公开(公告)号：US20240126938A1

公开(公告)日：2024-04-18

申请号：US18046972

申请日：2022-10-17

Applicant: Dassault Systemes SolidWorks Corporation

Inventor： Nicholas Constantine Birkett-Smith ,  Pruthvi Venkatesh ,  Manish Bharvirkar ,  Christopher George Brooking ,  Sushant Sinha

IPC: G06F30/17

CPC classification number: G06F30/17 ,  G06F2111/04

Abstract: A system and method automatically repairs a reference corresponding to a missing constraint of a component feature in a computer aided drafting (CAD) environment. A first component is identified where the reference indicates the missing component feature belongs. A solid or surface body of the first component is identified. A candidate replacement feature of the first solid or surface body is identified. The candidate replacement feature is compared with the missing feature. If the candidate comparison meets a predetermined criteria, the missing constraint reference is replaced with a reference to the candidate replacement feature.

公开(公告)号：US11941331B2

公开(公告)日：2024-03-26

申请号：US17897310

申请日：2022-08-29

Applicant: Dassault Systemes Simulia Corp.

Inventor： Bernd Crouse ,  Rui Xu

IPC: G06F30/20 ,  E21B43/16 ,  G01F1/704 ,  G01F1/74 ,  G06T15/08 ,  G01N13/00 ,  G01N33/24

CPC classification number: G06F30/20 ,  E21B43/16 ,  G01F1/704 ,  G01F1/74 ,  G06T15/08 ,  G01N13/00 ,  G01N33/24

Abstract: Systems, methods, and computer program products can be used for visualizing the behavior of flow of two or more fluid phases, wherein a fluid phase behavior is represented in a visualization. One of the methods includes determining an occupation time, which is the amount of elapsed time from when a fluid phase first occupies a particular location until a second time. The method includes generating data for a visualization, with a location in the visualization corresponding to the particular location, and with the generated data for that location in the visualization indicating the occupation time.

公开(公告)号：US11936830B2

公开(公告)日：2024-03-19

申请号：US17972322

申请日：2022-10-24

Applicant: DASSAULT SYSTEMES

Inventor： Maxime Pia

IPC: H04N1/32 ,  G06T1/00

CPC classification number: H04N1/32309 ,  G06T1/0092 ,  H04N1/3232

Abstract: A computer implemented method for embedding a marker in an image or video content including receiving an input image or frame for embedding, determining a binary message to be encoded within said input image or frame comprising bits sequences having an identical number of bits which is superior or equal to two, said binary message comprising at least a header part comprising at least two consecutive bits sequences which are not identical, detecting a region within said input image or frame such that the color within said region is uniform and that said region presents a chosen length and height, associating each possible bits sequence to a corresponding encoding color determined from the color within said uniform region and an encoding rule such that the respective colors are all different from one another, and generating a marker color table in which each element stores an encoding color associated to a bits sequence of the binary message, such that the color table constitutes a color encoding of the binary message, and embedding said marker in said region by appending directionally pixel blocks comprising at least a chosen number of pixels in an appending direction, the pixels within a given pixel block being each colored with the encoding color of an element of the marker color table, each element of the marker color table being associated with at least one pixel block.

公开(公告)号：US20240078353A1

公开(公告)日：2024-03-07

申请号：US18460054

申请日：2023-09-01

Applicant: DASSAULT SYSTEMES

Inventor： Julien BOUCHER ,  Mariem MEZGHANNI ,  Arthur NDOKO

IPC: G06F30/13 ,  G06F30/20 ,  G06T7/564

CPC classification number: G06F30/13 ,  G06F30/20 ,  G06T7/564 ,  G06T2207/10028

Abstract: A computer-implemented method for generating a 3D model representing a factory. The method includes obtaining a point cloud from a scan of the factory and fitting the point cloud with linear CAD extrusions. Such a method is an improved solution for generating a 3D model representing a factory.

公开(公告)号：US11922573B2

公开(公告)日：2024-03-05

申请号：US16727413

申请日：2019-12-26

Applicant: DASSAULT SYSTEMES

Inventor： Fernando Manuel Sanchez Bermudez ,  Eloi Mehr

IPC: G06T17/10 ,  G06F30/23 ,  G06F30/27 ,  G06N3/084 ,  G06N3/088 ,  G06N5/046 ,  G06N20/10 ,  G06T17/20 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82 ,  G06V20/64 ,  G06F119/18

CPC classification number: G06T17/10 ,  G06F30/23 ,  G06F30/27 ,  G06N3/084 ,  G06N3/088 ,  G06N5/046 ,  G06N20/10 ,  G06T17/20 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/647 ,  G06F2119/18

Abstract: The disclosure notably relates to computer-implemented method for learning a neural network configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes providing a dataset including freehand drawings each representing a respective 3D shape, and learning the neural network based on the dataset. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape.

