Abstract: The disclosure notably relates to a computer-implemented method for machine-learning a classification function configured for detection of mechanical interfaces of a CAD model representing a single mechanical part. The method comprises obtaining a training dataset comprising graphs, each graph representing a CAD model representing a single mechanical part. Each graph comprises one or more nodes representing a canonical surface of the respective CAD model. Each node comprises a label from the list: primary face, secondary face, tertiary face, maintain face, or no interface. Each graph further comprises one or more edges representing a connection between the canonical surfaces. The method further comprises training the classification function based on the dataset to classify, with a label of the label list, each node of a graph representing a CAD model representing a single mechanical part. This provides an improved solution for detecting mechanical interfaces.

Abstract: A computer-implemented method for machine-learning a classification function configured for detection of mechanical interfaces of a CAD model representing a mechanical assembly of parts. The method includes obtaining a training dataset comprising graphs representing a local contact between parts of a CAD model. The graph includes one or more nodes representing canonical surfaces of the CAD model. Each node comprises a label within the label list: primary face, secondary face, tertiary face, maintain face, and no interface. The graph further includes one or more internal edges and one or more external edges. The method further includes training the classification function based on the training dataset to classify, with a label of the label list, each node of a graph representing a local contact between parts of a CAD model representing a mechanical assembly of parts. This provides an improved solution for detecting mechanical interfaces.

Abstract: The disclosure notably relates to a computer-implemented method for designing a 3D modeled object representing a product to be manufactured. The designing method comprises, by a computer system, displaying simultaneously a 3D shape representation of the 3D modeled object, and a 2D block representation of the 3D modeled object. The designing method also comprises by a user interacting graphically with the 2D block representation, performing a selection, among the at least one block node, of one or more connectors. The designing method also comprises using a pre-trained machine-learning function for prediction of one or more operators among the predetermined set of operators. The disclosure improves ergonomics.

Abstract: A computer-implemented method for machine-learning a function. The method includes obtaining a dataset including 2D polyline profiles each representing respectively a portion of a manufacturing contour in a result of a structural optimization that represents a mechanical part, each 2D polyline profile being associated in the dataset with a respective primitive parametric curve class among a predetermined set of primitive parametric curve classes. The method further comprises training the function based on the dataset. The function is configured to take an input 2D polyline profile and to provide an output primitive parametric curve class. Such a method forms an improved solution for processing a result of a structural optimization that represents a mechanical part.

Abstract: A computer-implemented method for designing a 3D modeled object representing a product to be manufactured, the designing method including, by a computer system, displaying simultaneously a 3D shape representation of the 3D modeled object, and a 2D block representation of the 3D modeled object. The method also comprises by a user interacting graphically with the 2D block representation, performing a selection of one or more block nodes among the at least one block node, upon user-action, adding to the 2D block representation a block node representing a respective operator of the subset, and automatically determining a respective arc between the output connector of each selected block node and a respective input connector of the added block node. The disclosure improves ergonomics.