The present disclosure provides an injection molding method and system. The injection molding method includes the operations of: sensing physical parameters associated with an injection molding product; analyzing physical parameters to generate an optimized digital twin model of a physical asset; and producing the injection molding product according to the optimized digital twin model. Analyzing the physical parameters to generate the optimized digital twin model of the physical asset includes operations of: simulating, by a digital twin model, the physical parameters to generate simulated parameters according to first input parameters; validating whether the digital twin model is an optimized digital twin model according to the simulated parameters and the physical parameters; and optimizing the digital twin model to generate the optimized digital twin model when the physical parameters differ from the simulated parameters.

Embodiments relate to an aligner breakage solution that tests probability of aligner breakage at weak points. A method includes gathering a digital model representing an aligner for a dental arch of a patient, receiving material property information for a material to be used to manufacture the aligner, and analyzing one or more regions of the aligner. Analyzing a region of the aligner comprises simulating application of a load around the region, determining at least one of a stress, a strain or a strain energy density at the region, evaluating a strength of the aligner at the region, and determining whether the region satisfies a damage criterion based on the strength of the aligner at the region.

The computer-implemented method for glass bending includes obtaining a deviation of a real shape of a glass from a desired shape of the glass, the glass is produced by a glass bending process; determining a variation of at least one parameter associated with the glass bending process, at least in part based on the deviation of the real shape from the desired shape; and adjusting the at least one parameter based on the variation for compensation of the deviation.

According to examples, an apparatus may include a processor that may access a digital model of an item to be fabricated to have a plurality of features, in which the digital model may include a surface. The processor may pack a plurality of digital ellipsoids to intersect the surface of the digital model of the item, in which the plurality of digital ellipsoids are arranged with respect to each other based on a curvature of the surface. The processor may also determine locations on the surface at which the plurality of digital ellipsoids intersect the surface and may set the determined locations as points on the surface at which the plurality of features are to be formed.

A method of designing and engineering a building element (e.g., a staircase) that is structurally verified and may be easily certified. The method uses a parametric three-dimensional (3D) model of the building element and a constraint space definition. It ensures that the building element will fit in the building and will comply with functional, legal, and/or other requirements, such as strength, dimensional requirements, or use of certain materials. A computer system provides a user tool for easily amending the building element while visualizing it in its specific use. It also converts the amended building element to processing instructions for 3D manufacturing, such that the end product complies with the constraint space definition. A user without extensive knowledge of engineering, complex computer-aided design (CAD) programs, or 3D manufacturing can easily amend a design to his or her personal need and have the building element custom produced.

A computing device includes: a tomographic image acquisition unit that acquires a plurality of tomographic images representing shapes of reinforcing fibers and shapes of resin in a plurality of cross sections obtained when an article containing the reinforcing fibers and the resin is divided in parallel; and a computing unit that calculates a rigidity parameter of each of a plurality of small regions obtained by dividing the article, based on the plurality of acquired tomographic images.

Described is a method for creating a network for simulating an object, wherein the network is determined by means of object data of the object, that is used to provide a digital representation of the object that has a plurality of spatially resolved structural information relating to the object. The method may comprise: providing object data of the object; carrying out a first simulation of at least one spatially resolved physical variable of the object by means of the object data; determining spatially resolved structural information to be taken into consideration by means of the simulated spatially resolved physical variable of the object for a network for simulating the object from the plurality of spatially resolved structural information; and creating the network by means of the structural information for a second simulation of the object. A computer-implemented method may reduce the number of elements of the network for the simulation.

The invention relates to a method for transferring a stress state of an FE simulation result to a new FE mesh geometry of a simulated construction system, such as a component for motor vehicles that has a 3-D shape, in a simulation chain of production operations, comprising: a) providing a first data set, which describes the FE simulation result with a stress state of the FE simulation of the construction system or component of a first production operation, b) creating the new FE mesh geometry of the simulated construction system or component, which new FE mesh geometry is associated with a second production operation, c) transferring the stress state of the provided first data set to the new FE mesh geometry of the construction system or component, d) performing an equilibrium calculation by using the stress tensor in the FE mesh geometry, wherein deformation of the construction system or component results, which deformation differs from the deformation in the FE mesh by a shape alteration u>tolerance value ε, e) iteratively repeating the equilibrium calculation as a cyclic equilibrium iteration in the new FE mesh geometry (in the new target FE mesh) of the construction system or component, wherein, in each cycle, a new stress state is applied to the FE mesh geometry of the construction system or component and stress components that lead to undesired shape alterations are decreased until a displacement/termination criterion of shape alteration u<tolerance value ε is achieved, and f) displaying the fulfilled condition of u<ε.

In various embodiments, a stylization subsystem automatically modifies a three-dimensional (3D) object design. In operation, the stylization subsystem generates a simplified quad mesh based on an input triangle mesh that represents the 3D object design, a preferred orientation associated with at least a portion of the input triangle mesh, and mesh complexity constraint(s). The stylization subsystem then converts the simplified quad mesh to a simplified T-spline. Subsequently, the stylization subsystem creases one or more of edges included in the simplified T-spline to generate a stylized T-spline. Notably, the stylized T-spline represents a stylized design that is more convergent with the preferred orientation(s) than the 3D object design. Advantageously, relative to prior art approaches, the stylization subsystem can more efficiently modify the 3D object design to improve overall aesthetics and manufacturability.

Embodiments relate to an aligner breakage solution that tests damage to an aligner using machine learning. A method includes of training a machine learning model to predict damage to an orthodontic aligner includes gathering a training dataset comprising digital designs for a plurality of orthodontic aligners, wherein each digital design is associated with a respective orthodontic aligner of the plurality of orthodontic aligners, and wherein each digital design comprises metadata indicating whether the associated respective orthodontic aligner was damaged during manufacturing of the associated respective orthodontic aligner. The method further includes training the machine learning model using the training dataset, wherein the machine learning model is trained to process data from a digital design for an orthodontic aligner and to output a probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner.