CN113110345A - Intelligent manufacturing unit management and control system and device based on flexible circuit board SMT workshop - Google Patents
Intelligent manufacturing unit management and control system and device based on flexible circuit board SMT workshop Download PDFInfo
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Abstract
The invention discloses an intelligent manufacturing unit management and control system and device based on a flexible circuit board SMT workshop, wherein the system comprises an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing self-configuration unit and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-perception self-configuration unit is realized through an intelligent manufacturing unit database and an intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is realized through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base; through this intelligent unit management and control system of making based on flexible circuit board SMT workshop, can improve the intelligent level in SMT workshop, promote production efficiency by a wide margin, realize the intelligent production in SMT workshop.
Description
Technical Field
The invention relates to the field of intelligent manufacture of FPC (flexible printed circuit) boards in PCB (printed circuit board) manufacture, in particular to an intelligent manufacture unit management and control system and device based on a flexible printed circuit board SMT (surface mount technology) workshop.
Background
The flexible circuit board is also called a flexible board or an FPC board, and is one of the PCB circuit boards. The informatization and networking degrees of the production workshop of the FPC are low, the equipment basically realizes automation, but the equipment is mostly single-machine production, data are recorded manually, production management (such as scheduling, progress, equipment management and the like) and field monitoring (such as equipment states and the like) all depend on manual follow-up, the actual field progress and the real-time state of the equipment cannot be fed back in time, problems and solutions cannot be found in time, production management personnel cannot carry out production management according to the field states in time, the production efficiency and the product quality are directly influenced, and the cost of enterprises is increased.
FPC's last unloading automation level is low, and the material loading, unloading of each process of production all rely on artifically, have occupied a large amount of labours, and FPC takes place to roll over the damage as flexible material easily in artifical handling, causes the consumptive material extravagant, and in the material loading link, need carry out accurate counterpoint to the material, and the location accuracy of material can not be guaranteed in artifical material loading to cause the defective products to produce. In addition, the production line has long process flow, the product relates to a plurality of working procedures, and the personnel in the manufacturing process are numerous; the product is produced in a customized manner, the production change frequency is high, and the production line arrangement difficulty is high; the equipment is various, and data acquisition and information interaction are difficult; the problems that the existing information system has a plurality of isolated islands and the system information is not intercommunicated, so that the intelligent degree is low and the like are problems to be solved urgently by production enterprises.
Disclosure of Invention
The invention provides an intelligent manufacturing unit management and control system and device based on a flexible circuit board SMT workshop, aiming at the current situations of multiple equipment types, difficult data acquisition and information interaction, low full-process connection automation operation degree of materials and products, more information islands, low intelligent manufacturing degree and the like in the SMT workshop at present.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides an intelligent manufacturing unit management and control system based on a flexible circuit board SMT workshop, which comprises an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing self-configuration unit and an intelligent manufacturing unit product quality information prediction unit, wherein the intelligent manufacturing unit knowledge base is used for storing the intelligent manufacturing unit knowledge base; the intelligent manufacturing unit process parameter self-perception self-configuration unit is realized through an intelligent manufacturing unit database and an intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is realized through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base;
the intelligent manufacturing unit knowledge base is used for processing a structured database, and training input and output information in the database by using a big data mining technology to form a reasonable and available knowledge base;
the intelligent manufacturing unit database is used for dynamically acquiring and maintaining typical key processes, important process parameters, manufacturing equipment key information and product quality information of a flexible circuit board SMT workshop to form a structured manufacturing unit database;
the intelligent manufacturing unit process parameter self-perception self-configuration unit is used for intelligently dividing the state of the intelligent manufacturing unit, automatically perceiving the state of the intelligent manufacturing unit under a specific working condition, and intelligently configuring the process parameters under the conditions of specific input raw materials and target products based on the process parameter self-configuration of the intelligent manufacturing unit knowledge base;
the product quality information prediction unit of the intelligent manufacturing unit is used for detecting the product quality under the input condition of specific raw materials and processes and dynamically adjusting the product quality detection result according to the perception state of the manufacturing unit.
