54 results about "Computer-aided manufacturing" patented technology

The invention relates to the technical field of computer-aided manufacturing, and provides a staged processing real-time cutting simulation method and system.The method comprises the steps that S1, initialization modeling is conducted, specifically, a blank voxel grid model, a tool body voxel grid and a triangular grid are built; s2, performing a first simulation stage of low-precision real-time cutting dominated by voxel grids, judging a space overlapping relationship between the tool body voxel grids and the blank voxel grids in real time so as to determine a voxel region to be removed, and deleting blank voxels in the overlapping region through Boolean operation; s3, in the execution process of the first simulation stage, monitoring a preset multi-dimensional switching trigger condition in real time, and when any condition or a combination of multiple conditions is met, entering a second simulation stage; and S4, a second simulation stage of high-precision real-time cutting with the triangular network as the dominant is carried out, the voxel grid intermediate workpiece is converted into a transition triangular grid, and high-precision cutting calculation is carried out based on the triangular grid. And the efficiency-precision contradiction is broken through through a staged strategy.

The invention discloses a special-shaped pipe forming compensation method and system based on digital twinning, and belongs to the technical field of computer-aided manufacturing and intelligent control. The method comprises the steps that multi-source sensing data in the special-shaped pipe forming process is obtained, and time-space fusion processing is executed; generating a time-space aligned multi-source sensing data set, carrying out dynamic calibration on the parameterized virtual digital twin, generating a calibrated virtual digital twin, carrying out simulation calculation on the forming process of the special pipe in a future time window, outputting predicted deviation data, and combining with a preset compensation strategy to generate a compensation instruction through logical judgment and calculation; and obtaining an adjustment result after the compensation instruction is applied, and updating the compensation strategy by using a reinforcement learning algorithm. According to the method, prospective simulation prediction is carried out by constructing the dynamically calibrated virtual digital twins, closed-loop optimization is carried out on a compensation strategy by utilizing a reinforcement learning algorithm, and active, high-precision and self-adaptive compensation control on the special pipe forming process can be realized.

The invention belongs to the field of computer-aided manufacturing, and provides an interactive 3D printing control system and method based on multidimensional data, and the method comprises the steps: collecting multidimensional disturbance data in real time in a printing environment; performing multi-dimensional coupling on the disturbance data, the forming platform attitude data, the printing nozzle feeding speed data and the curing energy distribution data, and constructing a joint disturbance prediction model; outputting a printing parameter compensation instruction based on the joint disturbance prediction model; meanwhile, a visual interaction interface allows an operator to carry out manual auxiliary intervention based on real-time displayed airflow disturbance three-dimensional field distribution; and receiving the compensation instruction, driving a corresponding execution mechanism which comprises a nozzle micro driver, a platform piezoelectric regulator and a light source array controller, and collecting new disturbance feedback data after compensation execution.

The invention relates to the field of numerical control machining and computer-aided manufacturing software, and particularly discloses a honeycomb core six-axis ultrasonic cutting track digital control and interpolation optimization system which comprises a track preprocessing module, a parameterized spline interpolation module, a six-axis linkage inverse solution module, a dynamic feed-forward compensation module, an ultrasonic energy adaptive control module and a multi-source information fusion and decision module. By the adoption of the technical scheme, smooth and efficient interpolation of a track, dynamic feed-forward compensation of motion errors and self-adaptive adjustment of cutting energy can be achieved, and therefore the machining precision, the surface quality and the system stability are improved. According to the invention, ultrasonic energy control is originally incorporated into an overall trajectory control closed loop, and real-time accurate regulation and control of cutting energy are realized through the ultrasonic energy adaptive control module. The module is based on force, amplitude, temperature and other multi-sensor information, adopts fuzzy reasoning to intelligently decide output power, and ensures that cutting energy is constant and optimal under different processing conditions.

The invention discloses a process planning model pre-training method and system based on multi-processing scene segmented imitation learning, and relates to the field of computer-aided manufacturing, comprising the steps of: for various processing scenes comprising different geometric features, material characteristics and processing requirements, generating processing paths of various strategies by using a mature process database of CAM software; virtual trial cutting is carried out through a processing process world model to generate a large number of initial states, rich and diversified training samples are provided for reinforcement learning pre-training, and on the basis, large-scale pre-training is carried out by adopting a segmented behavior cloning method to obtain a process autonomous planning base agent which learns processing strategies in different processing scenes; in the face of a new processing task, a processing path can be quickly generated through transfer learning. According to the method, the generalization ability is remarkably improved, meanwhile, geometric-physical-control collaborative planning is achieved, and an intelligent solution is provided for efficient planning of the modern manufacturing industry technology.

