WO2023054806A1 - Process-based convergence surface processing method, program, and platform - Google Patents

Abstract

The present invention provides a process-based convergence surface processing method comprising: a process input step for inputting a value of a process design for processing a surface of a material; a modeling step for modeling a surface shape of the material via data according to the process design; and a step for analyzing and outputting a surface function value indicating functionality of the surface of the material according to the modeling, thereby reproducing, in a virtual space, a result according to the process design via a process-based convergence design technique and verifying same to quickly determine manufacturability (producibility).

Description

Process-based fusion/composite surface processing method, program and platform

The present invention designs a new high-efficiency functional surface as AI technology by designing a new high-efficiency functional surface, selecting materials and It is a process-based fusion/composite surface processing method, program, and platform technology that can automatically or semi-automatically derive technical elements and processes for production.

The existing functional surface manufacturing process is a design-based manufacturing method in which pre-design is followed by post-production. In other words, 3D design based on research information based on natural simulation or the performance of released products, and through industry-specific analysis and simulation, find a technology that can produce a verified model with a target shape and performance approximation, design and manufacture the process. However, this conventional method is a process in which design and manufacturing are separated, and there is a difficulty in that design and analysis must be performed for each surface shape, and the manufacturing process must be redesigned for each process. This leads to a waste of time and material resources and results in an increase in production cost.

In addition, functional surface development (interpretation) and manufacturing processes are specialized for each industry, but there is a problem in that the diversity of product development is low because they are developed only in similar industries.

In order to solve the above problems, the present invention aims to provide a process-based convergence/composite surface processing method that can quickly determine whether or not to manufacture by reproducing and verifying in virtual space through modeling and analysis through process design. there is

In addition, a process-based convergence/complex surface processing method that can design new high-efficiency functional surfaces as AI technology by converting information on functional surfaces into big data and automatically or semi-automatically derive technical elements and processes for material selection and production We want to provide that purpose.

In order to solve the above problems, the present invention includes a process input step of inputting process design values for material surface processing; A modeling step of modeling the surface shape of the material by data according to the process design; It provides a process-based convergence/composite surface processing method comprising the step of interpreting and outputting the surface function value representing the functionality of the surface of the material according to the modeling.

In the process input step, the process design value is characterized in that the output of the AI program by inputting the desired surface function value based on the surface function value big data.

In the step of analyzing and outputting the surface function value, the surface function value is terminated if the surface function value is within the error range of the set desired surface function value, and if the surface function value exceeds the error range of the set desired surface function value It is characterized in that the process design value is changed by correcting by the learned AI program.

In the step of interpreting and outputting the surface function value, the AI program outputs a process design value based on the surface function value data.

In the step of interpreting and outputting the surface function value, if the surface function value is within the error range of the desired surface function value set, the process design value and surface function value data output when the end is completed are relearned by the AI program. characterized by

The process design value is characterized in that it is input by setting the type of equipment for surface processing, processing conditions, and processing order.

The device for surface processing is characterized in that at least one of a waveform-based processing device, a rotating body-based processing device, a wave-and-rotating body-based processing device, a particle-based processing device, and an electromagnetic-based processing device.

In the case of a vibration cutting machine among the devices for surface processing, it is characterized in that a vibration waveform is reflected.

The surface functional value is characterized in that one or more of the mechanical, physical, and chemical properties of the material are numerically expressed.

The surface functional value is characterized in that any one of optical, energy, water repellency, sunlight, hydrophobicity, antiviral, parent cell, hydrodynamics, and tribology is data.

In the step of analyzing and outputting the surface function value, it is characterized in that the type and material of the material are set and input.

The AI program is characterized in that the big data is learned as surface function values and process design values based on research information, industry information, and processing error information.

According to the above solution, the following effects can be expected.

With process-based convergence and complex design techniques, it is possible to quickly determine whether or not to manufacture (production) by reproducing and verifying the results of process design in virtual space.

By setting various manufacturing technologies and inputting processing conditions and environmental data for each process, the result can be output as 2D and 3D data through calculation, and the suitability of the design can be checked through simulation.

When designing a functional surface, it can be designed based on the fusion/composite process, and various attempts according to the manufacturing process can be obtained in advance through process design in virtual space.

Process-based convergence design and manufacturing techniques can be output using Big Data and AI, and AI can derive from shape design to analysis and manufacturing processes.

Design values worked by humans can be verified, corrected and supplemented by AI technology, and design and process corrections or new models can be automatically created.

By storing information and performance of actually manufactured products in Big Data, AI can compare and analyze design values and actual results and automatically calculate error rates and correction values.

1 is a flow chart of a process-based fusion/composite surface processing method according to an embodiment of the present invention.

Figure 2 is a flow chart using the AI program of the process-based convergence and composite surface processing method according to an embodiment of the present invention.

Figure 3 is a detailed flow chart of the AI program of the process-based convergence and composite surface processing method according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. Since the bar shown in the following description and accompanying drawings is presented for a general understanding of the present invention, the technical scope of the present invention is not limited thereto. In addition, detailed descriptions of well-known configurations and functions that may unnecessarily obscure the gist of the present invention will be omitted.

