CN110795874A - Digital twin model for flexible circuit board manufacturing process - Google Patents
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Abstract
The invention discloses a digital twin model for a flexible circuit board manufacturing process. The digital twin model of the flexible circuit board manufacturing process consists of three parts, namely a physical space, a virtual space, and a data information chain and data processing system. The physical space is the flexible circuit board manufacturing process. The virtual space is a flexible circuit board manufacturing process model, and a virtual entity system model capable of representing the whole life cycle of the flexible circuit board manufacturing is constructed in the virtual information space. The data information chain and the data processing system are an information transmission chain which is used for connecting a physical space and a virtual space, and the information processing system is used for carrying out artificial intelligence analysis on the transmitted information. The digital twin model of the flexible circuit board manufacturing process carries out real-time monitoring, fault prediction and process parameter optimization on the full life cycle production process, improves the yield of the flexible circuit board, reduces the production cost of products and improves the production efficiency.
Description
Technical Field
The invention relates to the field of flexible circuit board product manufacturing processes, in particular to a digital twin model for a flexible circuit board manufacturing process.
Background
Flexible circuit boards have been widely used in electronic products such as notebook computers, memory cards, digital cameras, digital video cameras, and mobile phones, as the root products of the modern electronic industry have developed rapidly in recent years. The flexible printed circuit board uses polyimide as a bottom plate, and a printed circuit with copper foil as a conductor is attached to the surface of the bottom plate, so that mounting support can be provided for various electronic components and IC chips, signal transmission, insulation and mutual electrical connection can be realized, and the flexible printed circuit board has excellent electrical characteristics. Compared with the traditional printed circuit board, the flexible circuit board has the advantages of light weight, thinness, short size, small size, flexible structure and the like, and can realize dynamic bending, curling and folding besides static bending. The digital twin is to realize the mirror image of the physical entity space in the virtual space by utilizing physical model data and integrating multidisciplinary and multiscale simulation technology. The digital twin, also known as digital mirror image, digital map or digital twins, reflects the production cycle process of the corresponding physical entity product.
With the increase of market demand, flexible circuit board production enterprises also face multiple tests, wherein, how to improve the yield and the production efficiency becomes the most concerned problem for manufacturers. However, in the conventional manufacturing process of the flexible circuit board, most enterprises adopt a method of product spot inspection to ensure the quality of the flexible circuit board, but the quality of the flexible circuit board can not be detected until all processes are finished, so that the detection result has certain hysteresis. If an anomaly occurs in a process, it may result in a large batch of rejects. Although the flexible circuit board has simple and small appearance, the manufacturing process is complex, the process is various, and the quality of the final product is determined to a great extent by the states of all the manufactured process flows. In addition, the information amount of physical detection is limited, and the production process must be analyzed and detected at deep level and multiple angles through virtual modeling to obtain more comprehensive running state information. Therefore, a digital twin model needs to be developed for each process in the flexible circuit board manufacturing, a digital virtual model body of each process is established, manufacturing parameters of each process are optimized, the abnormality of each process is predicted in real time, and early warning is carried out in time before a fault occurs, so that the manufacturing yield of each process is improved. Therefore, the research on the simulation method of the flexible circuit board manufacturing process has important significance for improving the yield and the production efficiency.
Disclosure of Invention
The invention aims to provide a digital twin model for a flexible circuit board manufacturing process aiming at the problem of the existing flexible circuit board manufacturing process so as to optimize manufacturing parameters of each process and implement abnormal prediction.
In order to achieve the purpose, the invention adopts the technical scheme that:
a digital twin model for flexible circuit board manufacturing process is composed of three parts, namely a physical space, a virtual space and a data information transmission and processing system;
the physical space, namely the flexible circuit board manufacturing process, comprises the processes of punching, coating, exposing, developing, etching, tin melting, stripping and electrical measurement;
the virtual space is a flexible circuit board manufacturing process model, a virtual entity system model which can represent the whole life cycle of the flexible circuit board manufacturing is constructed in the virtual information space, and the virtual entity system model comprises a punching thermodynamic model, a coating fluid mechanical model, an exposure photochemical model, a developing chemical model, an etching chemical model, a tin-chemical detection model, a strip mechanical model and an electric measurement database model;
the data information transmission and processing system is a system which is a data information transmission chain connecting the physical space and the virtual space and carries out artificial intelligent analysis on real-time data and process parameters of the manufacturing process of the physical space and output parameters of each model of the virtual space through a data processing platform.