The invention relates to the technical field of computer-aided manufacturing, in particular to a three-dimensional model hole feature recognition method, device and equipment based on B-Rep topology and a computer program product. The method comprises the steps that firstly, an inner ring of the outer surface of a three-dimensional model is obtained, concavity-convexity detection of edges is conducted according to geometrical features of in-plane holes, and the inner ring of the outer surface of the three-dimensional model is obtained; further performing ray method detection on the fillet edge so as to identify the in-plane hole according to the concavity and convexity of the edge and the side surface; and acquiring an outer ring of the outer surface of the three-dimensional model, performing path search according to the geometric feature constraint of the boundary hole to obtain a closed wireframe, and checking whether the closed wireframe meets the geometric feature constraint of the boundary hole again to identify a non-rounded edge hole and a rounded edge hole. According to the method, the in-plane holes and the boundary holes of the three-dimensional model are recognized directly based on the B-Rep topology, computing resources and cost are saved, the process adaptability is high, and the method is suitable for high-precision manufacturing scenes.

The invention relates to the technical field of computer-aided manufacturing, in particular to a cartoon production management system and method based on a cloud platform, and the system comprises a production task definition module which is used for decomposing a project into independent production units based on project production requirements, associating a corresponding digital asset type and a preset evaluation dimension set for each unit, and generating a production task; and combining with personnel and schedule information to establish a structured asset making task set. According to the method, the manufacturing project is disassembled, the project is decomposed into the independent manufacturing units, and the specific digital asset type is associated with the evaluation dimension set, so that a clear and structured manufacturing task relationship is established, and subsequent scoring and auditing operations can be accurately carried out aiming at the specific dimension and the asset type; and the pertinence of task execution and feedback is improved.

Systems and methods are provided for scanning a dental impression to obtain a digital model of a patient's dentition as an input to computer aided design (CAD) and computer aided manufacturing (CAM) methods for producing dental prostheses. Systems and methods are provided for scanning a physical impression of a patient's dentition and constructing a virtual surface image of the patient's dentition from the scan data thereby obtained. The virtual surface image of the patient's dentition is constructed using isosurfaces and density gradients of a volumetric image and then directly creating a surface image based upon void spaces that correspond to the patient's dentition.

The application relates to the technical field of circuit board production, in particular to a kind of impedance line width measuring method and computer readable storage medium.The measuring method comprises S1, the impedance information of impedance line to be measured is obtained by pre-manufacturing auxiliary manufacturing automation equipment;S2, the impedance information on pre-manufacturing auxiliary manufacturing automation equipment is obtained by computer aided manufacturing software through automation script, and the automatic line width measuring instrument program is automatically generated according to the impedance information;S3, the actual value of impedance line width on the circuit board is measured according to the automatic line width measuring instrument program;S4, the impedance line width standard value generated by the automatic line width measuring instrument program and the actual value of impedance line width measured by the production equipment are generated into a report, and whether the impedance line width of the impedance circuit board meets the requirements is judged according to the comparison value, the impedance line width measuring method can directly and accurately measure the actual value of impedance line width on the circuit board, which is beneficial to improve the production quality of the circuit board and also beneficial to improve the precision of the circuit board.

Disclosed are example embodiments of methods and systems for automatically coloring a dental prosthesis. One of the systems includes: a memory configured to store a computer-aided manufacturing (CAM) file of the dental prosthesis; a holding apparatus for securing the dental prosthesis; one or more outlets for dispensing coloring fluid; an coloring fluid controller configured to control the one or more outlets to dispense coloring fluid at a preset size and frequency based at least on the CAM file; and a motion controller configured to move the holding apparatus or the one or more outlets based at least on the CAM file.

The invention relates to a computer-aided manufacturing process (10) for producing workpieces (12, 12a, 12b, 14, 16) by means of several workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) defined in manufacturing orders (18, 18a-c) from several workpiece blanks (26) with a manufacturing system (28) comprising the process steps: a) Forming (30) a processing queue (32) by separating the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) contained in the production orders (18, 18a-c) by assigning an order affiliation; b) Creating (36) a cross-order production plan (38) by positioning at least some of the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) provided in the processing stock (32) on one or more workpiece blanks (26); c) Establishing (40) a partial production plan (42a-d) of the production plan (38), wherein the partial production plan (42a-d) provides for the production of the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) positioned on a single workpiece blank (26), wherein the establishment is carried out taking into account a occupancy level of the workpiece blank (26); d) Manufacturing (44) the workpieces (12, 12a, 12b, 14, 16) according to the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) of the part production plan (42a-d). The invention also relates to a manufacturing system (28).

