A computer-implemented method (110) for designing at least one shaped body (112), a computer-implemented method (138) for designing a manufacturing process for manufacturing at least one shaped body (112), a designing system (152) for designing at least one shaped body (112) and a manufacture-designing system for designing a manufacturing process for manufacturing at least one shaped body (112). The computer-implemented method (110) for designing at least one shaped body (112) comprises: a) retrieving, by using at least one interface (154), at least one set of target criteria for the shaped body (112); b) defining, by using at least one geometry defining unit (156), at least one seed geometry for the shaped body (112); c) generating, by using at least one parameter generating unit (158), a set of parameters comprising at least one geometry parameter of the seed geometry; d) simulating, by using at least one simulation unit (160), the shaped body by varying values of the set of parameters and by corn-paring simulated criteria for these values with the set of target criteria, thereby generating at least one adapted set of parameters for which the target criteria are fulfilled at least within predetermined tolerances; and e) determining, by using at least one lead candidate geometry defining unit (162), at least one lead candidate geometry of the at least one shaped body (112) from the adapted set of parameters.

A computer-implemented method (110) for designing at least one shaped body (112), a computer-implemented method (138) for designing a manufacturing process for manufacturing at least one shaped body (112), a designing system (152) for designing at least one shaped body (112) and a manufacture-designing system for designing a manufacturing process for manufacturing at least one shaped body (112). The computer-implemented method (110) for designing at least one shaped body (112) comprises: a) retrieving, by using at least one interface (154), at least one set of target criteria for the shaped body (112); b) defining, by using at least one geometry defining unit (156), at least one seed geometry for the shaped body (112); c) generating, by using at least one parameter generating unit (158), a set of parameters comprising at least one geometry parameter of the seed geometry; d) simulating, by using at least one simulation unit (160), the shaped body by varying values of the set of parameters and by corn-paring simulated criteria for these values with the set of target criteria, thereby generating at least one adapted set of parameters for which the target criteria are fulfilled at least within predetermined tolerances; and e) determining, by using at least one lead candidate geometry defining unit (162), at least one lead candidate geometry of the at least one shaped body (112) from the adapted set of parameters.

A system for assisting the design of manufactured components requiring post-processing and comprising an input module receiving original design data relative to engineering requirements of a component and manufacturing and post-processing data relative to the component. The system also comprising a compensation determination module receiving the original design data and the manufacturing and post-processing data from the input module, predicting the geometrical deviations created by the at least one post-processing procedure and generating dimension compensation data defining compensations for each one of the features of the component using at least one machine learning model generated by a machine learning algorithm trained using a training dataset. The system further comprises a compensated model generation module configured to receive the compensation data and to generate a compensated Computer Assisted Design (CAD) model therefrom. A computer implemented method for assisting the design of manufactured components requiring post-processing is also provided.

A system for assisting the design of manufactured components requiring post-processing and comprising an input module receiving original design data relative to engineering requirements of a component and manufacturing and post-processing data relative to the component. The system also comprising a compensation determination module receiving the original design data and the manufacturing and post-processing data from the input module, predicting the geometrical deviations created by the at least one post-processing procedure and generating dimension compensation data defining compensations for each one of the features of the component using at least one machine learning model generated by a machine learning algorithm trained using a training dataset. The system further comprises a compensated model generation module configured to receive the compensation data and to generate a compensated Computer Assisted Design (CAD) model therefrom. A computer implemented method for assisting the design of manufactured components requiring post-processing is also provided.

A computer-implemented method includes receiving, in computer memory, a first test data set that comprises results of a real-world test of a material, where the first test data set comprises a plurality of test data points. The method further includes identifying one or more critical points among the test data points in the first test data set and processing the first test data set with a computer processor to produce a second test data set with differing (e.g., fewer) test data points than the first test data set, wherein the second test data set includes all the test data points that were identified as critical points in the first test data set and at least some other data points.

A computer-implemented method includes receiving, in computer memory, a first test data set that comprises results of a real-world test of a material, where the first test data set comprises a plurality of test data points. The method further includes identifying one or more critical points among the test data points in the first test data set and processing the first test data set with a computer processor to produce a second test data set with differing (e.g., fewer) test data points than the first test data set, wherein the second test data set includes all the test data points that were identified as critical points in the first test data set and at least some other data points.

In a dimension creation device, an element selector selects a first target element and a second target element from elements of a three-dimensional model. A direction indicator indicates a direction of a dimension to be created. A dimension creator creates, when the element selector selects a vertex or an edge as each of the first target element and the second target element and the three-dimensional model includes a first orthogonal face including the first target element and orthogonal to the direction indicated by the direction indicator and a second orthogonal face including the second target element and orthogonal to the direction indicated by the direction indicator, the dimension between the first orthogonal face and the second orthogonal face in the direction indicated by the direction indicator in a manner associated with the first orthogonal face and the second orthogonal face.

In a dimension creation device, an element selector selects a first target element and a second target element from elements of a three-dimensional model. A direction indicator indicates a direction of a dimension to be created. A dimension creator creates, when the element selector selects a vertex or an edge as each of the first target element and the second target element and the three-dimensional model includes a first orthogonal face including the first target element and orthogonal to the direction indicated by the direction indicator and a second orthogonal face including the second target element and orthogonal to the direction indicated by the direction indicator, the dimension between the first orthogonal face and the second orthogonal face in the direction indicated by the direction indicator in a manner associated with the first orthogonal face and the second orthogonal face.

Disclosed herein are systems and methods for providing personalized oral irrigation. One variation of a method of generating a model of an oral insert including a fluid inlet port, fluid nozzles, manifolds, and a tray configured to retain teeth may comprise the steps of displaying a graphical representation of the oral insert model, generating a geometry of the fluid nozzles based on oral scan data of a jaw, defining a tray surface that encloses the fluid nozzles based on the oral scan data, generating a geometry of the manifolds that connect the fluid inlet port to the fluid nozzles on the graphical representation of the oral insert model. The manifolds are configured to provide a predetermined range of hydraulic pressures to each of the fluid nozzles.

Disclosed herein are systems and methods for providing personalized oral irrigation. One variation of a method of generating a model of an oral insert including a fluid inlet port, fluid nozzles, manifolds, and a tray configured to retain teeth may comprise the steps of displaying a graphical representation of the oral insert model, generating a geometry of the fluid nozzles based on oral scan data of a jaw, defining a tray surface that encloses the fluid nozzles based on the oral scan data, generating a geometry of the manifolds that connect the fluid inlet port to the fluid nozzles on the graphical representation of the oral insert model. The manifolds are configured to provide a predetermined range of hydraulic pressures to each of the fluid nozzles.