KR20230043563A - Workflow-based semantic CAD data conversion method and device therefor - Google Patents

Abstract

According to an embodiment of the present invention, a semantic computer-aided design (CAD) data conversion method comprises the steps of: receiving CAD data; splitting the input CAD data into node units, which are the minimum geometric units; collecting unit information from a database and defining the order of the collected unit information to generate a workflow; combining the divided node units to generate semantic information corresponding to each of the collected unit information; and combining the semantic information according to the order of the corresponding unit information to generate semantic CAD data. According to the present invention, the work efficiency of a user is improved by automatically converting existing 3D CAD data into semantic CAD data which matches a workflow intended by the user.

Description

Workflow-based semantic CAD data conversion method and device therefor}

This specification proposes a semantic CAD (Computer-Aided Design) data conversion method and an apparatus therefor.

Based on the development of CAD technology, 3D CAD drawings have been expanded from 2D drawings to 3D drawings, and are expressed and generated in various formats according to CAD tools/programs produced by various manufacturers.

In the case of such conventional 3D CAD data, various information is included, but it is limited to geometric information, surface finish, tolerance, or product-related information. This limitation of information naturally served as a factor limiting the use of 3D CAD data to the original work at the time of creation. As a result, conventional 3D CAD data has a problem in that it is difficult to actively utilize/apply it for a purpose/task different from its original purpose/task (eg, shape information extraction for application to a digital twin system). That is, there was a problem that it was very difficult and inefficient to apply the existing 3D CAD data to a purpose or task different from the intended purpose/task at the time of creation.

In order to solve this problem, there have been attempts to expand the range of CAD data utilization by linking additional information to 3D CAD data. There was a problem of poor usability.

Accordingly, an object of the present specification is to convert existing 3D CAD data into semantic CAD data that conforms to the user's workflow, thereby solving the above problems and providing CAD data with higher usability and usefulness.

In the semantic computer-aided design (CAD) data conversion method according to an embodiment of the present invention, the step of receiving CAD data; Dividing the input CAD data into nodes, which are the smallest geometrical units; Collecting unit information from a database and defining an order of the collected unit information to create a Work Flow; combining the divided node units to generate semantic information corresponding to each of the collected unit information; and generating semantic CAD data by combining the semantic information in an order of corresponding unit information; can include

According to one embodiment of the present invention, there is an effect that it can be utilized in a form suitable for various work environments and workflows by extending the limits of information expression of existing 3D CAD data.

In addition, according to one embodiment of the present invention, since the existing 3D CAD data is automatically converted into the dynamic CAD data corresponding to the user's intended workflow, the user's work efficiency is greatly improved/improved.

For other effects of the present invention, other effects of the present invention will be described in detail below with reference to the respective drawings and embodiments.

1 is a block diagram of a semantic CAD data conversion device according to an embodiment of the present invention.
2 is a flowchart illustrating a semantic CAD data conversion method of Semantic Binder according to an embodiment of the present invention.
3 is a diagram illustrating a semantic CAD data generation method according to an embodiment of the present invention.
4 is a block diagram of a semantic CAD conversion device according to an embodiment of the present invention.

Since the technology to be described below can have various changes and various embodiments, specific embodiments will be illustrated in the drawings and described in detail. However, this is not intended to limit the technology described below to specific embodiments, and it should be understood to include all modifications, equivalents, or substitutes included in the spirit and scope of the technology described below.

Terms such as first, second, A, B, etc. may be used to describe various elements, but the elements are not limited by the above terms, and are merely used to distinguish one element from another. used only as For example, without departing from the scope of the technology described below, a first element may be referred to as a second element, and similarly, the second element may be referred to as a first element. The terms and/or include any combination of a plurality of related recited items or any of a plurality of related recited items. For example, 'A and/or B' may be interpreted as meaning 'at least one of A or B'. Also, '/' can be interpreted as 'and' or 'or'.

In the terms used in this specification, singular expressions should be understood to include plural expressions unless clearly interpreted differently in context, and terms such as “comprising” refer to the described features, numbers, steps, operations, and components. , parts or combinations thereof, but it should be understood that it does not exclude the possibility of the presence or addition of one or more other features or numbers, step-action components, parts or combinations thereof.