As a preferred technical scheme, the intelligent manufacturing unit knowledge base establishes a machine learning model by daily experience and combining rules and algorithms, repeatedly trains modular information of the database, performs data mining and analysis, and stores an information model obtained by data mining in the knowledge base as new knowledge to form a quality prediction knowledge base and a self-configuration knowledge base;
the intelligent manufacturing unit knowledge base comprises a quality prediction knowledge base and a self-configuration knowledge base;
the quality prediction knowledge base is used for predicting the quality of a specific product under the configuration of specific equipment parameters and specific process parameters after data mining and analysis;
the self-configuration knowledge base realizes the equipment participation and the automatic configuration knowledge base of the process parameters in the production process.
As a preferred technical scheme, the intelligent manufacturing unit database performs autonomous perception and reception on multi-source heterogeneous data through data acquisition to form a process basic database and a production information database;
the intelligent manufacturing unit database comprises a data acquisition unit, a process basic database and a production information database;
the data acquisition unit is used for performing autonomous perception reception on multi-source heterogeneous data and forming structured data after processing;
the process basic database is used for storing a database of processing parameters, equipment information, material parameters and product basic quality information;
and the production information database is used for storing the database of the processing equipment state, the material processing state and the product quality detection information.
The intelligent manufacturing unit process parameter self-perception self-configuration unit is used for making a decision through an intelligent manufacturing unit knowledge base, autonomously perceiving reasonable processing parameters of oriented processing of a product, and the expected capacity and the continuous service life state information of processing equipment of the intelligent manufacturing unit, and simultaneously feeding back and supplementing the self-perception state information of the processing equipment based on equipment state information periodically acquired in a process information database so as to realize the optimal self-perception of the process parameters of the intelligent manufacturing unit.
As a preferred technical scheme, the intelligent manufacturing unit process parameter self-sensing self-configuration unit comprises a parameter processing module, an expected capacity module, a life state module and a control module;
the parameter processing module is used for configuring equipment parameters and process parameters when specific products are produced in the daily production process;
the expected capacity module is used for estimating the capacity within time in the daily production process;
the service life state module is used for monitoring the service life state of the equipment in the daily production process;
the control module is used for processing technological parameters and automatic configuration of processing equipment, and configuration parameter experience obtained by a manufacturing unit knowledge base is used.
As an optimal technical scheme, the product quality information prediction unit of the intelligent manufacturing unit is used for primarily predicting the product quality information by applying a quality prediction knowledge base constructed by learning and training on the basis of the product basic quality information contained in a process basic database in the knowledge base aiming at the input performance parameters and product design information of production materials and auxiliary materials. And a data module for detecting information based on material processing information, processing equipment state and product quality contained in the knowledge base supplements and feeds back the product quality information, and is matched with corresponding rules, logics and algorithms to realize product quality prediction in the production process, judge the expected quality condition of the product under the configuration of the process parameters and the processing equipment and realize the tracing of the cause of the waste.
As a preferred technical scheme, the product quality information prediction unit of the intelligent manufacturing unit comprises a material parameter configuration module, a product basic quality information module and a knowledge base updating module;
the material parameter configuration module is used for various materials and auxiliary materials required in the daily production process;
the product basic quality information module is used for tracing according to the reasons of the waste products, comparing information in a knowledge base through basic information of materials and auxiliary materials and configuration information of processing equipment and process parameters, and reversely deducing the reasons of the waste products or forming a new knowledge base.