1 is a flow chart of a process-based fusion/composite surface processing method according to an embodiment of the present invention.

Referring to FIG. 1, the present invention largely includes a process input step of inputting process design values for material surface processing, a modeling step of modeling the surface shape of the material by data according to the process design, and It is characterized in that the surface function value is output based on the process design through the step of analyzing and outputting the surface function value representing the functionality of the material surface.

First, the process input step is a step of designing a process for processing the surface of a material.

Process design can be designed with a program tool, and process design for material processing can be performed because the type of equipment, processing conditions according to the type of equipment, processing sequence, etc. are programmed into setting modes and steps.

Here, the process design value can be input by selecting the type of equipment for material surface processing, processing conditions, and processing sequence settings, and it is necessary to verify the data through calculation and processing.

Any device for processing the surface can be used as long as it is for processing the surface of the material, and if classified, it is a waveform-based processing device, a rotating body-based processing device, a wave-and-rotating body-based processing device, a particle-based processing device, and an electromagnetic-based processing device. device as an example.

Specifically, the waveform-based processing machine can perform a machining process using vibration, which is a waveform, and examples thereof include a vibration cutting machine, a slow tool servo (STS), a fast tool servo (FTS), and a shaping machine.

A rotating body-based processing machine can perform a machining process using a spindle, which is a rotating body, and examples thereof include milling, turning, and CNC.

Wave and rotating body-based processing machines can perform processing using ultrasonic (vibration) spindles, and examples include milling, turning, CNC, polishing machines, and grinding machines.

Particle-based processing equipment is a processing process using particle injection, and examples thereof include a grinder, a grinding machine, an abrasive air jet (AAJ), and an abrasive water jet (AWJ).

Electromagnetic-based processing equipment is capable of processing processes using electronic devices, such as ion beam, electric discharge machining, and laser processing.

Process design can be used by inputting one of the above devices, and various types of surface patterns can be designed through setting input of complex device mode that uses various devices in combination according to the purpose, functionality, complexity and specificity of the surface shape. can

In the case of the FTS among the above surface processing devices, processing conditions may be set by channel, tool design, and waveform design. The channel can be set in a structure (single-axis, multi-axis) and layer structure (single-layer, multi-layer, layered), and the tool design can be set in the shape of a machining tool, such as a triangle, square, curve, or circle, and the waveform design can be set in the waveform mode. , waveform type, frequency, displacement, period, etc. can be set and designed.

In the case of a laser among the devices for surface processing, the type, size, distance adjustment, etc. of the laser can be set, and the type of tool path capable of irradiating the laser can be set.

In the case of an AAJ (Abrasive Air Jet) among the surface processing devices, the type of particle, the shape of the particle, the size of the particle, etc. can be set, the amount of sprayed particles can be set, and the spray pressure or speed can be set. can

The modeling step is expressed as 2D and 3D images by a program that graphically expresses the shape of the material by process design, so that the surface shape can be confirmed, and the designed model is divided into embossed and intaglio to automatically generate and data can be output.

In the step of analyzing and outputting the surface functional value, the functional value desired by the user for the surface of the material that has undergone process design and modeling is expressed numerically and can be achieved by an analysis program.

The surface functional value allows one or more of mechanical, physical, and chemical properties of the surface of a material to be expressed. Specifically, the surface function value allows the user to add or change a mode for any one of the characteristics of optics, energy, water repellency, sunlight, hydrophobicity, antiviral, cell-friendly, hydrodynamics, and tribology by user setting, so that the numerical values for each characteristic It can be expressed as and is preferably set in the analysis result module.

In detail, optical properties include transmittance, reflectance, and refractive index, and solar properties include light concentration and energy efficiency. Antiviral properties include antiviral values, fluid dynamics include lubrication coefficient, and tribology can be output with friction coefficient and surface tension.

In the step of analyzing and outputting the surface function value, surface function values according to information on the material can be derived through a setting mode that reflects the type of material and physical, mechanical, physical, and chemical characteristics of the material before running the analysis program. .

As such, it has the advantage of being able to quickly determine whether or not to manufacture by reproducing and verifying the result of the process design in virtual space through modeling and analysis. In addition, by setting various manufacturing technologies and inputting processing conditions and environmental data for each process, the result is output as 2D or 3D data through calculation, and the suitability of the design can be checked through simulation. In addition, when designing a functional surface, it can be designed based on the convergence/composite process, and various attempts according to the manufacturing process can be obtained in advance through process design in virtual space.

On the other hand, in the process-based convergence/composite surface processing method of the present invention, an AI program can be used.

Figure 2 is a flow chart using the AI program of the process-based convergence and composite surface processing method according to an embodiment of the present invention.

Referring to FIG. 2, a process input step of inputting process design values for material surface processing, a modeling step of modeling the surface shape of the material by data based on the process design, and surface function values according to the modeling The step of interpreting and outputting is the same as described above, and in the process input step, the process design value can be derived using an AI program.

