SYSTEM AND METHOD FOR PERFORMING QUALITY CONTROL

• US 20190318479A1
• Filed: 06/28/2019
• Published: 10/17/2019
• Est. Priority Date: 03/22/2018
• Status: Active Grant

• Current Assignee: James R Glidewell Dental Ceramics Incorporated
• Original Assignee: James R Glidewell Dental Ceramics Incorporated
• Inventors: Ajri, Abhishek Babasaheb, Nemagrdi, Vaheh Golestanian, Jokada, Marco Antonio, Leeson, David Christopher
• Granted Patent: US 11,210,788 B2
• Time in Patent Office: Days
• CPC Class Codes: A61C 13/0004 Computer-assisted sizing or machining of dental prostheses
• CPC Class Codes: A61C 9/0093 Workpiece support
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 2113/10 Additive manufacturing, e.g. 3D printing
• CPC Class Codes: G06F 2119/18 Manufacturability analysis or optimisation for manufacturability
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 30/23 using finite element methods [FEM] or finite difference methods [FDM]
• CPC Class Codes: G06T 2207/30036 Dental; Teeth
• CPC Class Codes: G06T 2207/30052 Implant; Prosthesis
• CPC Class Codes: G06T 7/0014 using an image reference approach

Abstract

Disclosed are example embodiments of methods and systems for identifying and quantifying manufacturing defects of a manufactured dental prosthesis. Certain embodiments of the system for performing quality control on manufactured dental prostheses includes: a quality control module configured to determine whether the dental prosthesis is a good or a defective product based at least on a differences model generated by comparing a design model and a scanned model of the manufactured dental prosthesis.

Claims

1. A method for performing quality control on a manufactured dental prosthesis, the method comprising:

determining whether the manufactured dental prosthesis is a good or a defective product based at least on a differences model generated by comparing a design model and a scanned model of the manufactured dental prosthesis.

2. The method of claim 1, wherein determining whether the manufactured dental prosthesis is a good or defective product further comprises performing a statistical analysis on the differences model.

3. The method of claim 2, wherein determining whether the manufactured dental prosthesis is a good or defective product further comprises determining a standard deviation of offset values of points of the differences model.

4. The method of claim 3, wherein the manufactured dental prosthesis comprises an anterior crown and wherein the anterior crown is determined to be a defective product if the standard deviation is above 20 microns.

5. The method of claim 1, wherein the differences model generated by comparing the design model and the scanned model further comprises omitting from the differences model data points below a margin line of the differences model.

6. The method of claim 5, wherein the margin line has a height ranging between 10-20% of an overall height of the manufactured dental prosthesis.

7. The method of claim 5, wherein omitting from the differences model further comprises omitting data points of an occlusal surface of the manufactured dental prosthesis.

8. The method of claim 7, wherein the manufactured dental prosthesis is a bridge, and wherein omitting from the differences model further comprises omitting data points of an occlusal surface of each tooth of the bridge.

9. The method of claim 8, wherein the differences model generated by comparing the design model and the scanned model further comprises omitting data points of surfaces between any two teeth of the bridge.

10. The method of claim 1, wherein the differences model generated by comparing the design model and the scanned model further comprises omitting from the differences model data points of sprue locations, wherein a sprue location is where a sprue is placed to secure the manufactured dental prosthesis within a milling block.

11. The method of claim 1, further comprises determining that the manufactured dental prosthesis is too small or too large based on a distribution of differences that is negatively or positively biased as compared to a normal distribution.

12. The method of claim 1, further comprises determining that the manufactured dental prosthesis has a step when a distribution of differences includes peaks at a left and right side of a normal distribution curve.

13. The method of claim 1, further comprises:

determining whether the manufactured dental prosthesis is too small or too large based on a distribution of differences that is negatively or positively biased as compared to a normal distribution;

determining whether the manufactured dental prosthesis has a step when a distribution of differences includes peaks at a left and right side of a normal distribution curve; and

shutting down one or more crown manufacturing machineries based at least on whether the manufactured dental prosthesis is too small, too large, or has a step.

14. A system for performing quality control on a dental prosthesis, the system comprising:

a quality control module configured to determine whether the dental prosthesis is a good or a defective product based at least on a differences model generated by comparing a design model and a scanned model of the manufactured dental prosthesis.

15. The system of claim 14, wherein the quality control module is configured to determine whether the dental prosthesis is a good or defective product by determining a standard deviation of a difference value of points in the differences model.

16. The system of claim 15, wherein the dental prosthesis comprises an anterior crown and wherein the anterior crown is determined to be a defective product if the standard deviation is above 20 microns.

17. The system of claim 14, wherein the quality control module is further configured to omit from the differences model data points below a margin line of the differences model.

18. The system of claim 17, wherein the quality control module is further configured to omit data points of occlusal surfaces of the dental prosthesis from the differences model, wherein the dental prosthesis comprises a dental bridge.

19. The system of claim 18, wherein the quality control module is further configured to omit data points of surfaces between any two teeth of the dental bridge from the differences model.

20. The system of claim 14, wherein the quality control module is further configured to omit from the differences model data points of sprue locations, wherein a sprue location is where a sprue is placed to secure the dental prosthesis within a milling block.

21. The system of claim 14, further comprises determining that the manufactured dental prosthesis is too small or too large based on a distribution of differences that is negatively or positively biased as compared to a normal distribution.

22. The system of claim 14, further comprises determining that the manufactured dental prosthesis has a step when a distribution of differences includes peaks at a left and right side of a normal distribution curve.

23. A method for performing quality control on a dental prosthesis, the method comprising:

generating a design model of a dental prosthesis;

manufacturing the dental prosthesis based on the generated design model;

scanning the manufactured dental prosthesis to create a 3D scan model;

generating a differences model by comparing the design model with the 3D scan model; and

determining whether the manufactured dental prosthesis is a good or a defective product based at least on a differences model.

24. A method for performing quality control on a design model of a dental prosthesis, the method comprising:

determining whether the design model of the dental prosthesis is a good or a design model based at least on a differences model generated by comparing the design model and a data model generated using a simulated manufacturing process.

25. The method of claim 24, wherein the simulated manufacturing process comprises a simulated CNC milling or 3D printing process.