Prior to a detailed description of the drawings, it is to be clarified that the classification of components in the present specification is merely a classification for each main function in charge of each component. That is, two or more components to be described below may be combined into one component, or one component may be divided into two or more for each more subdivided function. In addition, each component to be described below may additionally perform some or all of the functions of other components in addition to its main function, and some of the main functions of each component may be performed by other components. Of course, it may be dedicated and performed by .

In addition, in performing a method or method of operation, each process constituting the method may occur in a different order from the specified order unless a specific order is clearly described in context. That is, each process may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

The present specification relates to a method, apparatus, and system for converting semantic/semantic CAD data/models, and more particularly, reconstructs pre-generated CAD data/models into a structure that can be converted into semantic CAD data/models, It relates to a method, device, and system for constructing/creating a workflow suitable for the user's work by referring to the information of, and then generating semantic CAD data/model by combining/integrating the workflow and the reconstructed CAD data/model. Furthermore, these semantic CAD data/models can be linked with peripheral/external related devices.

In particular, this specification proposes a method of reconstructing/converting existing CAD data/models based on an external government, thereby increasing the quality, usefulness, and flexibility of existing CAD data. The method proposed in this specification is not simply a combination of externally fragmented individual information units, but conventional CAD data/models in that it generates information and semantic connection information for each unit and combines them with a workflow that appropriately reflects the user's requirements. There is a difference between the conversion method and the difference. In addition, according to the embodiment proposed in this specification, semantic information is extracted from the original CAD data/model based on meta data, geometric information, and/or hierarchical structure information, and then processed into a form suitable for business/process purposes. , can be bound with externally generated semantic information and workflow. Through this, it is possible to provide CAD data/models applied with a semantic-based workflow that could not be provided by existing CAD conversion services, as well as existing unprocessed original CAD data/models or unidirectionally connected CAD data/models. Compared to the model, it has a higher work suitability and productivity improvement can be expected.

In this specification, combining semantic information with CAD data/model means that information on how semantic relationships are connected between scattered information fragments is added, and through this, each element of the CAD data/model is accurate and Confusion is eliminated by referencing the appropriate information. These characteristics and effects have a very important meaning because they can be used as a core resource of a system that recommends an intelligent workflow suitable for the user's work/work needs.

1 is a block diagram of a semantic CAD data conversion device according to an embodiment of the present invention.

This block diagram is a block diagram for dividing and explaining the components centering on each function of the semantic CAD data conversion device 100. A plurality of components may be integrated into one component or one component may be separated into a plurality of components. may be

First of all, the semantic CAD data conversion device 100 refers to a device, module, server, application, and/or program in which the method proposed in this specification is implemented, and converts original CAD data into semantic CAD data to suit the user's workflow. We can provide a conversion service.

The semantic CAD data conversion device 100 converts actual work / process / factory / work site (ie, 3D CAD data / model) into a virtual shape, and the user's state received from the external database to the shape Depending on the point of view, it can be displayed in the desired form. Here, 'shape' means shape information or shape properties. For example, 'shape' can be divided into 'geometric shape' for the shape of the polygon set constituting the 3D CAD data/model and 'semantic shape' for the meaning. In addition, the state here means external information, relationship information, state information, etc. received from an external database, and for example, process/work/work process, progress, node, relationship between hierarchies, and interaction A sequence, a combination having a meaning, and the like may correspond to this.

CAD data can be largely classified into a hierarchy such as vertex -> polygon -> mesh -> block -> product. In particular, in the case of a 3D model, a single CAD data/model may be formed by combining geometric shapes and semantic information of each unit shape, group and inter-group hierarchical information according to use, and semantic relationship information of groups. CAD data can be segmented/decomposed to suit the needs and needs of the user. Criteria and conditions for division/disassembly may be predefined in the CAD data itself, or may be added according to requirements of a workflow created/constructed according to an embodiment proposed in this specification. If the minimum divided/decomposed unit is defined as a terminal node, each terminal node may have a semantic attribute (eg, semantic information) or may be assigned a new semantic attribute. Terminal nodes may be grouped according to semantic attributes, and each group may be rearranged in a hierarchical structure. Structural rearrangement between nodes and groups may be determined according to mutual semantic relationships.

