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 .
DETAILED ACTION
1. Claims 1-20 are presented for examination.
Claim Rejections - 35 USC section 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
2. Claims 5, 12, and 19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As per Claims 5, 12, and 19, they recite the limitation “said physical product with a tolerance outside said predetermined tolerance range” which is unclear what the limitation refers. The claim introduces “tolerance” as a property of the identified combinations without stating what quantity that term denotes, and further the specification at paragraph and [0114] state that:
[0065] The result of such an analysis is then compared against a predefined tolerance range to determine if a potential defect has been discovered. As a result, such an analysis involves determining whether any combination of components to be assembled into the physical product has been identified as failing to meet the predetermined tolerance range thereby identifying a potential defect in assembling the physical product. A “tolerance range,” as used herein, refers to the statistical boundaries that represent the range of outcomes for a given process. For example, a tolerance range may correspond to a thickness dimension (e.g., maximum thickness of 0.82 mm and a minimum thickness of 0.75 mm) for the physical product that was assembled based on integrating three separate components to form the physical product.
[0114] Tolerance refers to the maximum variance in the dimensions of the components where such components can still be assembled together to form the composite product (or a larger component of the composite product) properly.
Thus, “tolerance” is ambiguous as there are two readings that yield different claim scope: (a) the permitted variance specified for the components where tolerance refers to the maximum variance in the dimensions of the components where such components can still be assembled together properly as described at paragraph [0114]; or (b) the measured dimensional outcome of the combination, which is the quantity the specification compares against the “predetermined tolerance range” - that range being defined at paragraph [0065] as the statistical boundaries that represent the range of outcomes for a given process. Under reading (a) the recitation is internally inconsistent, because a permitted maximum variance is itself a bound and cannot lie “outside” the range against which conformance is measured while under reading (b) the recitation is coherent but claims a different thing. Thus, it is unclear and indefinite the metes and bounds of the claimed invention is. Examiner Interpretation: the limitation “with a tolerance outside said predetermined tolerance range” is interpreted as requiring that the measured dimensional outcome of the identified combination of components falls outside the statistical boundaries of the predetermined tolerance range, consistent with paragraphs [0065], [0140], and [0141] of the specification where the comparison being described as determining whether any combination of components has been identified as failing to meet the predetermined tolerance range..
Claim Rejections - 35 USC section 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
3. Claims 1-5, 8-12, and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Söderberg (“Toward a Digital Twin for real-time geometry assurance in individualized production”) in view of Kohlhoff (US 2019/0266804 A1).
As per Claim 1, 8, and 15, Söderberg teaches a computer-implemented method/computer program product/system for optimizing a manufacturing process of a physical product using a virtual environment (section 1.3 “Digital Twin for geometry assurance”, pg. 138; section 6, pg. 140), comprising:
receiving component batch data regarding batches of components to be assembled into said physical product (section 5, pgs. 139-140 “The Digital Twin has an interface to the inspection database that contains information about individual part geometries as well as statistical distributions for batches of parts”; section 1.1, pg. 137: inspection data for parts, gathered per batch as statistical distributions, is received into the twin, i.e., the “component batch data” as claimed);
generating a representative sample as a digital representation for each batch of components to be used in said virtual environment based on said component batch data (section 2.2, pg. 138 “Variation simulation can be performed by utilizing transformation matrices to calculate how part variation propagates in the assembly. The method is often combined with Monte Carlo (MC) simulation”; section 2, pg. 138; section 5, pg. 140: the Monte Carlo variation simulation draws sampled digital part instances from the per-batch statistical distributions, so each batch is represented in the simulation by generated representative digital geometry. Examiner’s Note -the claimed “representative sample as a digital representation for each batch” corresponds to the sampled part-variation instances the Monte Carlo simulation generates from the statistical distributions stored for batches of parts); and
creating and executing a digital twin simulation in said virtual environment using said digital representation for each batch of components (section 4, pg. 139 “the virtual assembly model (variation simulation model) is used together with inspection data to control production and to detect and correct errors”: the inherited Digital Twin containing the part geometries is executed as the virtual assembly model over batches or individuals); and
identifying a combination of components to be assembled into said physical product that fails to meet a predetermined tolerance range based on said digital twin simulation (section 4, pg. 139; section 1.1, pg. 137; section 2.1, pg. 138: the geometry-assurance process decomposes product requirements into tolerances on the parts and subassemblies, the stability analysis shows how variation propagates and affects critical features and dimensions, and the executed variation-simulation model is used to detect errors, so the simulation evaluates a candidate combination of scanned parts against the defined tolerances. Examiner’s Note - Söderberg states the tolerances against which the assembly is evaluated and the simulation that predicts each combination’s deviation and the predicted deviation of Söderberg to be compared against those defined tolerances, which is the claimed identification of a combination that “fails to meet a predetermined tolerance range”). In particular, Söderberg teaches a Digital Twin for geometry assurance in which per-batch statistical part data from an inspection database feeds a Monte Carlo/finite-element variation simulation of the assembled product, executed as a virtual assembly model that detects and corrects geometrical errors before and during production.
