Patent application EP18201618A (EP), filed 2018-10-19
Publication number: EP3486812A1
Title: AUTOMATIC ASSEMBLY MATE CREATION FOR FREQUENTLY-USED COMPONENTS
Abstract: [0001]    Methods and systems identify frequently-used CAD components and apply machine learning techniques to predict mateable entities and corresponding mate types for those components to automatically add components to a CAD model. An example method includes accessing information regarding CAD model parts and related mate information stored in a computer database, and dividing parts into a plurality of clusters having parts with similar global shape signatures. In response to a new part being added, contextual signatures of entities of the new part are input into a mateability predictor neural network to determine a mateable entity of the new part. Input into a mate-type predictor neural network is (i) a contextual signature of the mateable entity and (ii) a contextual signature of an entity of another part of the CAD model to determine a mate type between the entities. A mate between the new part and the other part is automatically added based on the determined mate type.
IPC codes: G06F  17/    50            A I
G06N  20/    00            A I
G06T  19/    20            A I
G06F  30/    17            A I
G06T  19/    00            A I
Claims: number: 1
text: A computer-implemented method of automatically creating mates between geometric entities of a computer-aided design (CAD) model of a real-world object and a new part, the method comprising:
number: 2
text: A computer-implemented method as in claim 1 wherein a contextual signature for an entity of a part is a numerical representation of one or more contextual locations of the entity within the part.
number: 3
text: A computer-implemented method as in claim 2 wherein the contextual signature is calculated by computing ratios between a centroid of the entity and planes of a bounding box around the part.
number: 4
text: A computer-implemented method as in claim 1, 2 or 3 wherein:
number: 5
text: A computer-implemented method as in claim 4 wherein dividing CAD model parts into a plurality of clusters includes:
number: 6
text: A computer-implemented method as in claim 4 or 5 wherein training the mateability predictor neural network includes training the mateability predictor neural network with mateability information for the CAD model parts of a cluster having a relatively higher density compared to other clusters, the relatively higher density of the cluster indicating that the parts of the cluster are frequently used in CAD models.
number: 7
text: A computer-implemented method as in claim 4, 5 or 6 wherein training the mateability predictor neural network includes training the mateability predictor neural network with mateability information for all entities of the CAD model parts.
number: 8
text: A computer-implemented method as in any one of claims 4 to 7 wherein training the mateability predictor neural network includes training multiple mateability predictor neural networks, each corresponding to a different mate type.
number: 9
text: A computer-implemented method as in any one of claims 4 to 8 wherein training the mate-type predictor neural network includes training the mate-type predictor neural network with (i) mateable entities of a cluster including frequently-used parts and (ii) all entities of parts with which the frequently-used parts mate.
number: 10
text: A computer-implemented method as in claim 1, 2 or 3 wherein providing the mateability predictor neural network comprises accessing the mateability predictor neural network, and providing the mate-type predictor neural network comprises accessing the mate-type predictor neural network.
number: 11
text: A computer-implemented method as in any one of claims 1 to 10 wherein automatically adding at least one mate includes:
number: 12
text: A computer-aided design (CAD) system comprising:
number: 13
text: A computer program comprising instructions configured for causing a processor to perform the method of any one of claims 1 to 11.
number: 14
text: A data structure configured to be provided in the method of any one of claims 1 to 10 and comprising:
number: 15
text: A computer-readable storage medium having recorded thereon the computer program of claim 13 and/or the data structure of claim 14.
Office action: search_report, dated 2019-05-22
Prior art cited: ref_id: US2013080121A1
ref_type: patent
severity: background
ref_id: US2002107673A1
ref_type: patent
severity: background
ref_id: - WANG E ET AL: "Feature-Based Assembly Mating Reasoning", JOURNAL OF MANUFACTURING SYST, SOCIETY OF MANUFACTURING ENGINEERS, DEARBORN, MI, US, vol. 18, no. 3, 1 January 1999 (1999-01-01), pages 187 - 202, XP004182930, ISSN: 0278-6125
ref_type: npl
severity: background
ref_id: - CHEN C L P ET AL: "AN INTEGRATION OF NEURAL NETWORK AND RULE-BASED SYSTEMS FOR DESIGN AND PLANNING OF MECHANICAL ASSEMBLIES", IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS, IEEE INC. NEW YORK, US, vol. 23, no. 5, 1 September 1993 (1993-09-01), pages 1359 - 1371, XP000417062, ISSN: 0018-9472, DOI: 10.1109/21.260667
ref_type: npl
severity: background
ref_id: US2002107673
ref_type: patent
severity: background
ref_id: US2013080121
ref_type: patent
severity: background
ref_id: - WANG E ET AL, "Feature-Based Assembly Mating Reasoning", JOURNAL OF MANUFACTURING SYST, SOCIETY OF MANUFACTURING ENGINEERS, DEARBORN, MI, US, (19990101), vol. 18, no. 3, ISSN 0278-6125, pages 187 - 202, XP004182930 [A] 1-15 * abstract * * section 3, 4.2 * * the whole document *
ref_type: npl
severity: background
ref_id: - CHEN C L P ET AL, "AN INTEGRATION OF NEURAL NETWORK AND RULE-BASED SYSTEMS FOR DESIGN AND PLANNING OF MECHANICAL ASSEMBLIES", IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS, IEEE INC. NEW YORK, US, (19930901), vol. 23, no. 5, doi:10.1109/21.260667, ISSN 0018-9472, pages 1359 - 1371, XP000417062 [A] 1-15 * the whole document *
ref_type: npl
severity: background
Final disposition: pending (2019-05-22)