DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are presented for examination.
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/30/24 was considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Claim Rejections - 35 USC § 102
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.
5. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
6. Claims 1-20 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Wowczuk et al. (Wowczuk), US publication no. 2021/0291259 A1.
As per claim 1, Wowczuk teaches a method of creating a mold design for casting a product [figures 2-4], the method comprising:
receiving, by a processor, product design information for one or more metal products [para 6, 50];
preprocessing, by the processor, the product design information to create a pre-processed file [8, 31];
creating, by the processor, one or more mold designs using the preprocessed file [figure 4; para 56];
analyzing, by the processor, the one or more mold designs to detect the presence or absence of defects [para 7, 15, 61];
nesting, by the processor, the one or more mold designs in a work area; and generating, by the processor, printing instructions for the one or more mold designs [figure 5; para 31, 43].
Wowczuk teaches:
[0031] Some embodiments are directed to a method of generating a mold, the method comprising obtaining a product design through a digital input, manipulating the digital input to prepare a mold information, and making a mold from the mold information using an additive manufacturing process. In some embodiments, a method of making
a cast product may comprise obtaining a product design through a digital input, manipulating the digital input to prepare the mold information, making a mold from the mold information using an additive manufacturing process, positioning the mold in a build area, forming a cast part or a cast product from the mold using a cast material; and, optionally, finishing the cast product per customer specifications. In some embodiments, one or more cast parts are needed for the cast product. In some embodiments, the digital input is manipulated/modified to optimize a mold design for the additive manufacturing process. In some embodiments, the digital input may be manipulated/modified to make a mold design by optimizing part size, dimensional depth, dimensional profile, profilometry (surface roughness/finish), strength, porosity, compaction, orientation, feature complexity, or the like. This manipulation and/or modification of the digital input can optimize the final product and/or processing
characteristics across the scope of manufactured products. In some embodiments, the feature complexity may include typefaces or design aspects. In some embodiments, individual mold designs may be nested to optimize material use and production speed during the additive manufacturing process.
[0056] Once the product model has been created, a mold for casting the product can be designed. FIG. 4 illustrates a sample process for creating a mold for a specific digital product model. A processing device, such as logic devices 105, 110 as described above, or a processing device integrated into, for example, manufacturing device 120, can initially input 405 a product model. It should be noted that, when creating a mold for casting a product, the model of the product can be used as a template to create the mold. Thus, the mold is shaped as a negative of the model, defining open spaces associated with solid features of the products, and having solid spaces associated with open features of the product.
[0061] The processing device can further optimize 430 the mold design. In certain implementations, optimizing 430 the mold design can include one or more of determining a wall thickness to prevent blow-out defects, determining a minimum
mold height to achieve an independent and/or stable pour velocity (according to, for example, Chvorinov's Rule), determining a pour cup strategy, determining a venting
strategy, and determining other optimization parameters, such as angling the mold, modifying the orientation of the mold, and other similar ideas and concepts.
As per claim 2, Wowczuk teaches the preprocessing comprises:
editing, by the processor, the product design information; and converting, by the processor, the product design information to at least one of an encapsulated postscript (EPS) vector, Portable Document Format (PDF), or Scalable Vector Graphics (SVG) [para 30, 40, 51].
As per claim 3, Wowczuk teaches the analyzing comprises: rendering, by the processor, a two-dimensional image for each of the one or more mold designs;
classifying, by the processor, each two-dimensional image using a machine learning algorithm; and generating, by the processor, an error flag in response to the classification corresponding to the presence of a defect [para 15, 50, 54, 61].
As per claim 4, Wowczuk teaches the machine learning algorithm [modeling application] is a convolutional neural network [para 34, 35, 50].
As per claim 5, Wowczuk teaches training the machine learning algorithm on a data set of images comprising labeled defects [para 35, 50, 61].
As per claim 6, Wowczuk teaches rendering the two dimensional image further comprises mirroring elements associated with a cavity in the one or more mold designs [para 50, 61].
As per claim 7, Wowczuk teaches generating the printing instructions comprises slicing, by the processor, the one or more mold designs into a plurality of two-dimensional slices [para 41, 44, 58].
As per claim 8, Wowczuk teaches creating, by the manufacturing device, the mold by an additive manufacturing process according to the printing instructions [figure 2; para 41, 44].
As per claim 9, Wowczuk teaches creating the mold by an additive manufacturing process comprises printing the mold with sand [para 29, 38, 47].
As per claim 10, Wowczuk teaches analyzing comprises: extracting, by the processor, text from the one or more mold designs using optical character recognition; and analyzing, by the processor, the text for at least one of spelling errors, character alignment, or character size consistency [para 50, 54].
As to claims 11-20, basically are the corresponding elements that are carried out the method of operating step in claims 1-10. Accordingly, claims 11-20 are rejected for the same reason as set forth in claims 1-10.
7. Examiner's note: Examiner has cited particular paragraphs and columns and line numbers in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. MPEP 2141.02 VI: “PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS."
8. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Aoyagi al., US publication no. 2024/0139815, discloses an additive manufacturing development method comprising: predicting a defect that occurs in a product based on a combination of a plurality of design data and a plurality of manufacturing conditions, which are used to additively manufacture the product;
collecting defect detection data for defect detection by monitoring the product during manufacturing in accordance with the combination of the plurality of design data and the plurality of manufacturing conditions.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHUN CAO whose telephone number is (571)272-3664. The examiner can normally be reached on M-F 7:30 am-4:00 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached on 571-272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHUN CAO/Primary Examiner, Art Unit 2115
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