Further, the data information transmission and processing system transmits the real-time data and the process parameters of the manufacturing process of the physical space to the virtual space and the data processing platform, transmits the output parameters of the virtual space model to the data processing platform, and transmits the optimized process parameter data output by the data processing platform to the physical space.
Furthermore, the data processing platform optimizes the process parameters based on the real-time data of the manufacturing process and the data of the full-life-cycle large samples of the process parameters and the data of the full-life-cycle large samples obtained based on the virtual space, and realizes the advance prejudgment of the productivity, the efficiency, the possible production bottlenecks and other problems through machine learning, thereby finally predicting the yield and the production efficiency.
Furthermore, the punching comprises a punching process and a punching information acquisition process, wherein the punching process refers to mechanical drilling of the circuit board through a drill, and the punching information acquisition process refers to acquisition of coordinate information of the drill, acquisition of chip morphology images, monitoring of drilling force and monitoring of drilling temperature;
the punching thermodynamic model is a finite element entity model of the punching process, information acquired by the punching process is used as simulation input, the drill bit and the circuit board are subjected to thermodynamic analysis, and thermodynamic data of the circuit board full model are calculated.
Further, the coating comprises a coating process and a coating information acquisition process, wherein the coating process refers to coating operation of a coating material on the circuit board by a dry film method, and the coating information acquisition process refers to acquisition of area, thickness and temperature information of the coating material;
the coating hydrodynamics model is a finite element model of a coating process, takes the area, thickness and temperature information of a coating material as simulation input, carries out hydrodynamics simulation on the coating material, and calculates the uniformity of the coating material and the fineness of a pattern.
Further, the exposure includes an exposure process and an information acquisition process of the exposure process, the exposure process is a process of aligning the circuit board with the exposure machine and exposing the circuit board through the exposure machine, and the information acquisition process of the exposure refers to acquiring light frequency and exposure time data.
The exposure photochemical model is a photochemical model of the action of the material and light, and the exposure modification rate data of the material is obtained by calculating the photopolymerization reaction by taking the material parameters, the exposure light frequency and the exposure time of the circuit board as input parameters.
Further, the development comprises a development process and an information acquisition process of the development process. The developing process is to wash the exposed circuit board in developer solution, and the unexposed dry film can be dissolved in the developer solution, and the exposed dry film can not be dissolved, so that a dry film pattern is formed through developing. The development information acquisition is to acquire the developing solution material, temperature and washing duration information.
The developing chemical model is a first principle model of chemical reaction of a dry film of a circuit board and a developing solution, materials of the developing solution, temperature and washing duration are used as input parameters, the solubility of reaction activation energy and the solubility of the dry film are calculated through a first principle calculation method, and the definition and the fineness of a dry film graph are predicted.
Further, the etching comprises an etching process and an information acquisition process of the etching process. The etching is to put the circuit board in the etching solution for etching, the dry film has etching resistance, the part of the cover film protects the copper under the dry film, and the copper exposed on the outer surface is etched, thus forming the circuit pattern with the dry film and the copper. The etching information is acquired by acquiring dry film materials, etching solution temperature and circuit pattern geometric parameter information.
The etching chemical model is a first principle model of chemical reaction of the circuit board and the etching solution, the temperature of the dry film material, the etching solution material and the etching solution is used as input parameters, and the reaction activation energy is calculated by a first principle calculation method.
Further, the tin melting is a tin melting process and an information acquisition process of the tin melting process. The tin melting refers to depositing a layer of tin on the position of a circuit board bonding pad by a chemical method, and the thickness of the tin is about 10-30 microns. The information acquisition of the tin melting process is to acquire the shape information and the temperature information of the tin after deposition.
The tin melting thermodynamic model is a tin material geometric model containing temperature information and is established by collecting shape information and temperature information of tin after deposition, and the stress distribution condition of the tin material geometric model is calculated.