The invention provides an intelligent manufacturing unit control device based on a flexible circuit board SMT workshop, which comprises a system control layer, a network layer and an application layer, wherein the system control layer and the application layer exchange data through the network layer;
the system control layer comprises an intelligent control system, an MES system and a 4G module;
the intelligent management and control system is used for simultaneously acquiring key information of relevant parameters of manufacturing equipment aiming at important parameters in SMT production line type equipment manufactured by PCBs and establishing an intelligent manufacturing unit database based on big data analysis; aiming at the structured post-processing of a database, the database and data mining, and from the aspects of expert decision, algorithm analysis and database management and maintenance, under the condition of inputting specific material parameters and target product parameters, aiming at each key intelligent manufacturing unit, the intelligent perception and self-configuration of the processing parameters of the processing equipment of the intelligent manufacturing unit are realized;
the MES system is used for managing and controlling the whole production process of the flexible circuit board from the establishment of the work order plan to the warehousing of the finished products;
the 4G module is used for data exchange between the 4G base stations and transmitting a command of the intelligent management and control system to the AGV through the 4G module and the 4G base stations;
the network layer comprises a switch, an Ethernet and a 4G base station;
the switch is used for data exchange among all devices and systems;
the Ethernet is an independent local area network, is completely separated from an office network and the outside, and reduces the invasion of external viruses and trojans;
the 4G base station is used for data transmission between the AGV and the system management and control layer;
the application layer comprises an RTU, a virtual RTU and application equipment, and the application equipment is connected with the switch through the RTU.
As a preferred technical scheme, the RTU has ethernet, RS 232, RS485 and DP interfaces, and can implement TCP/IP, MODBUS RTU and PROFIBUS protocol communication, with specific indexes as follows:
input voltage: AC 220V;
power supply frequency: 50 HZ;
power consumption: less than 100W;
CPU process image size: 1024 bytes in/1024 bytes out;
bit memory size: 8192 bytes;
I/O number: 14-point input/10-point output, which can be expanded by a module;
the AI number: 2-way (0-10V), precision: 10 bit resolution;
6 high-speed counters are arranged; 3 clock frequencies of 100kHz and 3 clock frequencies of 30kHz
2 paths of pulse output;
the supported communication interface is 1 Ethernet; 1 RS 232; 1 RS 485;
the supported communication protocols comprise MODBUS TCP, S7 protocol, Profitbus DP and ProfitNet;
the data acquisition period is 0.1 s.
As a preferred technical scheme, the virtual RTU obtains production data by reading data records of the controller through software, and communicates and transmits the data with a monitoring PC and an MES system through communication capacity of the virtual RTU;
virtual RTU parameters:
and (3) polling period: less than or equal to 1 min;
data reading time: less than or equal to 1 s;
the method is characterized in that: the system has the functions of starting up and automatically starting up the system when a fault occurs;
continuous fault-free run time: not less than 1000 hours.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the intelligent manufacturing unit management and control system based on the SMT workshop comprises an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing self-configuration unit and an intelligent manufacturing unit product quality information prediction unit.
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
drawings
FIG. 1 is an overall hierarchy of the system of the present invention;
FIG. 2 is a database building flow diagram of the present invention;
FIG. 3 is a knowledge base building flow diagram of the present invention;
FIG. 4 is a schematic diagram of the self-sensing and self-configuration method of the present invention;
FIG. 5 is a schematic illustration of product quality information prediction according to the present invention;
fig. 6 is a network architecture diagram of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As used in embodiments herein, a "electronic device" "a communication terminal" (or simply "terminal") includes, but is not limited to, an apparatus configured to receive/transmit communication signals via a wireline connection, such as via a Public Switched Telephone Network (PSTN), a Digital Subscriber Line (DSL), a digital cable, a direct cable connection, and/or another data connection/network, and/or via a wireless interface (e.g., for a cellular network, a Wireless Local Area Network (WLAN), a digital television network such as a DVB-H network, a satellite network, an AM-FM broadcast transmitter, and/or another communication terminal). A communication terminal arranged to communicate over a wireless interface may be referred to as a "wireless communication terminal", a "wireless terminal", a "mobile terminal" and/or an "electronic device". Examples of electronic devices include, but are not limited to, satellite or cellular telephones; a Personal Communications System (PCS) terminal that may combine a cellular radiotelephone with data processing, facsimile and data communications capabilities; PDAs that may include radiotelephones, pagers, internet/intranet access, Web browsers, notepads, calendars, and/or Global Positioning System (GPS) receivers; and conventional laptop and/or palmtop receivers or other electronic devices that include a radiotelephone transceiver.
As used in the specification and in the claims, certain terms are used to refer to particular components. As one skilled in the art will appreciate, manufacturers may refer to a component by different names. The specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to,"; "substantially" means that a person skilled in the art can solve the technical problem within a certain error range and basically achieve the technical effect.
Examples
As shown in fig. 1 to 5, the intelligent manufacturing unit management and control system based on the flexible circuit board SMT shop of the present embodiment includes an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing self-configuration unit, and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-perception self-configuration unit is realized through an intelligent manufacturing unit database and an intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is realized through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base.
The intelligent manufacturing unit knowledge base is used for processing a structured database, and training input and output information in the database by applying a big data mining technology to form a reasonable and available knowledge base.
The intelligent manufacturing unit database is used for dynamically acquiring and maintaining typical key processes, important process parameters, manufacturing equipment key information and product quality information of a flexible circuit board SMT workshop to form a structured manufacturing unit database.
The intelligent manufacturing unit process parameter self-perception self-configuration unit is used for intelligently dividing the state of the intelligent manufacturing unit, automatically perceiving the state of the intelligent manufacturing unit under a specific working condition, and intelligently configuring the process parameters under the conditions of specific input raw materials and target products based on the process parameter self-configuration of the intelligent manufacturing unit knowledge base.
The product quality information prediction unit of the intelligent manufacturing unit is used for detecting the product quality under the input condition of specific raw materials and processes and dynamically adjusting the product quality detection result according to the perception state of the manufacturing unit.
Further, as shown in fig. 2, the intelligent manufacturing unit database performs autonomous sensing reception on multi-source heterogeneous data through data acquisition to form a process base database and a production information database.
The intelligent manufacturing unit database comprises a data acquisition unit, a process basic database and a production information database.
And the data acquisition unit is used for performing autonomous perception reception on the multi-source heterogeneous data and forming structured data after processing.
The process basic database is used for storing a database of processing parameters, equipment information, material parameters and product basic quality information.
And the production information database is used for storing the database of the processing equipment state, the material processing state and the product quality detection information.
Further, as shown in fig. 3, the intelligent manufacturing unit knowledge base establishes a machine learning model by daily experience in combination with rules and algorithms, repeatedly trains the modular information of the database, performs data mining and analysis, and stores an information model obtained by data mining in the knowledge base as new knowledge to form a quality prediction knowledge base and a self-configuration knowledge base.
The daily experience is used for the production experience accumulated by people in the daily production process.
The rule is used for adjusting the parameter of the equipment in the daily production process.
The algorithm is used for establishing a learning algorithm of a machine learning model.
And the training is used for mining and analyzing the database modularization information.
Further, the intelligent manufacturing unit knowledge base comprises a quality prediction knowledge base and a self-configuration knowledge base.
And after data mining and analysis, the quality prediction knowledge base carries out quality prediction under the configuration of specific equipment parameters and specific process parameters for specific products.
The self-configuration knowledge base realizes the equipment participation and the automatic configuration knowledge base of the process parameters in the production process.
Further, as shown in fig. 4, the intelligent manufacturing unit process parameter self-sensing self-configuration unit makes a decision through the intelligent manufacturing unit knowledge base, autonomously senses the reasonable processing parameters of the directional processing of the product, and the state information of the expected capacity, the sustained service life and the like of the processing equipment of the intelligent manufacturing unit, and simultaneously feeds back and supplements the self-sensing state information of the processing equipment based on the equipment state information periodically collected in the process information database, so as to realize the optimal self-sensing of the process parameters of the intelligent manufacturing unit, and automatically configures the processing process parameters of the product and the reasonable selection result of the processing equipment based on the relevant process parameter information obtained by the self-sensing by using the trained physical system autonomous control method.
Furthermore, the intelligent manufacturing unit process parameter self-sensing self-configuration unit comprises a parameter processing module, an expected capacity module, a life state module and a control module.
The parameter processing module is used for configuring equipment parameters and process parameters when specific products are produced in the daily production process.
The expected capacity module is used for estimating the capacity within the time in the daily production process.
And the life state module is used for monitoring the life state of the equipment in the daily production process.
The control module is used for processing technological parameters and automatic configuration of processing equipment, and configuration parameter experience obtained by a manufacturing unit knowledge base is used.