公开(公告)号：US11886172B2

公开(公告)日：2024-01-30

申请号：US17645043

申请日：2021-12-17

Applicant: DASSAULT SYSTEMES

Inventor： Laure-Anne Poisson ,  Philippe Belmans ,  Ana Marcusanu ,  Vincent Siess

IPC: G05B19/418

CPC classification number: G05B19/41865 ,  G05B2219/32423

Abstract: It is proposed a method for factory operation. The method includes providing manufacturing tasks each represented by a law describing a manufacturing of a product by one or more manageable machines. The method includes obtaining one or more manufacturing constraints and one or more manufacturing events. The method includes determining an operating mode of the factory based on the one or more manufacturing constraints and on one or more product constraints. The determining includes one or more iterations. Each iteration computes a respective propensity of each manufacturing task representing a frequency with which the task is chosen for manufacturing the product given the constraints and/or a previous event(s) occurrence. The iteration ranks the tasks according to a propensity descending order. The iteration visits the tasks according to the ranking and affecting to each task one or more manageable machines and resources. The iteration executes the tasks until an event(s).

公开(公告)号：US20240028797A1

公开(公告)日：2024-01-25

申请号：US18358830

申请日：2023-07-25

Applicant: DASSAULT SYSTEMES

Inventor： Ali TLILI ,  Oumaima KHALED

IPC: G06F30/27

CPC classification number: G06F30/27

Abstract: A computer-implemented method for designing a manufacturing product. The method including obtaining a set of materials for manufacturing the product, a set of use and/or manufacturing constraints for the manufacturing product, and specifications indicating an extent of compatibility of one or more reference materials with the constraints. The method further including determining an optimal subset of the set of materials for manufacturing the product. The determining includes classifying the materials with respect to compatibility with the constraints and based on the provided specifications. This constitutes an improved method for designing a manufacturing product.

公开(公告)号：US20230418986A1

公开(公告)日：2023-12-28

申请号：US18341933

申请日：2023-06-27

Applicant: DASSAULT SYSTEMES

Inventor： Lucas BRIFAULT ,  Ariane JOURDAN ,  Eloi MEHR

IPC: G06F30/12

CPC classification number: G06F30/12

Abstract: The disclosure notably relates to a computer-implemented method for generating a CAD feature tree from a discrete geometrical representation of a mechanical product. The method comprises obtaining the discrete geometrical representation, and a set of CAD features. The method further comprises determining one or more sequences of CAD features from the set of CAD features by optimizing an objective function which rewards a fitting of the discrete geometrical representation by a candidate sequence, and penalizes a complexity of a candidate sequence, the complexity of a candidate sequence being a function of the candidate sequence that increases when adding a feature to the candidate sequence.

公开(公告)号：US20230393566A1

公开(公告)日：2023-12-07

申请号：US18331052

申请日：2023-06-07

Applicant: DASSAULT SYSTEMES

Inventor： Xavier GREHANT ,  Arnaud DALIE

IPC: G05B19/418 ,  G06T7/00

CPC classification number: G05B19/41875 ,  G06T7/001

Abstract: A computer-implemented method for inferring an emerging problem in product manufacturing. The method comprises obtaining a time-ordered set comprising one or more snapshots of a product and one or more similarity thresholds. The method also comprises obtaining at least one recent snapshot, the at least one recent snapshot being time-ordered after at least one snapshot of the time-ordered set. The method also comprises retrieving a subset of one or more snapshots from the time-ordered set, the one or more snapshots being time-ordered before the at least one recent snapshot and satisfying, with respect to the at least one recent snapshot, a similarity above at least one of the one or more similarity thresholds. The method also comprises determining a trend from the retrieved subset and a baseline, the trend being a time distribution of the snapshots of the retrieved subset with respect to the baseline.

公开(公告)号：US11829118B2

公开(公告)日：2023-11-28

申请号：US16855055

申请日：2020-04-22

Applicant: Dassault Systemes Simulia Corp.

Inventor： Alexander Jacobus Maria Van der Velden ,  Jing Bi ,  Subham Sett

IPC: G05B13/04 ,  G06N20/00 ,  B22F10/00 ,  G05B19/4099 ,  G06F30/10 ,  B33Y50/02 ,  B29C64/153 ,  B29C64/393 ,  G06F30/27 ,  G06F119/18 ,  G06F111/18 ,  G06F113/10

CPC classification number: G05B19/4099 ,  B22F10/00 ,  B29C64/153 ,  B29C64/393 ,  B33Y50/02 ,  G05B13/048 ,  G06F30/10 ,  G06F30/27 ,  G06N20/00 ,  G05B2219/49023 ,  G06F2111/18 ,  G06F2113/10 ,  G06F2119/18

Abstract: A method includes simulating a process, with computer-based software, to produce virtual data about the process; identifying process parameters for a real-world version of the process; providing a real-world sensor to sense a parameter associated with the real-world version of the process; receiving sensor readings from the real-world sensor while the real-world version is being performed; and training a machine-learning software model to predict a behavior of the real-world sensor based on the virtual data about the process, the process parameters, and the sensor readings.