Further, the striping is a striping process and an information acquisition process of the striping process. The slitting process is to automatically cut a whole circuit board into a plurality of independent circuit boards through a slitting machine. The information acquisition process of the slitting process is to acquire the stress and temperature information of the circuit board in the slitting process.
The mechanical model of the slitting machine is used for carrying out dynamic and static simulation on the cutting process by establishing a whole circuit board and the mechanical model of the slitting machine, and calculating the accuracy of the cutting size.
Further, the electrical measurement is an electrical measurement process and an information acquisition process of the electrical measurement process. The electric measurement process is to perform switch circuit detection on the circuit board through a resistance measuring instrument. The information acquisition process of the electrical measurement process is to acquire resistance information of each circuit of the circuit board.
The electric logging database model collects the collected resistance information of each line of the circuit board and establishes a database, and the failure rate of each line resistance of the circuit board is predicted through a machine learning algorithm based on a Bayesian method.
The invention has the advantages that:
and establishing a digital twin model for the flexible circuit board manufacturing process, and carrying out real-time monitoring, fault prediction and process parameter optimization on the full life cycle production process. Compared with the method for realizing process optimization and predicting the fault rate in a single process through a single process model, the digital twin model can quickly and accurately realize process optimization in the whole production process and predict the fault rate of each process, and finally the yield of the flexible circuit board is improved, the production cost of the product is reduced, and the production efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of a digital twinning model for a flexible circuit board manufacturing process.
Detailed Description
The invention is described in further detail below with reference to the following figures and specific examples:
the embodiment of the invention provides a digital twin model for a flexible circuit board manufacturing process.
In the punching process, the coordinate information of a drill bit, the image information of the shape of the cutting, the drilling force and the drilling temperature are monitored and collected, and the data are transmitted to a thermodynamic model and a data processing platform of the punching process.
Establishing a punching process thermodynamic model corresponding to a physical space punching process in a virtual space, establishing a finite element entity model of a punching process, establishing a heat conduction control equation according to a Fourier heat transfer law and an energy conservation law, taking information acquired by the punching process as simulation input, performing thermodynamic analysis on a drill bit and a circuit board based on a heat conduction finite element method, calculating to obtain circuit board full model thermodynamic data, and transmitting the circuit board full model thermodynamic data to a data processing platform.
In the coating process, the area, thickness and temperature information data of the coating material are collected and transmitted to a coating fluid mechanics model and a data processing platform.
Establishing a coating fluid mechanics model corresponding to a physical space coating process in a virtual space, taking the area, thickness and temperature information of a coating material as simulation input, carrying out grid division and setting calculation boundary conditions on the model based on a computational fluid dynamics method, finally carrying out fluid mechanics simulation on the coating material, calculating the uniformity of the coating material and the fineness of a pattern, and transmitting the data of the uniformity of the coating material and the fineness of the pattern to a data processing platform.
In the exposure process, light frequency and exposure time data are collected and transmitted to an exposure photochemical model and a data processing platform.
Establishing an exposure photochemical model corresponding to a physical space exposure process in a virtual space, taking material parameters, exposure light frequency and exposure time of a circuit board as input parameters, selecting parameters such as exchange correlation functional and pseudo potential in a simulation process based on a density functional theory, simulating photopolymerization reaction by first principle software to obtain exposure modification rate data of the material, and outputting the exposure modification rate data of the material to a data processing platform.
In the developing process, developing solution material, temperature and washing duration information data are collected and transmitted to a developing chemical model and a data processing platform.
Establishing a developing chemical model corresponding to a physical space developing process in a virtual space, taking a developing solution material, temperature and washing duration as input parameters, selecting parameters such as exchange correlation functional and pseudo potential in a simulation process based on a density functional theory, calculating the solubility of reaction activation energy and a dry film by a first principle calculation method, and inputting the reaction activation energy of the material and the solubility data of the dry film into a data processing platform.
In the etching process, dry film materials, etching solution temperature and circuit pattern geometric parameter information are collected, and the data are transmitted to an etching chemical model and a data processing platform.