Further, as shown in fig. 5, the product quality information prediction unit of the intelligent manufacturing unit performs preliminary prediction on the product quality information based on the product basic quality information included in the process basic database in the knowledge base, based on the input performance parameters of the production materials and the auxiliary materials and the product design information, by using a quality prediction knowledge base constructed through learning and training. Based on data modules such as material processing information, processing equipment states, product quality detection information and the like contained in a knowledge base, product quality information is supplemented and fed back, product quality prediction in a production process is realized by matching with corresponding rules, logics and algorithms, expected quality conditions of products obtained under the configuration of the process parameters and the processing equipment are judged, and the reason tracing of the wastes is realized.
Furthermore, the product quality information prediction unit of the intelligent manufacturing unit comprises a material parameter configuration module, a product basic quality information module and a knowledge base updating module.
The material parameter configuration module is used for various materials and auxiliary materials required in the daily production process.
The product basic quality information module is used for tracing according to the reasons of the waste products, comparing information in a knowledge base through basic information of materials and auxiliary materials and configuration information of processing equipment and process parameters, and reversely deducing the reasons of the waste products or forming a new knowledge base.
As shown in fig. 6, in another embodiment of the present invention, an intelligent manufacturing unit management and control apparatus based on a flexible circuit board SMT shop includes a system management and control layer, a network layer, and an application layer, where the system management and control layer exchanges data with the application layer through the network layer; the specific scheme is as follows:
(1) the system management and control layer comprises an intelligent management and control system, an MES system and a 4G module.
The intelligent management and control system is used for simultaneously acquiring key information such as relevant parameters of manufacturing equipment and the like aiming at important parameters in SMT production line type equipment manufactured by PCBs and establishing an intelligent manufacturing unit database based on big data analysis; aiming at the structured post-processing of the database, the intelligent perception and self-configuration of the processing parameters of the processing equipment of the intelligent manufacturing units are realized by the database and data mining, from the aspects of expert decision, algorithm analysis, management and maintenance of the database and the like under the condition of inputting specific material parameters and target product parameters.
The MES system is used for managing and controlling the whole production process of the flexible circuit board from the establishment of the work order plan to the warehousing of the finished products; including tracking records of production resources (man, machine, material, law, loop), analytical pre-warning of production quality, scheduling of plans, scheduling of processes, and analysis of key indicators.
The 4G module is used for data exchange between the 4G base stations and transmitting the command of the intelligent management and control system to the AGV through the 4G module and the 4G base stations.
(2) The network layer comprises a switch, an Ethernet and a 4G base station.
The switch is used for data exchange among all the devices and systems.
The Ethernet is an independent local area network, is completely separated from an office network and the outside, and reduces the invasion of external viruses and trojans.
And the 4G base station is used for data transmission between the AGV and the system management and control layer.
(3) The application layer comprises an RTU, a virtual RTU and application equipment, and the application equipment is connected with the switch through the RTU.
(1)RTU：
The data communication interfaces of equipment, environmental equipment and a workshop material library on a production line are not uniform, and part of equipment does not have a communication function, so that the data acquisition is carried out by adding the communication function on corresponding equipment. The method mainly comprises two modes: an RTU and a virtual RTU.
Firstly, RTU equipment:
as shown in fig. 6, the devices in the production line 1 and the production line 2 and the environmental devices are controlled by programmable controllers (with different brands and models), and the main body does not have a lan port, so that the protocols are not uniform. In this case, the RTU is used to communicate with the programmable controller and perform protocol conversion.
The RTU is provided with Ethernet, RS 232, RS485 and DP interfaces, and can realize protocol communication such as TCP/IP, MODBUS RTU and PROFIBUS, and the specific indexes are as follows:
input voltage: AC 220V;
power supply frequency: 50 HZ;
power consumption: less than 100W;
CPU process image size: 1024 bytes in/1024 bytes out;
bit memory size: 8192 bytes;
I/O number: 14-point input/10-point output, which can be expanded by a module;
the AI number: 2-way (0-10V), precision: 10 bit resolution;
6 high-speed counters are arranged; 3 clock frequencies of 100kHz and 3 clock frequencies of 30kHz
2 paths of pulse output;
the supported communication interface is 1 Ethernet; 1 RS 232; 1 RS 485;
the supported communication protocols comprise MODBUS TCP, S7 protocol, Profitbus DP, ProfitNet and other data acquisition periods of 0.1S.