The present application belongs to the field of computer aided design and computer aided manufacturing system, and relates to a CAD model simplification and repair method based on intelligent decision: firstly, a user imports an original CAD entity model through an interactive interface in a CAD system; then, the system detects redundant topological information existing in the CAD entity model, including redundant points, edges and surfaces; then, an optimal cleaning sequence is generated by using a reinforcement learning method for all the detected redundant topological problems; then, two geometric surfaces that need to be merged are merged in the process of removing the redundant topologies in sequence; finally, the merged topologies are updated on the whole model. The method can solve the problems of strong cleaning sequence dependency and large geometric distortion in traditional geometric simplification, and ensure the manifold and topological correctness of the final model after simplification, and is applied to subsequent mesh generation and precision manufacturing.

The invention discloses a material removal process replay and cutting force parallel simulation method based on an operation log, and belongs to the technical field of machining and computer-aided manufacturing. The method comprises the following steps: initializing a three-dimensional operation log system and allocating storage space according to the total number of numerical control machining steps and preset entry capacity; recording material removal operation parameters of the grid units according to a preset interval in the material removal process to form an operation record chain; corresponding entries are positioned through log indexes, reverse material removal operation is executed, and a precise target historical state is obtained through topology verification; calculating local cutting force based on the sub-domain data and summarizing to generate a global cutting force curve; according to the method provided by the invention, only key operation parameters are recorded, storage resources are dynamically allocated, and storage overhead is reduced; efficient and accurate state backtracking of any step is achieved through log indexing and reverse operation, the cutting force simulation efficiency is improved in combination with parallel computing, and the problems that a traditional method is heavy in storage burden, slow in backtracking and low in simulation efficiency are solved.

The invention provides a personalized ornament generative design method based on cultural label vectors. The method comprises the following steps: constructing design parameter vectors including materials, colors, shapes, quality, processes, combinations and wearing positions; constructing a quantitative mapping relation function of the material, color, shape, quality, process and culture label vectors, and correcting through combination and wearing positions to obtain a final culture label prediction vector; taking the difference between a set five-element discrete classification vector preference target value and a final prediction vector as a label error term, and constructing a differentiable target function in combination with cost constraint, work efficiency penalty and label overflow penalty; and performing optimization solution on the target function to obtain an optimal design parameter vector, and generating a corresponding ornament digital model design scheme based on the optimal design parameter vector. Technical coupling of numeralization mapping of traditional cultural symbols and computer-aided manufacturing is realized, and an algorithm framework which can be industrially realized is provided for large-scale personalized ornament customization.

The present disclosure provides an automatic tool selection method and system for a blade disc flow channel, and relates to the technical field of computer-aided manufacturing. The method comprises the following steps: based on a three-dimensional geometric model corresponding to the blade disc, determining a hub spline curve and a casing spline curve corresponding to the flow channel, and performing parameterization processing on the two to obtain initial parameters; based on the initial parameters, performing iterative calculation on each hub feature point to obtain a depth range corresponding to the flow channel; based on the three-dimensional geometric model, determining a suction surface curve and a pressure surface curve corresponding to the flow channel; traversing each feature point in the suction surface curve, determining the nearest feature point corresponding to each feature point from the pressure surface curve based on an iterative search algorithm, and based on each feature point and the corresponding nearest feature point, determining a width range corresponding to the flow channel; and based on the depth range and the width range, determining a target tool corresponding to the flow channel. Through the above method, the machining precision and efficiency of the flow channel are improved.