The semantic CAD data conversion apparatus 100 proposed in this specification reconstructs by applying semantic technology to CAD data, simultaneously reconstructs external data based on semantic technology, and converts it into one data based on the user's workflow. It is characterized by combining / integrating. More specifically, the semantic CAD data conversion device 100 divides/decomposes the input CAD data into units capable of semantic analysis, and then generates semantic information necessary for the user based on the analysis result with reference to external data. It performs the function of providing/outputting the bound data (i.e., semantic CAD data).

Here, the semantic technology collectively refers to a technology of generating and interconnecting semantic information in a form understandable by a machine, rather than connecting a search word and a search object in a one-to-one correspondence relationship in computer science. Binding also means an operation to define a connection between information/data before processing and generated semantic information so that necessary information can be accessed by making a query based on semantic information according to a user's requirement.

Referring to FIG. 1, the semantic CAD data conversion device 100 largely includes a data input unit 110, a semantic binder 120, and a database unit (or may be referred to as 'TIM Vault') (140 ), and/or the data output unit 130.

The data input unit 110 may correspond to a component that receives original (3D) CAD data, which is an object of conversion into semantic CAD data, and the data output unit 130 receives the converted original (3D) CAD data according to an embodiment of the present invention. It may correspond to a configuration for outputting CAD data, that is, semantic CAD data. The database 140 may correspond to a cloud-based storage space as an external data/information/data storage, and may store various external data/information/data related to a user's work/process/work. The Semantic Binder 120 may process/reconstruct original (3D) CAD data input through the data input unit 110 based on semantic technology and convert them into semantic CAD data.

The work execution procedure of Semantic Binder (120) is largely divided into 1. Exploring semantic units by analyzing CAD data, 2. Analyzing external data and assigning meaning to CAD data, 3. Establishing a workflow. can be divided into

In detail, the Semantic Binder 120 analyzes the structure of the original unprocessed CAD data to determine the hierarchical structure, and then decomposes all geometric elements into node units, which are the minimum units having meaning. Furthermore, the Semantic Binder 120 classifies the decomposed geometric elements by semantic attributes, classifies the same attributes into geometric groups, and reconstructs each classified geometric group into a form capable of semantic analysis. For example, the required model pattern may be different depending on the task. If semantic information is given to each geometric group, the geometric group can be reconstructed and used according to the required model pattern. And/or, the Semantic Binder 120 may decompose the 3D CAD structure into geometric units, store the analyzed information, and then reference/use it as a basis for policy decision.

And/or, Semantic Binder 120 collects unit information such as workflow related data, BOM or meta data after connecting data related to or necessary to original CAD data among data stored in database 140 And, the collected unit information can be reconstructed according to the user's requirements (or input) to create meaningful information according to the workflow.

And/or, the Semantic Binder 120 may create semantic information by combining the divided/decomposed CAD data with unit information collected from the outside and reconstructed. CAD data to which semantic information is assigned (ie, semantic CAD data) may be output in a unique file format or transmitted as an input to the next service step.

CAD data that has been divided/decomposed and analyzed and unit information collected from the outside can be reconstructed by directly generating semantic information by the user, or reconstructed using semantic information generated by machine/AI learning based on the collected learning data. there is.

In order to perform the functions described above, the Semantic Binder 120 can perform four functions, and each function consists of a Shape Divider (120-1), a Shape Analyzer (120-2), and a State Gatherer (120-3). ) and/or Semantic Attacher 120-4.

The Shape Divider 120-1 may perform a function of analyzing the structure of the original CAD data and dividing/decomposing it into predetermined units (eg, a node unit, which is the minimum unit). The Shape Analyzer (120-2) analyzes the units decomposed/divided by the Shape Divider (120-1) and reconstructs them according to the desired policy (and/or workflow, user input, preset policies/rules/patterns, etc.) function can be performed. The State Gatherer 120-3 may perform a function of collecting various business data/information from a database. Semantic Attacher (120-4) can create and bind semantic information based on analyzed CAD data and collected work information. Hereinafter, the function of each component will be described in detail.

