EP-4741138-A2 - EVEN HEAT DISTRIBUTION IN THERMOFORMING DENTAL APPLIANCES

Abstract

A method includes receiving sensor data associated with manufacturing of one or more dental appliances in a dental appliance manufacturing system. The method further includes providing the sensor data as input into a trained machine learning model and receiving output from the trained machine learning model. The method further includes determining, based on the output, one or more heating element setpoints to cause a substantially even heat distribution on a sheet of plastic to form the one or more dental appliances.

Inventors

• MARTÍNEZ GONZÁLEZ, Luis Carlos
• GARCIA SAUCEDO, ROWAN FERNANDO
• RITO MARTINEZ, Mario Alfonso
• NÚÑEZ GARCÍA, ISMAEL
• ALFARO, RENÉ DAVID
• SAMBU, SHIVA P.

Assignees

• Align Technology, Inc.

Dates

Publication Date

20260513

Application Date

20220610

Claims (15)

1. A method comprising: receiving sensor data associated with manufacturing of one or more dental appliances in a dental appliance manufacturing system; providing the sensor data as input into a trained machine learning model; receiving, from the trained machine learning model, output; and determining, based on the output, one or more heating element setpoints to cause a substantially even heat distribution on a sheet of plastic to form the one or more dental appliances.
2. The method of claim 1, wherein the input to the trained machine learning model further comprises heating capacity data associated with one or more of a mold of a dental arch or a corresponding sheet of plastic associated with forming a dental appliance of the one or more dental appliances.
3. The method of claim 1, wherein the input to the trained machine learning model further comprises heating time data.
4. The method of claim 1, wherein the sensor data comprises a first subset and a second subset, the first subset being associated with ambient temperature, and the second subset being associated with target or actual temperature data associated with the sheet of plastic.
5. The method of claim 1, wherein the dental appliance manufacturing system comprises a plurality of heating elements, wherein each heating element of the plurality of heating elements corresponds to a respective zone of a plurality of zones associated with the sheet of plastic, and wherein the one or more heating element setpoints correspond to one or more of the plurality of zones.
6. The method of claim 1, wherein each of the one or more heating element setpoints corresponds to a respective amount of energy to be provided to a corresponding heating element.
7. The method of claim 1, wherein the sensor data corresponds to current setpoints and the one or more heating element setpoints correspond to one or more updates to the current setpoints.
8. The method of claim 1 further comprising causing energy to be output to one or more heating elements of the dental appliance manufacturing system to operate based on the one or more heating element setpoints.
9. The method of claim 1, wherein the sensor data is received from a plurality of sensors
10. The method of claim 9, wherein two or more sensors are associated with each zone of a plurality of zones of the dental appliance manufacturing system.
11. The method of claim 10, wherein each zone of the plurality of zones is associated with a corresponding heating element.
12. The method of claim 1 further comprising: receiving historical sensor data associated with historical manufacturing of historical dental appliances in a corresponding dental appliance manufacturing system; identifying historical heating element setpoints and historical heat distribution data associated with the historical manufacturing of the historical dental appliances; and training a machine learning model based on input data comprising the historical sensor data and target output comprising the historical heating element setpoints and the historical heat distribution data to generate the trained machine learning model.
13. The method of claim 12, wherein the historical heat distribution data is one or more of heating that is substantially constant, heating that meets a threshold time, or heating that does not meet the threshold time.
14. A non-transitory computer-readable storage medium storing instructions that, when executed by a processing device, cause the processing device to perform the method of one or more of claims 1-13.
15. A system comprising: a memory; and a processing device coupled to the memory, the processing device to perform the method of one or more of claims 1-13.

Description

TECHNICAL FIELD The technical field relates to the field of manufacturing dental appliances and, in particular, to dynamic thermoforming of dental appliances. BACKGROUND For some applications, shells are formed around molds to achieve a negative of the mold. The shells are then removed from the molds to be further used for various applications. One example application in which a shell is formed around a mold and then later used is corrective dentistry or orthodontic treatment. In such an application, the mold is of a dental arch for a patient and the shell is a dental appliance (e.g., aligner to be used for aligning one or more teeth of the patient, orthodontic retainers, orthodontic splints, sleep appliances for mouth insertion, etc.). Molds may be formed using rapid prototyping equipment such as 3D printers, which may manufacture the molds using additive manufacturing techniques (e.g., stereolithography) or subtractive manufacturing techniques (e.g., milling).The dental appliances may then be formed over the molds one at a time using the dental appliance manufacturing equipment that is sized and configured the same for all sizes of dental appliances. The forming of dental appliances one at a time using dental appliance manufacturing equipment that is sized and configured the same for all sizes of dental appliances may result in a bottleneck in the dental appliance production process and may result in waste of material, time, and energy. SUMMARY Some example implementations are summarized herein. In a first implementation, a method comprises: identifying first geometry of a first mold associated with a first dental arch and a second geometry of a second mold associated with a second dental arch; determining, based on the first geometry and the second geometry, that the first mold and the second mold are to be used for simultaneous forming of a first dental appliance and a second dental appliance on a plate in a dental appliance manufacturing system; and causing, based on the first geometry and the second geometry, one or more portions of the dental appliance manufacturing system to be configured to form the first dental appliance and the second dental appliance. A second implementation may extend the first implementation. In the second implementation, the method further comprises determining the first mold matches a first digital model associated with the first dental arch and the second mold matches a second digital model associated with the second dental arch. A third implementation may extend the second implementation. In the third implementation, the method further comprises: capturing one or more images of the first mold associated with the first dental arch; identifying, from at least one of the one or more images, a first identifier associated with the first dental arch; and retrieving, based on the first identifier, the first digital model corresponding to the first mold, wherein the determining that the first mold matches the first digital model is responsive to providing the one or more images and the first digital model to a trained machine learning model. A fourth implementation may extend the third implementation. In the fourth implementation, the identifying of the first identifier is via one or more of optical character recognition (OCR) or reading an asset tag. A fifth implementation may extend any of the first through fourth implementations. In the fifth implementation, determining that the first mold and the second mold are to be used for the simultaneous forming is to minimize plastic used during the simultaneous forming. A sixth implementation may extend any of the first through fifth implementations. In the sixth implementation, causing of the one or more portions of the dental appliance manufacturing system to be configured comprises causing one or more of width or length of a pallet to be adjusted, and wherein a sheet of plastic sized based on the first geometry and the second geometry is to be secured to the pallet to form the first dental appliance and the second dental appliance. A seventh implementation may extend any of the first through sixth implementations. In the seventh implementation, causing of the one or more portions of the dental appliance manufacturing system to be configured comprises causing one or more of mask size, heating element position, or temperature of a heating section of the dental appliance manufacturing system to be adjusted. An eighth implementation may extend any of the first through seventh implementations. In the eighth implementation, a heating section of the dental appliance manufacturing system is configured to heat a sheet of plastic for the forming of the first dental appliance and the second dental appliance, and wherein the sheet of plastic is an oval shape. A ninth implementation may extend any of the first through eighth implementations. In the ninth implementation, causing of the one or more portions of the dental appliance manufacturing sy