The invention discloses a model optimization method and system for polishing processing path planning, and relates to the technical field of computer aided manufacturing system model processing, and the method comprises the steps: obtaining and standardizing topological data of a two-dimensional model; automatically separating the contour from the axis based on the endpoint distance and a tolerance threshold; detecting and cutting repeated edge geometry in the contour; according to the space relation between the contour and the axis, non-machining areas are removed, and a machinable contour is extracted; and reconstructing the machinable contour into a three-dimensional model through a rotation algorithm. According to the method, the whole-course automation of model preprocessing is realized, the data processing efficiency and the objective stability of the result are remarkably improved, and a clean and high-quality geometric model basis is provided for a subsequent CAM system to generate an accurate and reliable polishing processing path.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing instructions for printing of 3D objects. One of the methods includes obtaining i) information regarding one or more geometric features of a 3D model of an object to be printed by an extrusion-based 3D printer and ii) process parameters for use in printing; generating, by the computer-aided manufacturing environment, print instructions for the printing of the 3D object by the extrusion-based 3D printer in a series of multiple layers, wherein modified process parameters are generated as part of the print instructions by modifying the obtained process parameters for a proper subset of layers based on the information regarding the one or more geometric features of the 3D model of the object; and providing, by the computer-aided manufacturing environment, the print instructions comprising the modified process parameters to operate the extrusion-based 3D printer to print the object.

This invention provides an information processing method and information processing device that can automatically determine the processing process, the tools to be used, and the processing conditions in computer-aided manufacturing. [Solution] The information processing method performed by the computer includes the steps of: acquiring overall machining shape data that shows the overall machining shape of the workpiece; dividing the overall machining shape data into a plurality of partial machining shape data, each showing the machining shape of a different part of the workpiece; determining the machining type for each partial machining shape data based on the machining shape of each partial machining shape data; and referring to a first database that stores actual information including actual machining shape data, actual machining process data, actual tool used data, and actual machining condition data, determining a first machining process, a first tool used, and first machining conditions according to the machining type for each part from the plurality of partial machining shape data.

The invention relates to a method for manufacturing components (5) layer by layer on a building platform (3) by local solidification of powdered material (9) in each layer (S) by means of at least one energy beam (8a, 8b), comprising the following steps: providing geometry data containing information about the geometry of individual layers (S) of the component (5) that is to be additively produced; and defining an irradiation pattern for the layers (S) by a computer-assisted manufacturing method, wherein: the irradiation pattern comprises, for each layer, a contour region (K) and an extensive region (F) preferably lying inside the contour region (K); the contour region (K) of each layer (S) consists of multiple irradiation vectors (V) lying next to one another; and the vectors (V) lying next to one another in the contour region (K) are exposed with different energy input parameters, such as line energy, energy output, exposure speed, energy beam diameter, power density and / or distance from the adjacent vector (V) in the contour region (K).

The invention provides an AI digital lens generation method and system based on a 3D eyeball digital model. The method comprises the following steps: acquiring original parameter data of a to-be-detected eyeball by utilizing multi-modal scanning; constructing a 3D eyeball digital model by using the original parameter data, inputting the 3D eyeball digital model into a pre-trained joint network, and extracting eyeball refraction parameters and an eight-order Zernike high-order aberration coefficient; inputting a collaborative design model of a generative adversarial network GAN and a multi-target non-sorting genetic algorithm NSGA-II by taking the eyeball refraction parameter and the high-order aberration coefficient as generative conditions, and determining an optimal lens free-form surface height map; and based on the optimal lens free-form surface height map, digital lens production is controlled through computer-aided manufacturing (CAM), and virtual try-on verification is performed in combination with an augmented reality (AR) technology. The technical problems that traditional refraction correction precision is insufficient and high-order aberration cannot be effectively compensated are fundamentally solved.

An ankle-foot orthosis having a foot plate defining a foot bed contoured to underlie the foot of the wearer, a flexible cuff configured to wrap around at least a portion of the shank of the wearer, and a strut assembly comprising a plurality of metal wires connecting the foot plate to the cuff. The plurality of metal wires may include piano wires. The foot plate may be fabricated with a computer aided manufacturing process.

The invention relates to a computer-aided manufacturing process (10) for manufacturing workpieces (12) on machine tools (14) with a numerical control (16), comprising the following process steps: a) Providing (20) a production order (22) for the production of several workpieces (12), wherein the production order (22) is designed as a numerical control program (18); b) Creating (26) manufacturing geometries (28; 28a, 28b) for the workpieces to be manufactured (12) from the manufacturing order (22) by evaluating the numerical control program (18); c) Creating (34) a geometry plan (36) for the manufacturing order (22) by determining relative positions between the manufacturing geometries (28; 28a, 28b); f) Identifying (50) and outputting manufacturing-related error sources (52) by evaluating the geometry plan (36).

