Applying Annotations to Three-Dimensional (3D) Object Data Models Based on Object Parts
US-2016246767-A1 · Aug 25, 2016 · US
US12124237B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12124237-B2 |
| Application number | US-202318133660-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 12, 2023 |
| Priority date | Oct 27, 2016 |
| Publication date | Oct 22, 2024 |
| Grant date | Oct 22, 2024 |
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A method for generating a quote for fabrication of a part to be fabricated includes receiving, from a customer device associated with a customer, a design request for a part to be fabricated by a fabrication process, the design request including a two-dimensional drawing file representing the part to be fabricated and descriptive information including a descriptive datum. The method includes extracting a first feature from the 2D drawing file, wherein the first feature represents a geometry of the part to be fabricated. The method includes extracting a second feature from the descriptive information, wherein the second feature represents the descriptive datum. The method includes generating, as a function of the first and second features, a quote for fabrication for the part to be fabricated, the quote for fabrication including a cost and time to fabricate the part to be fabricated and sending the quote for fabrication to the customer.
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What is claimed is: 1. A method for generating a quote for fabrication of a part to be fabricated, the method comprising: receiving, from a customer device associated with a customer, a design request for a part to be fabricated by a fabrication process, the design request including a two-dimensional (2D) drawing file representing the part to be fabricated and descriptive information including a descriptive datum; extracting a first feature from the 2D drawing file, wherein the first feature represents a geometry of the part to be fabricated; extracting a second feature from the descriptive information, wherein the second feature represents the descriptive datum; determining an orientation on a build plate for fabricating the part to be fabricated based on the first and second features, wherein determining the orientation comprises selecting the orientation to maximize the number of instances while fabricating the part to be fabricated that a printer can print simultaneously; generating, as a function of the orientation determined for the part to be fabricated, a quote for fabrication for the part to be fabricated, the quote for fabrication including a cost and time to fabricate the part to be fabricated; and sending the quote for fabrication to the customer. 2. The method of claim 1 , wherein the descriptive information is distinct from the 2D drawing file of the part to be fabricated. 3. The method of claim 2 , wherein extracting the second feature from the descriptive information comprises extracting the second feature from the descriptive datum. 4. The method of claim 1 , wherein the descriptive information comprises textual data relating to the part to be fabricated. 5. The method of claim 1 , wherein extracting the first feature from the 2D drawing file comprises receiving data corresponding to one or more interactions with an interface. 6. The method of claim 1 , wherein extracting the second feature from the descriptive information comprises receiving data corresponding to one or more interactions with an interface. 7. The method of claim 1 , wherein extracting the second feature comprises using one or more machine-learning modules, wherein the one or more machine-learning modules are configured to: extract, from the descriptive information, the descriptive datum of the part to be fabricated; associate, as a function of the descriptive datum, a property of the part to be fabricated with a 3D structure; and send, to the customer, the 3 D structure as a function of the associated property. 8. The method of claim 1 , wherein generating a quote for fabrication comprises using one or more machine-learning modules, wherein the one or more machine-learning modules are configured to: determine, as a function of the first and second extracted features, a plurality of fabrication methods associated with a part to be fabricated; and determine, for each of the fabrication methods of the plurality of fabrication methods, a respective cost associated with the part to be fabricated. 9. The method of claim 1 , wherein generating a quote for fabrication comprises using one or more machine-learning modules, wherein the one or more machine-learning modules are configured to: receive a plurality of fabrication methods associated with a part to be fabricated; score each fabrication method of the plurality of fabrication methods; select, as a function of the scores for each fabrication method of the plurality of fabrication methods, a fabrication method from the plurality of fabrication methods; and send, to the customer, the selected fabrication method. 10. The method of claim 1 , wherein the quote for fabrication of the part to be fabricated is associated with at least an anticipated fabricating tool. 11. A system for generating a quote for fabrication of a part to be fabricated, the system comprising: a computing device, the computing device configured to: receive, from a customer device associated with a customer, a design request for a part to be fabricated by a fabrication process, the design request including a two-dimensional (2D) drawing file representing the part to be fabricated and descriptive information including a descriptive datum; extract a first feature from the 2D drawing file, wherein the first feature represents a geometry of the part to be fabricated; extract a second feature from the descriptive information, wherein the second feature represents the descriptive datum of the part to be fabricated; determine an orientation on a build plate for fabricating the part to be fabricated based on the first and second features, wherein determining the orientation comprises selecting the orientation to maximize the number of instances while fabricating the part to be fabricated that a printer can print simultaneously; and a quote generator operating on the computing device, the quote generator configured to: generate, as a function of the orientation determined for the part to be fabricated, a quote for fabrication for the part to be fabricated, the quote for fabrication including a cost and time to fabricate the part to be fabricated; send the quote for fabrication to the customer. 12. The system of claim 11 , wherein the descriptive information is distinct from the 2D drawing file of the part to be fabricated. 13. The system of claim 12 , wherein extracting the second feature from the descriptive information comprises extracting the second feature from the descriptive datum. 14. The system of claim 11 , wherein the descriptive information comprises textual data relating to the part to be fabricated. 15. The system of claim 11 , wherein extracting the first feature from the 2D drawing file comprises receiving data corresponding to one or more interactions with an interface. 16. The system of claim 11 , wherein extracting the second feature from the descriptive information comprises receiving data corresponding to one or more interaction with an interface. 17. The system of claim 11 , further comprising one or more machine-learning modules operating on the computing device, wherein the one or more machine-learning modules are configured to: extract, from the descriptive information, the descriptive datum of the part to be fabricated; associate, as a function of the descriptive datum, a property of the part to be fabricated with a 3D structure; and send, to the customer, the 3D structure as a function of the associated property. 18. The system of claim 11 , further comprising one or more machine-learning modules operating on the computing device, wherein the one or more machine-learning modules is configured to: determine, as a function of the first and second extracted features, a plurality of fabrication methods associated with a part to be fabricated; and determine, for each of the fabrication methods of the plurality of fabrication methods, a respective cost associated with the part to be fabricated. 19. The system of claim 11 , further comprising one or more machine-learning modules operating on the computing device, wherein the one or more machine-learning modules are configured to: receive a plurality of fabrication methods associated with a part to be fabricated; score each fabrication method of the plurality of fabrication methods; select, as a function of the scores for each fabrication method of the plurality of fabrication methods, a fabrication method from the plurality of fabrication methods; and send, to the customer, the selected fabrication method. 20. The s
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