The Shape Divider (120-1) is a module that analyzes the original CAD data, identifies the hierarchical structure, and decomposes into the smallest disassembly unit (hereinafter referred to as node unit) having geometrically meaningful information.

Ultimately, the purpose of Shape Divider (120-1) is to decompose/divide original/raw/raw CAD data into shapes/units that can be analyzed/interpreted. More specifically, CAD data is basically data corresponding to a design drawing, and may be composed of an arbitrary number of unit objects having a hierarchical structure, and each unit object has shape and numerical information. In the case of a normal task of referring/using CAD data, additional information other than the information above is not required, so in most file formats, no more detailed information is provided by default. At this time, if relation information between each unit object and the unit object according to the hierarchical structure is analyzed and generated, this can be an important basic data for generating semantic information according to the user's business requirements. Therefore, the Shape Divider 120-1 can perform a function of disassembling/dividing unit objects, which are the basis for generating such important basic data, from CAD data.

The Shape Divider (120-1) can perform the following tasks.

- Check the metadata of the entered CAD data

- Hierarchical structure analysis and segmentation/disassembly by node by layer

- Geometric pattern classification (Mesh Segmentation) by node unit of each layer (here, the geometric pattern is, for example, a standardized polygon primitive (Polygon Primitive), NURBS (Non-Uniform Rational B-Splines), and / or a mesh group, etc.) may be)

- Output classified unit information (or node unit) to Shape Analyzer

The Shape Analyzer (120-2) analyzes the geometric information units (eg, node units) decomposed/divided into morphemes (minimum decomposition units having meaning) in the shape divider (120-1) and reconstructs them into semantic units (i.e., , generating semantic information). After the decomposed/divided unit information is classified by attribute through an analysis process, semantic information can be created by reconstructing it according to a desired policy according to business requirements.

For example, even if other departments try to refer to the CAD model produced by the design department, there is a very high possibility that it will not meet the requirements of the other department, so the Shape Analyzer (120-2) is a unit that refers to the CAD model of the design department. After decomposition/segmentation, semantic information that meets the requirements of other departments can be created by reconstructing to suit the requirements of different departments.

The Semantic Binder (120) converts existing CAD data into a form that can be analyzed and provides a basis for judgment by which users who want to refer to it can determine a shape suitable for the purpose, and the Shape Analyzer (120-2) As a sub-module of ), it is possible to select necessary information from CAD data according to the workflow and to reconstruct and combine it into meaningful information.

The Shape Analyzer (120-2) can perform the following tasks.

- Input shape unit information (i.e., node unit information) and layer information

- Classified geometric units are converted into meshes for pattern analysis (Mesh Classification): Minimum geometric/semantic unit of existing CAD data - Node -> Minimum geometric/semantic unit of converted CAD data - Conversion to mesh group

- Input unit information collected by State Gatherer (120-3)

- Selecting unit information in a form suitable for the workflow according to user needs

- semantic information generation: semantic information generation based on user input, and/or semantic information generation based on machine learning

- Output generated semantic information and selected unit information to Semantic Attacher (120-4)

The State Gatherer (120-3) is a module that connects to the database, collects unit information for generating semantic information of CAD data, and creates a workflow suitable for the user's task/work/process purpose.

Workflow refers to the overall flow of work/work/process procedures in which a series of tasks/tasks/processes are divided into detailed units, and then the units are given an order to proceed step by step. Small unit tasks are given a certain order according to their relationship with other tasks, and only when they are carried out according to the given order, the entire task/work/process can achieve the desired result. Even if it is assumed that there is a work group of the same unit, both the optimal work unit configuration and work order may be different depending on the difference in detailed conditions such as the type of work/purpose and requirements, and semantic information may also be different accordingly. Here, semantic information, that is, meaningful information, refers to the group of work units constituting the workflow and all elements that affect the workflow (eg, organization members, input/output information, software/hardware environment for performing tasks, etc.) and information that encompasses the priorities and work flow of these elements. A set of unit tasks alone is simply a resource and cannot have any meaning, and it can have meaning as a workflow only when the successive relationship and flow/sequence of each unit are defined.