However, Söderberg fails to teach explicitly (Claim 8) one or more computer readable storage mediums having program code embodied therewith; a memory for storing a computer program for optimizing a manufacturing process of a physical product using a virtual environment; (Claim 15) a processor connected to the memory, wherein the processor is configured to execute program instructions of the computer program; and (Claim 1, 8, and 15) generating an alert indicating a potential defect in assembling said physical product.
Kohlhoff teaches (Claim 8) one or more computer readable storage mediums having program code embodied therewith (Fig. 8, [0027] “The computer system 800 includes a processor 805 that executes software instructions or code stored on a computer readable storage medium 855 to perform the above-illustrated methods. The computer system 800 includes a media reader 840 to read the instructions from the computer readable storage medium 855 and store the instructions in storage 810 or in random access memory (RAM) 815. … The processor 805 reads instructions from the RAM 815 and performs actions as instructed.”);
(Claim 15) a memory for storing a computer program for optimizing a manufacturing process of a physical product using a virtual environment and a processor connected to the memory, wherein the processor is configured to execute program instructions of the computer program (Fig. 8, [0027]); and
(Claim 1, 8, and 15) generating an alert indicating a potential defect in assembling said physical product ([0023] “The 3D model of the component is dynamically validated while assembling the virtual workbench.”; [0021] “The AR/VR application validates the installation sequence of component 'B' and notifies the operator that the sequence is incorrect.”: the application validates and then, on a failed validation, notifies the operator, so the notification issues in response to the validation outcome, i.e., the “alert indicating a potential defect in assembling” generated “in response to” the identification as claimed; in the combination the identification supplied to it is Söderberg’s out-of-tolerance determination). In particular, Kohlhoff teaches an AR/VR virtual workbench, provided as program code executing on a computing device, in which an operator assembles 3D component models of a product while the application dynamically validates each assembly step in real time and notifies the operator when an assembly step is invalid.
Söderberg and Kohlhoff are analogous art because they are both from the same field of endeavor, virtual assembly simulation and validation of physical products before physical assembly.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to incorporate Kohlhoff into Söderberg’s invention for the purpose of a Digital Twin for real-time geometry assurance in individualized production to provide a virtual prototype build that is very efficient, in place of a build that would otherwise be very cumbersome and time consuming (Kohlhoff: [0024]).
As per Claim 2, 9, and 16, Söderberg teaches wherein said component batch data comprises statistical data, assembly data, dimensional data, test data, and/or characteristic data (section 5, pgs. 139-140 “database that contains information about individual part geometries as well as statistical distributions for batches of parts.”; section 1.1, pg. 137: the inspection database carries statistical distributions for batches of parts and individual part geometries, i.e., statistical data and dimensional data as claimed).
As per Claim 3, 10, and 17, Söderberg teaches wherein said digital twin simulation forms optimization data, wherein said optimization data comprises data used to quantify compatibility between said batches of components (section 5, pg. 140 “
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”: the deviation from nominal matching criterion computed for candidate pairings of parts drawn from the sorted classes quantifies how compatibly parts from the batches assemble, i.e., the “optimization data” as claimed).
As per Claim 4, 11, and 18, Söderberg fails to teach explicitly enabling a user to interact with said digital representation for each batch of components in said virtual environment to virtually assemble at least a portion of a digital product representation of said physical product.
Kohlhoff teaches enabling a user to interact with said digital representation for each batch of components in said virtual environment to virtually assemble at least a portion of a digital product representation of said physical product ([0019]-[0020] “The hand movement of the operator is received as continuous visual motion signals referred to as trajectories corresponding to assembling a 3D model of a component.”: the operator manipulates the 3D component models in the virtual workbench to build up the virtual product).