Establishing an etching chemical model corresponding to a physical space etching process in a virtual space, taking the temperature of a dry film material, an etching solution material and the etching solution as input parameters, selecting parameters such as an exchange correlation functional and a pseudo potential in a simulation process based on a density functional theory, calculating reaction activation energy by a first principle calculation method, and inputting reaction activation energy data into a data processing platform.
In the tin melting process, the shape information and the temperature information of the tin after deposition are collected, and the data are transmitted to a tin melting thermodynamic model and a data processing platform.
The tin melting thermodynamic model corresponding to the physical space tin melting process is established in a virtual space, a heat conduction control equation is established according to the Fourier heat transfer law and the energy conservation law, the shape information and the temperature information of tin after deposition are used as input parameters, a tin material geometric model containing the temperature information is established based on a heat conduction finite element method, the stress distribution condition of the tin material geometric model is calculated, and the stress distribution data is input into a data processing platform.
In the splitting process, the stress and temperature information of the circuit board in the splitting process is collected, and the data is transmitted to the splitting mechanical model and the data processing platform.
The method comprises the steps of establishing a slitting mechanical model corresponding to a physical space slitting process in a virtual space, performing dynamic and static simulation on a cutting process by establishing a mechanical model of a whole circuit board and a slitting machine and by using mechanical system dynamics automatic analysis software and finite element statics analysis software, calculating cutting size accuracy, and transmitting cutting size accuracy data to a data processing platform.
In the electrical measurement process, resistance information of each circuit of the circuit board is collected, and the data is transmitted to the strip mechanical model and the data processing platform.
Establishing an electrical measurement database model corresponding to a physical space electrical measurement process in a virtual space, collecting resistance information of each line of a circuit board, establishing a database, predicting the fault rate of each line of the circuit board through a machine learning algorithm based on a Bayesian method, and inputting the fault rate data of each line of the circuit board into a data processing platform.
A digital twin model for the flexible circuit board manufacturing process is established, real-time monitoring, fault prediction and process parameter optimization are carried out on the full life cycle production process, the yield of the flexible circuit board is improved, the production cost of the product is reduced, and the production efficiency is improved.
The data processing platform predicts the local part failure rate and the whole failure rate through deep learning based on real-time data of the manufacturing process and full-life-cycle large sample data of process parameters and based on full-life-cycle large sample data output by a virtual space. And optimizing the process parameters in real time, and transmitting the optimized process parameters to each manufacturing process in the physical space, thereby improving the production efficiency of each manufacturing process.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A digital twinning model for a flexible circuit board manufacturing process, characterized by: the system consists of three parts, namely a physical space, a virtual space and a data information transmission and processing system;
the physical space, namely the flexible circuit board manufacturing process, comprises the processes of punching, coating, exposing, developing, etching, tin melting, stripping and electrical measurement;
the virtual space is a flexible circuit board manufacturing process model, a virtual entity system model which can represent the whole life cycle of the flexible circuit board manufacturing is constructed in the virtual information space, and the virtual entity system model comprises a punching thermodynamic model, a coating fluid mechanical model, an exposure photochemical model, a developing chemical model, an etching chemical model, a tin-chemical detection model, a strip mechanical model and an electric measurement database model;
the data information transmission and processing system is a system which is a data information transmission chain connecting the physical space and the virtual space and carries out artificial intelligent analysis on real-time data and process parameters of the manufacturing process of the physical space and output parameters of each model of the virtual space through a data processing platform.
2. The digital twin model for flexible circuit board manufacturing process according to claim 1, wherein: the data information transmission and processing system transmits real-time data and process parameters of the manufacturing process of the physical space to the virtual space and the data processing platform, transmits output parameters of the virtual space model to the data processing platform, and transmits optimized process parameter data output by the data processing platform to the physical space.
3. The digital twin model for flexible circuit board manufacturing process according to claim 2, wherein: the data processing platform optimizes the process parameters based on real-time data of the manufacturing process, full-life-cycle large sample data of the process parameters and the full-life-cycle large sample data obtained based on the virtual space, and pre-judges the productivity, the efficiency, the possible production bottleneck and other problems in advance through machine learning, so as to finally predict the yield and the production efficiency.
4. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the punching comprises a punching process and a punching information acquisition process, wherein the punching process refers to mechanical drilling of the circuit board through a drill bit, and the punching information acquisition process refers to acquisition of coordinate information of the drill bit, acquisition of chip morphology images, monitoring of drilling force and monitoring of drilling temperature;
the punching thermodynamic model is a finite element entity model of the punching process, information acquired by the punching process is used as simulation input, the drill bit and the circuit board are subjected to thermodynamic analysis, and thermodynamic data of the circuit board full model are calculated.
5. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the coating comprises a coating process and a coating information acquisition process, wherein the coating process refers to coating operation of a coating material on the circuit board by a dry film method, and the coating information acquisition process refers to acquisition of area, thickness and temperature information of the coating material;
the coating hydrodynamics model is a finite element model of a coating process, takes the area, thickness and temperature information of a coating material as simulation input, carries out hydrodynamics simulation on the coating material, and calculates the uniformity of the coating material and the fineness of a pattern.
6. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the exposure comprises an exposure process and an information acquisition process of the exposure process, wherein the exposure process is a process of aligning the circuit board with an exposure machine and exposing the circuit board through the exposure machine, and the information acquisition process of the exposure refers to the acquisition of light frequency and exposure time data;
the exposure photochemical model is a photochemical model of the action of the material and light, and the exposure modification rate data of the material is obtained by calculating the photopolymerization reaction by taking the material parameters, the exposure light frequency and the exposure time of the circuit board as input parameters.
7. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the development comprises a development process and an information acquisition process of the development process, the development process is to put the exposed circuit board in a developing solution for washing, an unexposed dry film can be dissolved in the developing solution, and the exposed dry film can not be dissolved, so a dry film graph is formed through development; the developing information acquisition is to acquire developing solution material, temperature and washing duration information;
the developing chemical model is a first principle model of chemical reaction of a dry film of a circuit board and a developing solution, materials of the developing solution, temperature and washing duration are used as input parameters, the solubility of reaction activation energy and the solubility of the dry film are calculated through a first principle calculation method, and the definition and the fineness of a dry film graph are predicted.
8. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the etching comprises an etching process and an information acquisition process of the etching process, the etching is to put the circuit board into etching solution for etching, the dry film has etching resistance, the part of the cover film protects the copper below, and the copper exposed on the outer surface is etched away, so that a circuit pattern with the dry film and the copper is formed; the etching information acquisition comprises the acquisition of dry film materials, etching solution temperature and circuit graph geometric parameter information;
the etching chemical model is a first principle model of chemical reaction of the circuit board and the etching solution, the temperature of the dry film material, the etching solution material and the etching solution is used as input parameters, and the reaction activation energy is calculated by a first principle calculation method.
9. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the tin melting is a tin melting process and an information acquisition process of the tin melting process, wherein the tin melting process is to deposit a layer of tin with the thickness of 10-30 micrometers at the position of a circuit board pad by a chemical method; the information acquisition of the tin melting process is to acquire shape information and temperature information of tin after deposition;
the tin melting thermodynamic model is a tin material geometric model containing temperature information and is established by collecting shape information and temperature information of tin after deposition, and the stress distribution condition of the tin material geometric model is calculated.
10. A digital twin model for flexible circuit board manufacturing process according to claim 1, 2 or 3, characterized in that: the striping is a striping process and an information acquisition process of the striping process; the slitting process is to automatically cut the whole circuit board into a plurality of independent circuit boards through a slitting machine, and the information acquisition process of the slitting process is to acquire the stress and temperature information of the circuit board in the slitting process;
the slitting mechanical model is used for carrying out dynamic and static simulation on a cutting process by establishing a whole circuit board and a mechanical model of the slitting machine and calculating the cutting size accuracy;
the electric measurement is an electric measurement process and an information acquisition process of the electric measurement process, the electric measurement process is to perform on-off circuit detection on the circuit board through a resistance measuring instrument, and the information acquisition process of the electric measurement process is to acquire resistance information of each circuit of the circuit board;
the electric logging database model collects the collected resistance information of each line of the circuit board and establishes a database, and the failure rate of each line resistance of the circuit board is predicted through a machine learning algorithm based on a Bayesian method.
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