This semantic information may be a concept distinct from semantic information generated by the shape analyzer. More specifically, the semantic information generated by the shape analyzer is information generated based only on the information in the CAD data (particularly, generated by dividing/decomposing the CAD data into specific subunits), whereas the semantic information in the state gatherer is generated from the CAD data. As information generated/collected by referring to external data associated with, it may correspond to unit information.

The State Gatherer (120-3) can perform the following tasks.

- Establish a connection with the location of the necessary information for CAD data within the database

- Creation of workflows (e.g. creation of furniture process procedures to produce furniture)

- Collection of unit information according to the created workflow (for example, in the furniture process procedure, each process step is collected as each unit information)

- A set of unit information collected by Semantic Attacher (120-4) and output of the created workflow

The workflow may be directly generated based on user input, or a previously stored workflow may be referred to and utilized. In the former case, the user can directly create a workflow by inputting in accordance with the format according to the existing WMS. And / or the workflow may be generated based on the result of AI learning the collected unit information.

The Semantic Attacher (120-4) is a module that combines semantic information based on the unit information set generated by the Shape Analyzer (120-2) and the State Gatherer (120-3). The Semantic Attacher (120-4) can bind/combine semantic information into shape information based on the analyzed/decomposed/segmented shape information and the collected state. As a result, raw/original CAD data can be converted into semantic CAD data. Semantic Attacher (120-4) can read previously created semantic information or bind modified semantic information based on collected information. Semantic information can be generated based on a combination of shapes, combinations of states, or combinations of shapes and states.

2 is a flowchart illustrating a semantic CAD data conversion method of Semantic Binder according to an embodiment of the present invention.

Referring to FIG. 2 , first, the semantic CAD data conversion device (particularly, the data input unit) may receive CAD data from a user (S201).

Next, the semantic CAD data conversion device (particularly, the Shape Divider) may divide/decompose the input CAD data into nodes, which are the minimum geometrical units (S202). In particular, the semantic CAD data converter analyzes the hierarchical structure of the input CAD data and divides/decomposes each hierarchy into node units based on the hierarchical structure analysis result. Furthermore, the semantic CAD data conversion device may classify the divided/decomposed node unit into a predetermined geometric pattern. Examples of the preset geometric pattern may include standardized polygon primitives, NURBS (Non-Uniform Rational B-Splines), mesh groups, and the like.

Next, the semantic CAD data conversion device (particularly, the State Gatherer) may generate a workflow by collecting unit information from the database and defining an order of the collected unit information (S203). In particular, the semantic CAD data conversion device can create a workflow with optimal efficiency in consideration of the user's task/work/process purpose and efficiency. To this end, the semantic CAD data converter may create a workflow by defining the order of collected unit information in consideration of the priority of each unit information, work efficiency of the entire workflow, and/or a predetermined process sequence.

For example, if the user's task is a furniture manufacturing process, the semantic CAD data converter can collect each process step entering the furniture manufacturing process as unit information, and the optimal process step to maximize furniture manufacturing efficiency. A workflow can be created by determining/defining the order of

Next, the semantic CAD data conversion device (particularly, the Shape Analyzer) may combine the divided node units to generate semantic information corresponding to each unit information collected in step S203 (S204). In other words, the semantic CAD data conversion device may generate semantic information by combining at least one node unit corresponding to the collected unit information. For example, in a furniture manufacturing process, semantic information corresponding to a process of engraving a design intaglio on the surface of furniture (ie, first unit information) is the minimum geometric element/unit engraved on the surface of the entire furniture design drawing (ie, first unit information). , intaglios (geometric sets/elements/units representing ) node units) may be all combined to generate one semantic information.

There may be various ways to generate this semantic information, but the present specification proposes the following two embodiments. One embodiment proposes a method of generating semantic information based on a user input, and another embodiment proposes a method of generating semantic information based on a result of AI learning pre-generated semantic CAD data.

In the case of the former embodiment, the semantic CAD data conversion device may select a node unit corresponding to the unit information as a combination target based on a user input. For example, the semantic CAD data conversion device may directly input/select a node unit corresponding to a process of engraving a design intaglio on the surface of furniture (ie, first unit information) from the user, and select a node unit based on this. can

In the case of the latter embodiment, the semantic CAD data conversion device AI learns the pre-generated semantic CAD data to learn the entire process, workflow and / or node unit corresponding to each unit information, and node unit corresponding to the unit information The pattern/feature/property of can be extracted. Based on these learning results, the semantic CAD data conversion device can directly/automatically select a node unit corresponding to each unit information of the workflow and select it as a combination target.