② virtual RTU
As shown in fig. 6, the plant material controller is a computer, and the body has an ethernet port to access the production network, but does not have the capability of generating real-time data and the capability of communicating with the plant monitoring PC and the MES system. In actual production, the production data of the three workshops are mainly historical data, and the real-time data is not significant in function, so that the data are uploaded in a virtual RTU mode. In addition, the virtual RTU mode does not need to add extra hardware and has lower cost.
The virtual RTU reads the data record of the controller through software to obtain production data, and then communicates with the monitoring PC and the MES through the communication capacity of the virtual RTU and transmits the data.
Virtual RTU parameters:
and (3) polling period: less than or equal to 1 min;
data reading time: less than or equal to 1 s;
the method is characterized in that: the system has the functions of starting up and automatically starting up the system when a fault occurs;
continuous fault-free run time: more than or equal to 1000 hours;
(2) AGV, unmanned transport vehicle, when the material was not enough on the production line, intelligence management and control system sent the instruction to it through 4G basic station, and AGV accepts the instruction and moves to workshop material storehouse and acquire corresponding material to transport the production line that lacks the material to it.
(3) And the data billboard is used for displaying information of the MES system, the monitoring system or the video system, and production management personnel can know the implementation production state of the workshop without entering the production workshop.
(4) The environmental equipment is used for monitoring the equipment of the workshop environmental information, such as humidity, temperature, cleanliness and the like, and feeding back the equipment to the intelligent management and control system through the RTU. When the environment deviates from the environment required by normal production, the intelligent management and control system can regulate and control the corresponding control equipment.
(5) The workshop material library is used for storing a warehouse for ensuring normal production of a production line, is provided with automatic manipulator material taking equipment, and when the AGV moves to the workshop material library, the material library distributes corresponding materials to the AGV through an instruction of the intelligent management and control system.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (10)
1. The intelligent manufacturing unit management and control system based on the flexible circuit board SMT workshop is characterized by comprising an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing self-configuration unit and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-perception self-configuration unit is realized through an intelligent manufacturing unit database and an intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is realized through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base;
the intelligent manufacturing unit knowledge base is used for processing a structured database, and training input and output information in the database by using a big data mining technology to form a reasonable and available knowledge base;
the intelligent manufacturing unit database is used for dynamically acquiring and maintaining typical key processes, important process parameters, manufacturing equipment key information and product quality information of a flexible circuit board SMT workshop to form a structured manufacturing unit database;
the intelligent manufacturing unit process parameter self-perception self-configuration unit is used for intelligently dividing the state of the intelligent manufacturing unit, automatically perceiving the state of the intelligent manufacturing unit under a specific working condition, and intelligently configuring the process parameters under the conditions of specific input raw materials and target products based on the process parameter self-configuration of the intelligent manufacturing unit knowledge base;
the product quality information prediction unit of the intelligent manufacturing unit is used for detecting the product quality under the input condition of specific raw materials and processes and dynamically adjusting the product quality detection result according to the perception state of the manufacturing unit.
2. The flexible circuit board SMT workshop-based intelligent manufacturing unit management and control system according to claim 1, wherein the intelligent manufacturing unit knowledge base is configured to build a machine learning model through daily experience in combination with rules and algorithms, repeatedly train database modular information, perform data mining and analysis, and store information models obtained through data mining in the knowledge base as new knowledge to form a quality prediction knowledge base and a self-configuration knowledge base;
the intelligent manufacturing unit knowledge base comprises a quality prediction knowledge base and a self-configuration knowledge base;
the quality prediction knowledge base is used for predicting the quality of a specific product under the configuration of specific equipment parameters and specific process parameters after data mining and analysis;
the self-configuration knowledge base realizes the equipment participation and the automatic configuration knowledge base of the process parameters in the production process.
