Method to facilitate mass conversion of 2D drawings to 3D models
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.
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.
2. The method of claim 1 , wherein said other three-dimensional models comprise models created by other crowd members.
3. The method of claim 1 , wherein said other three-dimensional models comprise a digital representation of a product depicted in the two-dimensional drawings.
4. The method of claim 3 , where said digital representation is a scan of said product depicted in the two-dimensional drawings.
5. The method of claim 1 , wherein said match between said three-dimensional models comprises an indication of conversion accuracy.
6. 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.
7. The method of claim 1 , where said transmitting and receiving of said two-dimensional drawings and three-dimensional models is internet based.
8. The method of claim 1 , wherein said transmitting and receiving of said two-dimensional drawings and three-dimensional models is cloud based.
9. The method of claim 1 , wherein said comparison is done manually.
10. The method of claim 1 , wherein said comparison is done by computer program stored in a non-transitory computer-readable medium.
11. The method of claim 1 , wherein said selecting of said crowd members is based on pre-determined criteria or is random.
12. 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.
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.
14. The server of claim 13 , wherein said other three-dimensional models comprise models created by other crowd members.
15. The server of claim 13 , wherein said other three-dimensional models comprise a digital representation of a product depicted in the two-dimensional drawings.
16. The server of claim 15 , where said digital representation is a scan of said product depicted in the two-dimensional drawings.
17. 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.
18. The server of claim 17 , where said tolerances can vary depending on the characteristics of said features.
19. The server of claim 18 , wherein said characteristics comprise mass or volume.
20. The server of claim 11 , wherein said selecting of said crowd members is based on pre-determined criteria.
21. The server of claim 13 , wherein said computer-readable instruction comprises artificial intelligence, machine learning, or advanced analytic and statistical techniques.
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.