The semantic CAD data conversion device may generate semantic information corresponding to each unit information by combining/combining selected node units according to the above-described embodiment.

The semantic CAD data converter may perform a line work of converting a node-based geometric pattern into a mesh group before combining node units. The semantic CAD data conversion device may not perform a conversion operation on a node unit whose geometric pattern is a mesh group. Through such line work, by unifying node units into the same geometric pattern, overall process/work efficiency can be improved.

Next, the semantic CAD data converter may generate semantic CAD data by combining the semantic information according to the order of corresponding unit information (the order defined in the workflow) (S205). This step will be described in detail below with reference to FIG. 3 .

3 is a diagram illustrating a semantic CAD data generation method according to an embodiment of the present invention.

As illustrated in FIG. 3, semantic information may be generated corresponding to unit information corresponding to individual processes/works/tasks, and the generated semantic information is rearranged according to the order of unit information defined in the workflow, thereby It can be converted into semantic CAD data.

The semantic information of the semantic CAD data thus generated can be mutually bound with the corresponding unit information, and upon receipt of a user selection input for specific unit information in the workflow, the semantic information bound to the selected unit information is provided/output to the user. It can be. Through these functions/operations, users can easily access semantic information corresponding to each unit of information in a workflow, so that work efficiency is further improved and the range of CAD data is greatly expanded.

4 is a block diagram of a semantic CAD conversion device according to an embodiment of the present invention.

Referring to FIG. 4 , the semantic CAD converter 100 may include a control unit 410, a memory unit 420, a communication unit 430, and/or a user input unit 440.

The control unit 410 may control at least one component included in the semantic CAD conversion device to perform the embodiment proposed in this specification. The controller 410 may include a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), an application processor (AP), an application processor (AP), and/or any one well known in the art. It may be configured to include at least one type of processor. The controller 410 may perform calculations for at least one application, software, and/or program for executing a method according to embodiments of the present invention.

The memory unit 420 may store various digital data, and in particular, may correspond to a storage space for storing CAD data. The memory unit 420 represents various digital data storage spaces such as a flash memory, a hard disk drive (HDD), a solid state drive (SSD), and a cloud.

The communication unit 430 may transmit/receive data by communicating with an external device/device/server/database using at least one wired/wireless communication protocol.

The user input unit 440 may sense/detect/receive various user inputs to the semantic CAD converter 100 using at least one sensing unit. Here, the at least one sensing means is a gravity sensor, a geomagnetic sensor, a motion sensor, a gyroscope sensor, an acceleration sensor, an infrared sensor, an inclination sensor, a brightness sensor, an altitude sensor, an olfactory sensor, a temperature sensor, and a depth sensor. , a pressure sensor, a bending sensor, an audio sensor, a video sensor, a Global Positioning System (GPS) sensor, a touch sensor, and a grip sensor.

An object of the present invention is to use semantic technology to reconstruct conventional CAD models/data together with/based on external information/data, expand the limits of limited information expression, and convert them into a form suitable for various workflows, thereby enabling more work. To provide a work environment with improved efficiency/suitability.

According to one embodiment of the present invention, semantic information is simply created only with existing raw/original CAD data and/or externally stored data is not linked to raw/original CAD data, but raw/original CAD data and external information/ It is possible to provide a TIM cloud environment that guarantees the suitability of a workflow with improved work efficiency by simultaneously considering data to generate semantic information and performing relational connection and combination.

An embodiment according to the present invention may be implemented by various means, for example, hardware, firmware, software, or a combination thereof. In the case of hardware implementation, one embodiment of the present invention provides one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), FPGAs ( field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, etc.