3. The flexible circuit board SMT workshop-based intelligent manufacturing unit management and control system according to claim 1, wherein the intelligent manufacturing unit database performs autonomous sensing reception on multi-source heterogeneous data through data acquisition to form a process base database and a production information database;
the intelligent manufacturing unit database comprises a data acquisition unit, a process basic database and a production information database;
the data acquisition unit is used for performing autonomous perception reception on multi-source heterogeneous data and forming structured data after processing;
the process basic database is used for storing a database of processing parameters, equipment information, material parameters and product basic quality information;
and the production information database is used for storing the database of the processing equipment state, the material processing state and the product quality detection information.
4. The flexible circuit board SMT shop-based intelligent manufacturing unit management and control system according to claim 1, wherein the intelligent manufacturing unit process parameter self-sensing self-configuration unit makes decisions via an intelligent manufacturing unit knowledge base, autonomously senses reasonable processing parameters for product directional processing, autonomously senses expected capacity and continuous service life status information of the manufacturing equipment of the manufacturing unit, and simultaneously feeds back and supplements the self-sensing status information of the processing equipment based on the equipment status information periodically collected in the process information database to achieve optimal self-sensing of the process parameters of the intelligent manufacturing unit, and automatically configures the processing process parameters of the product and the reasonable selection results of the processing equipment based on the relevant process parameter information obtained by self-sensing by using a trained physical system autonomous control method.
5. The flexible circuit board SMT shop based intelligent manufacturing unit management and control system according to claim 4, wherein the intelligent manufacturing unit process parameter self-sensing self-configuration unit comprises a parameter processing module, an expected capacity module, a life status module, and a control module;
the parameter processing module is used for configuring equipment parameters and process parameters when specific products are produced in the daily production process;
the expected capacity module is used for estimating the capacity within time in the daily production process;
the service life state module is used for monitoring the service life state of the equipment in the daily production process;
the control module is used for processing technological parameters and automatic configuration of processing equipment, and configuration parameter experience obtained by a manufacturing unit knowledge base is used.
6. The flexible circuit board SMT shop-based intelligent manufacturing unit management and control system according to claim 1, wherein the intelligent manufacturing unit product quality information prediction unit is configured to perform preliminary prediction on product quality information based on product basic quality information included in a process basic database in the knowledge base based on input performance parameters of production materials and auxiliary materials and product design information, using a quality prediction knowledge base constructed through learning and training. And a data module for detecting information based on material processing information, processing equipment state and product quality contained in the knowledge base supplements and feeds back the product quality information, and is matched with corresponding rules, logics and algorithms to realize product quality prediction in the production process, judge the expected quality condition of the product under the configuration of the process parameters and the processing equipment and realize the tracing of the cause of the waste.
7. The flexible circuit board SMT shop based intelligent manufacturing unit management and control system according to claim 1, wherein the intelligent manufacturing unit product quality information prediction unit comprises a material parameter configuration module, a product basic quality information module, and a knowledge base update module;
the material parameter configuration module is used for various materials and auxiliary materials required in the daily production process;
the product basic quality information module is used for tracing according to the reasons of the waste products, comparing information in a knowledge base through basic information of materials and auxiliary materials and configuration information of processing equipment and process parameters, and reversely deducing the reasons of the waste products or forming a new knowledge base.
8. The intelligent manufacturing unit control device based on the flexible circuit board SMT workshop is characterized by comprising a system control layer, a network layer and an application layer, wherein the system control layer and the application layer exchange data through the network layer;
the system control layer comprises an intelligent control system, an MES system and a 4G module;
the intelligent management and control system is used for simultaneously acquiring key information of relevant parameters of manufacturing equipment aiming at important parameters in SMT production line type equipment manufactured by PCBs and establishing an intelligent manufacturing unit database based on big data analysis; aiming at the structured post-processing of a database, the database and data mining, and from the aspects of expert decision, algorithm analysis and database management and maintenance, under the condition of inputting specific material parameters and target product parameters, aiming at each key intelligent manufacturing unit, the intelligent perception and self-configuration of the processing parameters of the processing equipment of the intelligent manufacturing unit are realized;
the MES system is used for managing and controlling the whole production process of the flexible circuit board from the establishment of the work order plan to the warehousing of the finished products;
the 4G module is used for data exchange between the 4G base stations and transmitting a command of the intelligent management and control system to the AGV through the 4G module and the 4G base stations;
the network layer comprises a switch, an Ethernet and a 4G base station;
the switch is used for data exchange among all devices and systems;
the Ethernet is an independent local area network, is completely separated from an office network and the outside, and reduces the invasion of external viruses and trojans;
the 4G base station is used for data transmission between the AGV and the system management and control layer;
the application layer comprises an RTU, a virtual RTU and application equipment, and the application equipment is connected with the switch through the RTU.