Here, the AI program is characterized by outputting a process design value by inputting a desired surface function value based on surface function value big data, so that the process design value can be reflected in the process input step.

On the other hand, the AI program can learn AI by storing the shape and material information of the functional surface announced by industry and research field and the result thereof. By setting categories for each industry and research field, linking material information to the input shape information, and inputting performance information, AI learning can be performed on how performance changes according to shape and material.

For example, it is possible to learn manufacturing methods and techniques according to the shape and material of the process information, and to learn the machining error of the product compared to the design.

In addition, reverse engineering capability can be secured by identifying and learning the characteristics of surface shapes that can be implemented for each process.

For the surface shape information, if you input the 2D image included in the thesis, it is converted into a 3D shape through AI and stored, and the measurement information of products in the industry is stored. It can be used as correction information.

For example, regarding shape information, dimensions in design shapes or drawings can be converted by analyzing dimension lines and created dimensions, and in measurement photos, they can be converted by analyzing scale bars and contrast. 3D shapes can be reverse engineered. And for the product, 3D shape information of the actual product can be obtained through 3D measurement.

Regarding material information, information on transparency is obtained in optics, which shows the characteristics of each industry under the physical properties of the material, and information on surface tension and viscoelasticity is obtained in tribology.

In performance information, you can learn by inputting performance information by industry and research field. In optics, information such as transmittance, reflectance, and refractive index is obtained; in sunlight, information such as light collection rate and energy efficiency is obtained; in hydrophobicity, information on wetting angle; in antivirus, information on antiviral values; In fluid dynamics, lubrication coefficient information can be obtained, and in tribology, friction coefficient and surface tension information can be obtained.

The step of analyzing and outputting the surface function value ends when the surface function value is within the error range of the set desired surface function value. The data of the process design value and the surface function value that are output after the end is re-learned by the AI program. Here, the desired surface function value is a surface function value desired by the user.

Conversely, if the surface function value exceeds the error range of the set desired surface function value, it is corrected by the learned AI program and the process design value is changed and reflected in the design.

Therefore, it is possible to output process-based convergence design and manufacturing techniques using data and AI programs, and it is also possible to derive from shape design to analysis and manufacturing processes using AI. In addition, design values worked by humans can be verified and corrected and supplemented by AI technology, and design and process corrections or new models can be automatically created. By storing information and performance of actually manufactured products in big data, AI can compare and analyze design values and actual results and automatically calculate error rates and correction values.

As described above, it can be seen that the present invention is the basic technical idea of the process-based fusion/composite surface processing method, program, and platform, and within the scope of the basic idea of the present invention, conventional knowledge in the art Of course, many other variations are possible for those who have it.

Claims (14)

A process input step of inputting process design values for material surface processing; A modeling step of modeling the surface shape of the material by data according to the process design; Analyzing and outputting surface functional values representing the functionality of the surface of the material according to the modeling; Process-based convergence and composite surface processing method, characterized in that it comprises. According to claim 1, In the process input step, The process design value is a process-based convergence and complex surface processing method, characterized in that the output of the AI program by inputting the desired surface function value based on the surface function value big data. According to claim 2, In the step of analyzing and outputting the surface function value, Ending when the surface function value is within the error range of the set desired surface function value, When the surface function value exceeds the error range of the set desired surface function value, the process design value is changed by correcting it by the learned AI program. According to claim 2, In the step of analyzing and outputting the surface function value, The AI program is a process-based convergence and complex surface processing method, characterized in that for outputting the process design value based on the surface function value data. According to claim 3, In the step of analyzing and outputting the surface function value, When the surface function value is within the error range of the set desired surface function value, the data of the process design value and the surface function value output when ending is re-learned by the AI program. . According to claim 1, The process design value is, A process-based convergence/composite surface processing method characterized in that the type of equipment for surface processing, processing conditions, and processing sequence are set and input. According to claim 6, The device for surface processing, A process-based fusion/composite surface processing method, characterized in that at least one of a waveform-based processing device, a rotating body-based processing device, a waveform- and rotating body-based processing device, a particle-based processing device, and an electromagnetic-based processing device. According to claim 7, Process-based convergence and complex surface processing method, characterized in that the vibration waveform is reflected in the case of a vibration cutting device (FTS, Fast Tool Servo) among the devices for surface processing. According to claim 1, The surface functional value is, A process-based fusion/composite surface processing method characterized in that one or more of the mechanical, physical, and chemical properties of the material are numerically expressed. According to claim 9, The surface functional value is, A process-based convergence/composite surface processing method characterized in that any one of optical, energy, water repellency, sunlight, hydrophobicity, antiviral, cell-friendly, fluid dynamics, and tribology is data. According to claim 1, In the step of analyzing and outputting the surface function value, A process-based convergence/composite surface processing method characterized in that the type and material of the material are set and input. According to claim 2, The AI program, The big data is a process-based convergence and complex surface processing method, characterized in that it is learned as surface function values and process design values by research information, industry information, and processing error information. A program for executing any one of the above claims 1 to 12. According to claim 13, The platform on which the program runs.

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