The application discloses a tool holder matching determination method, device, equipment and medium. The method comprises the following steps: acquiring a cutting depth of machining a workpiece and a corresponding first tool holder, wherein the first tool holder is a tool holder simulated in programming in computer-aided manufacturing; acquiring the length of the probe-in part of a second tool holder according to the probe-in part of the first tool holder, wherein the second tool holder is a tool holder actually used in a computer numerical control machine tool, the probe-in part of the first tool holder is a part that can be probed into the workpiece, and the length of the probe-in part of the second tool holder is the length of a part that can be probed into the workpiece; and in the case that the sum of the length of the probe-in part of the second tool holder and the overhang length of the tool clamping part is greater than the cutting depth, it is determined that the second tool holder matches the first tool holder.

A method of generating a control sequence for a computer aided manufacturing (CAM) facility comprises storing geometry specifications of previous parts together with a dataset of a computer aided man

A method for computer aided manufacturing of an item, comprising: receiving a project setup and a current state of a manufacturing process for the item, the current state comprising a representation of a workpiece and an operation tree; selecting, for each candidate option, a working tool, additional parameters and computing a toolpath force for a toolpath associated with the candidate option; computing, for each candidate option of a subsequent step of manufacturing the item, a score using a scoring function, wherein an input to the scoring function comprises a simulation of an operation corresponding to the candidate option; performing a simulation based on the selected working tool and the computed toolpath force; selecting a sequence of manufacturing operations and corresponding working tools to manufacture the item; generating machine-executable instructions configured to cause a manufacturing machine to perform the selected sequence of manufacturing operation.

The invention belongs to the field of computer aided design and computer aided manufacturing systems, and relates to an intelligent decision-making CAD model simplification and repair method which comprises the following steps: firstly, a user imports an original CAD entity model in a CAD system through an interactive interface of the user; then, the system detects redundant topological information existing in the CAD entity model, and the redundant topological information comprises redundant points, edges and surfaces; a reinforcement learning method is used for all the detected redundant topology problems, and an optimal cleaning sequence is generated; combining the two geometric surfaces needing to be combined in the process of removing the redundant topology according to the sequence; and finally, the merged topology is updated on the whole model. By means of the method, the problems that in traditional geometric simplification, cleaning sequence dependency is high, and geometric distortion is large can be solved, it is ensured that after the CAD model is simplified, the manifold performance and topological correctness of the final model are guaranteed, and the method is applied to subsequent grid division and precision manufacturing.

The invention belongs to the technical field of medical instruments and computer-aided manufacturing, and provides a surgical navigation template based on an integrated engine and an automatic generation method and application of the surgical navigation template based on the integrated engine. Synchronous extraction and fusion modeling are carried out on a structure set contour and a preset channel center line through an integrated modeling engine, and a final three-dimensional entity is integrally generated through one-time Boolean subtraction operation; finally, the three-dimensional entity meets the following double geometric constraints: dissecting a fitting constraint; and function-oriented constraint. According to the method, end-to-end full-automatic conversion from a radiotherapy plan to a physical guide plate can be realized, so that errors caused by dependence on CT secondary segmentation and artificial modeling in a traditional method are avoided, and the surgical precision, efficiency and the consistency with an original plan are remarkably improved.

Methods, systems, and apparatus, including media encoded computer program products, for computer-aided design and manufacturing of physical structures using tool paths generated through reinforcement learning for use with subtractive manufacturing systems and techniques, including: obtaining a three-dimensional model of a manufacturable object in a computer-aided design or manufacturing program; generating a tool path that can be used by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three-dimensional model to a machine learning algorithm employing reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards related to desired tool path characteristics including tool path smoothness, tool path length, and avoidance of collisions with the three-dimensional model; and providing the tool path to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.

This application proposes a 3D model feature recognition method based on heterogeneous graph neural networks, belonging to the field of computer-aided manufacturing technology. The method includes the following steps: selecting a 3D model database with feature labels; sequentially acquiring the topology set, geometric information set, and normalized geometric information set for each 3D model, and extracting geometric features from each normalized geometric information set to obtain the corresponding geometric mapping feature set; constructing an initial heterogeneous graph neural network; using all geometric mapping feature sets, dividing the data of all 3D models in the 3D model database into training, validation, and test sets, and sequentially training, validating, and testing the initial heterogeneous graph neural network to obtain the final heterogeneous graph neural network; and using the final heterogeneous graph neural network to perform feature recognition on the 3D model. This application can effectively improve the feature recognition capability and accuracy of complex 3D models.