9. The intelligent manufacturing unit management and control device based on flexible circuit board SMT workshop according to claim 8, wherein the RTU is provided with Ethernet, RS 232, RS485 and DP interfaces, and can realize TCP/IP, MODBUS RTU and PROFIBUS protocol communication, and specific indexes are as follows:
input voltage: AC 220V;
power supply frequency: 50 HZ;
power consumption: less than 100W;
CPU process image size: 1024 bytes in/1024 bytes out;
bit memory size: 8192 bytes;
I/O number: 14-point input/10-point output, which can be expanded by a module;
the AI number: 2-way (0-10V), precision: 10 bit resolution;
6 high-speed counters are arranged; 3 clock frequencies of 100kHz and 3 clock frequencies of 30kHz
2 paths of pulse output;
the supported communication interface is 1 Ethernet; 1 RS 232; 1 RS 485;
the supported communication protocols comprise MODBUS TCP, S7 protocol, Profitbus DP and ProfitNet;
the data acquisition period is 0.1 s.
10. The intelligent manufacturing unit control device based on the flexible circuit board SMT workshop according to claim 8, wherein the virtual RTU reads data records of the controller through software to obtain production data, and communicates with the monitoring PC and the MES through own communication capability and transmits the data;
virtual RTU parameters:
and (3) polling period: less than or equal to 1 min;
data reading time: less than or equal to 1 s;
the method is characterized in that: the system has the functions of starting up and automatically starting up the system when a fault occurs;
continuous fault-free run time: not less than 1000 hours.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114140034A (en) * | 2022-01-30 | 2022-03-04 | 希望知舟技术(深圳)有限公司 | Quality monitoring method based on working conditions and related device |
| CN114394415A (en) * | 2021-12-28 | 2022-04-26 | 赤壁市万皇智能设备有限公司 | FPC automation line based on AGV automatic handling system |
| CN117250923A (en) * | 2023-09-25 | 2023-12-19 | 浙江迦楠智药科技有限公司 | Process, production and equipment operation linkage control method for pharmaceutical production line |
| CN117726080A (en) * | 2024-02-05 | 2024-03-19 | 南京迅集科技有限公司 | Multi-source heterogeneous data driven intelligent manufacturing decision system and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114394415A (en) * | 2021-12-28 | 2022-04-26 | 赤壁市万皇智能设备有限公司 | FPC automation line based on AGV automatic handling system |
| CN114394415B (en) * | 2021-12-28 | 2023-12-12 | 赤壁市万皇智能设备有限公司 | FPC automated production line based on AGV automatic handling system |
| CN114140034A (en) * | 2022-01-30 | 2022-03-04 | 希望知舟技术(深圳)有限公司 | Quality monitoring method based on working conditions and related device |
| CN114140034B (en) * | 2022-01-30 | 2022-04-29 | 希望知舟技术(深圳)有限公司 | Quality monitoring method based on working conditions and related device |
| CN117250923A (en) * | 2023-09-25 | 2023-12-19 | 浙江迦楠智药科技有限公司 | Process, production and equipment operation linkage control method for pharmaceutical production line |
| CN117726080A (en) * | 2024-02-05 | 2024-03-19 | 南京迅集科技有限公司 | Multi-source heterogeneous data driven intelligent manufacturing decision system and method |
| CN117726080B (en) * | 2024-02-05 | 2024-04-26 | 南京迅集科技有限公司 | Multi-source heterogeneous data driven intelligent manufacturing decision system and method |
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