In addition, in the case of implementation by firmware or software, an embodiment of the present invention is implemented in the form of a module, procedure, function, etc. that performs the functions or operations described above, and is stored on a recording medium readable through various computer means. can be recorded. Here, the recording medium may include program commands, data files, data structures, etc. alone or in combination. Program instructions recorded on the recording medium may be specially designed and configured for the present invention or may be known and usable to those skilled in computer software. For example, recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs (Compact Disk Read Only Memory) and DVDs (Digital Video Disks), floptical It includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, such as a floptical disk, and ROM, RAM, flash memory, and the like. Examples of program instructions may include high-level language codes that can be executed by a computer using an interpreter or the like as well as machine language codes generated by a compiler. These hardware devices may be configured to act as one or more software modules to perform the operations of the present invention, and vice versa.

In addition, an apparatus or terminal according to the present invention may be driven by a command that causes one or more processors to perform the functions and processes described above. For example, such instructions may include interpreted instructions, such as script instructions such as JavaScript or ECMAScript instructions, or executable code or other instructions stored on a computer readable medium. Furthermore, the device according to the present invention may be implemented in a distributed manner over a network, such as a server farm, or may be implemented in a single computer device.

In addition, a computer program (also known as a program, software, software application, script or code) loaded into a device according to the present invention and executing the method according to the present invention includes a compiled or interpreted language or a priori or procedural language. It can be written in any form of programming language, and can be deployed in any form, including stand-alone programs, modules, components, subroutines, or other units suitable for use in a computer environment. A computer program does not necessarily correspond to a file in a file system. A program may be in a single file provided to the requested program, or in multiple interacting files (e.g., one or more modules, subprograms, or files that store portions of code), or parts of files that hold other programs or data. (eg, one or more scripts stored within a markup language document). A computer program may be deployed to be executed on a single computer or multiple computers located at one site or distributed across multiple sites and interconnected by a communication network.

For convenience of explanation, each drawing has been divided and described, but it is also possible to design to implement a new embodiment by merging the embodiments described in each drawing. In addition, the present invention is not limited to the configuration and method of the described embodiments as described above, but the above-described embodiments are configured by selectively combining all or part of each embodiment so that various modifications can be made. It could be.

In addition, although preferred embodiments have been shown and described above, this specification is not limited to the specific embodiments described above, and those skilled in the art in the art to which the specification pertains without departing from the subject matter claimed in the claims Of course, various modifications are possible by the person, and these modifications should not be individually understood from the technical spirit or perspective of the present specification.

Claims (8)

In the semantic CAD (Computer-Aided Design) data conversion method,
Receiving CAD data;
Dividing the input CAD data into nodes, which are the smallest geometrical units;
Collecting unit information from a database and defining an order of the collected unit information to create a Work Flow;
combining the divided node units to generate semantic information corresponding to each of the collected unit information; and
generating semantic CAD data by combining the semantic information in an order of corresponding unit information; Including, semantic CAD data conversion method. According to claim 1,
The step of dividing into nodes,
Analyzing the hierarchical structure of the input CAD data;
Dividing each layer into nodes based on a result of analyzing the layer structure;
classifying the divided geometric patterns in units of nodes; Including, semantic CAD data conversion method. According to claim 2,
The geometric pattern,
A semantic CAD data conversion method corresponding to at least one of a standardized polygon primitive (Polygon Primitive), NURBS (Non-Uniform Rational B-Splines), and a mesh group. According to claim 2,
In the step of generating the semantic information, before combining the node units,
converting the node-based geometric pattern into a mesh group; and
selecting, among the node units, a node unit corresponding to the unit information as a combination target; Including, semantic CAD data conversion method. According to claim 4,
In the step of selecting the node unit as a combination target,
A method for converting semantic CAD data, which is performed based on user input or based on a result of AI (Artificial Intelligence) learning of pre-generated semantic CAD data. According to claim 1,
binding unit information and semantic information corresponding to each other; Further comprising, semantic CAD data conversion method. According to claim 6,
outputting the workflow;
Receiving a selection input for at least one piece of unit information included in the workflow; and
outputting semantic information bound to the selected unit information; Including, semantic CAD data conversion method. According to claim 1,
The step of creating the workflow is,
A step of generating the workflow by defining the order of the collected unit information based on at least one of a priority for each unit information, work efficiency of the entire workflow, and a predetermined process order, wherein the semantic CAD data conversion method.

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