As per Claim 5, 12, and 19, Söderberg fails to teach explicitly guiding said user through a virtual assembly interaction using said component batch data and said optimization data to identify one or more combinations of components to be assembled into said physical product with a tolerance outside said predetermined tolerance range.
Kohlhoff teaches guiding said user through a virtual assembly interaction using said component batch data and said optimization data to identify one or more combinations of components to be assembled into said physical product with a tolerance outside said predetermined tolerance range ([0019]-[ 0021] “With a 'show installation' command, the component gets highlighted in its final location in the product to help the operator find the right location.”: the operator is guided step by step through the virtual assembly while the application validates each step and highlights where a component belongs; in the combination it is Söderberg’s per-batch variation simulation that determines which combinations fall outside the tolerance range, and Kohlhoff’s guidance walks the user to them).
4. Claims 6, 7, 13, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Söderberg (“Toward a Digital Twin for real-time geometry assurance in individualized production”) in view of Kohlhoff (US 2019/0266804 A1), and further in view of Jayaram (US 2002/0123812 A1).
Söderberg as modified by Kohlhoff teaches most all the instant invention as applied to claims 1-5, 8-12, and 15-19 above.
As per Claim 6, 13, and 20, Söderberg as modified by Kohlhoff fails to teach explicitly generating haptic feedback to alert said user to said one or more combinations of components to be assembled into said physical product with said tolerance outside said predetermined tolerance range.
Jayaram teaches generating haptic feedback to alert said user to said one or more combinations of components to be assembled into said physical product with said tolerance outside said predetermined tolerance range ([0013] “Additionally, the invention can produce different types of haptic feedback for a user including force, sound and temperature.”; [0090] “If there is any interference detected during the assembly process, the user can try to find a way to get around it in the virtual environment.”: haptic feedback in the virtual assembly environment alerts the user at the exact instants where the parts being assembled interfere, i.e., to component combinations that cannot be assembled as intended). In particular, Jayaram teaches a virtual assembly design environment in which a user assembles CAD part models with tracked virtual hands while collision and swept-volume analysis identifies interferences, and haptic feedback including force, sound and temperature is produced for the user.
Söderberg, Kohlhoff, and Jayaram are analogous art because they are all from the same field of endeavor, virtual assembly simulation and validation of physical products before physical assembly.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to incorporate Jayaram into Söderberg as modified by Kohlhoff’s invention for the purpose of a Digital Twin for real-time geometry assurance in individualized production to provide a virtual prototype build that is very efficient, in place of a build that would otherwise be very cumbersome and time consuming (Kohlhoff: [0024]) and to provide full-size assembly in a virtual environment giving intuitive and valuable information that is impossible to obtain from conventional assembly modeling by CAD system (Jayaram: [0094]).
As per Claim 7 and 14, Söderberg as modified by Kohlhoff teaches generating a recommendation for addressing said one or more combinations of components to be assembled into said physical product with said tolerance outside said predetermined tolerance range (Kohlhoff: [0019]-[0021] “With a 'show installation' command, the component gets highlighted in its final location in the product to help the operator find the right location.”: upon an invalid assembly step the application indicates the correct installation for the component, i.e., a “recommendation for addressing” the defective combination as claimed).
Conclusion
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wärmefjord et al. (“Inspection Data to Support a Digital Twin for Geometry Assurance”) teaches inspection-data support for a production digital twin including selective assembly of parts by pairwise matching and statistical process control applied to classes of parts.
Zhang (US 2022/0207206 A1) teaches building geometric digital twin models of parts that integrate measured geometric distribution errors for virtual assembly analysis.
Atkinson (US 5956251 A) teaches statistical tolerancing of assemblies using production-lot sample statistics to predict conformance of assemblies to tolerance limits before assembly.
Marsh (US 7756321 B2) teaches virtually fitting measured part assemblies in a computer and referring out-of-tolerance fit results for corrective action.
Rudnitsky (US 2022/0342400 A1) teaches verifying robotic manufacturing control code in a simulator with feedback identifying detected errors and options to correct them.
6. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EUNHEE KIM whose telephone number is (571)272-2164. The examiner can normally be reached Monday-Friday 9am-5pm ET.
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, Ryan Pitaro can be reached at (571)272-4071. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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EUNHEE KIM
Primary Examiner
Art Unit 2188
/EUNHEE KIM/Primary Examiner, Art Unit 2188
Prosecution Insights