least the same reasons as their respective independent claims.
Conclusion
6. 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.
7. All Claims are rejected.
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
i) Chang, Rong‐yeu, and Wen‐hsien Yang. "Numerical simulation of mold filling in injection molding using a three‐dimensional finite volume approach." International Journal for Numerical Methods in Fluids 37.2 (2001): 125-148 which teaches the simulating in an injection molding system.
ii) U.S. Patent No. 10703030 which teaches a simulated injection molding system.
iii) Hua, Shaozhen, et al. "Simulation of jetting in injection molding using a finite volume method." Polymers 8.5 (2016): 172 which teaches the simulation of an injection molding system.
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SAA
/SAIF A ALHIJA/Primary Examiner, Art Unit 2186