# US 12,217,376 B2 · Method to facilitate mass conversion of 2D drawings to 3D models

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- Number: US 12,217,376 B2
- Document ID: US12217376B2
- Status: Granted
- Kind: B2
- Application number: 17/871,758
- Filed: 2022-07-22
- Published: 2022-11-17
- Granted: 2025-02-04
- Earliest claimed: 2020-06-23
- Assignees: Draawn, LLC
- Applicants: Draawn, LLC
- Inventors: James Cotteleer; Mark Cotteleer
- Web page: https://patentgrep.com/patent/US12217376B2

## CPC

- G06F 30/10: Geometric CAD
- G06T 19/20: Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts
- G06F 18/22: Matching criteria, e.g. proximity measures
- G06F 30/12: characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD
- G06Q 10/06: Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q 10/101: Collaborative creation, e.g. joint development of products or services
- G06Q 10/103: {Workflow collaboration or project management}
- G06Q 50/04: Manufacturing
- G06T 7/001: {using an image reference approach}
- G06T 17/00: Three-dimensional [3D] modelling for computer graphics
- G06T 19/00: Manipulating three-dimensional [3D] models or images for computer graphics
- G06V 10/95: {structured as a network, e.g. client-server architectures}
- G06V 20/30: in albums, collections or shared content, e.g. social network photos or video
- G06V 20/653: {by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces}
- G06T 2207/30164: Workpiece; Machine component
- G06T 2219/012: Dimensioning, tolerancing
- G06T 2219/024: Multi-user, collaborative environment
- G06T 2219/2008: Assembling, disassembling
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

An internet or cloud-based system, method, or platform (“platform”) used to facilitate the conversion of electronic two-dimensional drawings to three-dimensional models. A group of people (“crowd”) that has been found qualified to make such conversions, are selected for the conversion. The two-dimensional drawings are transmitted to the crowd for conversion to three-dimensional models. In some embodiments, multiple instances of the same two-dimensional drawings (or image data) is sent to multiple, independent crowd members in order that multiple versions of the same three-dimensional model can be created. Once the models are complete and returned, they are compared to each other on multiple features or characteristics. If two or more three-dimensional models are found to match within the prescribed tolerances, they are determined to be an accurate representation of the product or device shown in the two-dimensional drawings. In some embodiments, the two-dimensional drawings can be divided into subparts and submitted to different crowd members for conversion.

## Claims

### Claim 1

A method for converting two-dimensional drawings to three-dimensional models, comprising:
assembling electronic two-dimensional drawings of a device;
selecting two or more members from a crowd to convert said two-dimensional device drawings to an electronic three-dimensional model;
dissecting said two-dimensional drawings into subparts;
electronically transmitting different ones of said subparts of said two-dimension drawings to at least two different ones of said selected crowd members for conversion to said three-dimensional models of said subparts;
electronically receiving said three-dimensional models from two or more selected crowd members; and
comparing said received three-dimensional models to other three-dimensional models to determine if there is a match between the three-dimensional models within pre-determined feature tolerances.

### Claim 2 (depends on 1)

The method of claim 1, wherein said other three-dimensional models comprise models created by other crowd members.

### Claim 3 (depends on 1)

The method of claim 1, wherein said other three-dimensional models comprise a digital representation of a product depicted in the two-dimensional drawings.

### Claim 4 (depends on 3)

The method of claim 3, where said digital representation is a scan of said product depicted in the two-dimensional drawings.

### Claim 5 (depends on 1)

The method of claim 1, wherein said match between said three-dimensional models comprises an indication of conversion accuracy.

### Claim 6 (depends on 1)

The method of claim 1, where said feature tolerances can comprise one or more features from a group including dimension, weight, mass, center of mass, moment of inertia, volume and axis of rotation.

### Claim 7 (depends on 1)

The method of claim 1, where said transmitting and receiving of said two-dimensional drawings and three-dimensional models is internet based.

### Claim 8 (depends on 1)

The method of claim 1, wherein said transmitting and receiving of said two-dimensional drawings and three-dimensional models is cloud based.

### Claim 9 (depends on 1)

The method of claim 1, wherein said comparison is done manually.

### Claim 10 (depends on 1)

The method of claim 1, wherein said comparison is done by computer program stored in a non-transitory computer-readable medium.

### Claim 11 (depends on 1)

The method of claim 1, wherein said selecting of said crowd members is based on pre-determined criteria or is random.

### Claim 12 (depends on 1)

The method of claim 1, utilizing artificial intelligence, machine learning, or advanced analytic and statistical techniques in performing one or more steps of said method.

### Claim 13

A server implemented with a computer, the server comprising:
at least one processor configured to execute a computer-readable instruction, wherein the at least one processor is configured to:
select one or more two-dimensional drawings in electronic form for conversion;
selecting two or more crowd members from a pool of previously approved conversion crowd members based on selected criteria;
dissecting said two-dimensional drawings into subparts;
transmitting different ones of said two-dimensional drawings to at least two different ones of said selected crowd members for conversion to electronic three-dimensional models of said subparts;
receiving said three dimensional models from at least two or more of said crowd members; and
comparing said received three-dimensional models to other three-dimensional models to determine if there is a match between the three-dimensional models within pre-determined feature tolerances.

### Claim 14 (depends on 13)

The server of claim 13, wherein said other three-dimensional models comprise models created by other crowd members.

### Claim 15 (depends on 13)

The server of claim 13, wherein said other three-dimensional models comprise a digital representation of a product depicted in the two-dimensional drawings.

### Claim 16 (depends on 15)

The server of claim 15, where said digital representation is a scan of said product depicted in the two-dimensional drawings.

### Claim 17 (depends on 13)

The server of claim 13, where said feature tolerances can comprise one or more features from a group including dimension, weight, mass, center of mass, moment of inertia, volume and axis of rotation.

### Claim 18 (depends on 17)

The server of claim 17, where said tolerances can vary depending on the characteristics of said features.

### Claim 19 (depends on 18)

The server of claim 18, wherein said characteristics comprise mass or volume.

### Claim 20 (depends on 11)

The server of claim 11, wherein said selecting of said crowd members is based on pre-determined criteria.

### Claim 21 (depends on 13)

The server of claim 13, wherein said computer-readable instruction comprises artificial intelligence, machine learning, or advanced analytic and statistical techniques.

### Claim 22

A server implemented with a computer, the server comprising:
at least one processor configured to execute a computer-readable instruction utilizing artificial intelligent or machine learning, wherein the at least one processor is configured to:
select two-dimensional drawings in electronic form for conversion;
select two or more crowd members from a pool of previously approved conversion crowd members based on selected criteria;
transmit said electronic two-dimensional drawings to at least two different ones of said selected crowd members for conversion said electronic two-dimensional drawings to one or more electronic three-dimensional models;
receive said one or more three dimensional models from at least two or more of said crowd members; and
compare said received one or more three-dimensional models to other three-dimensional models to determine if there is a match between the three-dimensional models within pre-determined feature tolerances.