Intelligent manufacturing unit control system and device based on flexible circuit board SMT workshop

Abstract

The present invention discloses an intelligent manufacturing unit control system and device based on a flexible circuit board SMT workshop. The system comprises an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing and self-configuration unit, and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-sensing and self-configuration unit is realized by the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is realized by the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base; through the intelligent manufacturing unit control system based on the flexible circuit board SMT workshop, the intelligence level of the SMT workshop can be improved, the production efficiency can be greatly improved, and the intelligent production of the SMT workshop can be realized.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing of FPC boards in PCB manufacturing, and in particular to an intelligent manufacturing unit management and control system and device based on a flexible circuit board SMT workshop. Background Art

[0002] Flexible circuit boards, also known as soft boards or FPC boards, are a type of PCB circuit boards. The informatization and networking of FPC production workshops are low, and the equipment is basically automated, but most of them are single-machine production, and data is recorded manually. Production management (such as production scheduling, progress, equipment management, etc.) and on-site monitoring (such as equipment status, etc.) all rely on manual follow-up, and cannot timely feedback the actual progress on site and the real-time status of the equipment, and cannot timely discover and solve problems. Production management personnel cannot timely manage production according to the on-site status, which directly affects production efficiency and product quality, and increases the cost of the enterprise.

[0003] The level of automation in FPC loading and unloading is low. The loading and unloading of each production process all rely on manual labor, which occupies a large amount of labor. As a flexible material, FPC is easily damaged during manual handling, resulting in waste of consumables. In addition, in the loading process, the material needs to be accurately positioned. Manual loading cannot guarantee the positioning accuracy of the material, resulting in defective products. In addition, the production line process is long, the product involves many processes, and the manufacturing process has many people; the product is customized, the frequency of production change is high, and the production line scheduling is difficult; there are many types of equipment, and data collection and information exchange are difficult; there are many information islands in the existing information system, and the system information is not interoperable, resulting in a low degree of intelligence. These problems are all problems that production companies need to solve urgently. Summary of the invention

[0004] In view of the current situation in SMT workshops, there are many types of equipment, difficult data collection and information exchange, low degree of automation in the whole process of material and product connection, many information islands, and low degree of intelligent manufacturing. An intelligent manufacturing unit management and control system and device based on a flexible circuit board SMT workshop is provided.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides an intelligent manufacturing unit management and control system based on a flexible circuit board SMT workshop, comprising an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing and self-configuration unit, and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-sensing and self-configuration unit is implemented through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is implemented through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base;

[0007] The intelligent manufacturing unit knowledge base is used for processing structured databases, and uses big data mining technology to train input and output information in the database to form a reasonable and usable knowledge base;

[0008] The intelligent manufacturing unit database is used to dynamically collect and maintain typical key processes, important process parameters, key information of manufacturing equipment, and product quality information of the flexible circuit board SMT workshop to form a structured manufacturing unit database;

[0009] The process parameter self-sensing and self-configuring unit of the intelligent manufacturing unit is used for intelligent division of the states of the intelligent manufacturing unit, automatic state perception of the intelligent manufacturing unit under specific working conditions, and self-configuration of process parameters based on the knowledge base of the intelligent manufacturing unit, so as to realize intelligent configuration of process parameters under specific input raw materials and target product conditions;

[0010] The intelligent manufacturing unit product quality information prediction unit is used to detect product quality under the input conditions of specific raw materials and processes, and dynamically adjust the product quality detection results according to the perception status of the manufacturing unit.

[0011] As a preferred technical solution, the intelligent manufacturing unit knowledge base establishes a machine learning model through daily experience, combined with rules and algorithms, repeatedly trains the database modular information, conducts data mining and analysis, and stores the information model obtained by data mining as new knowledge in the knowledge base to form a quality prediction knowledge base and a self-configuration knowledge base;

[0012] The intelligent manufacturing unit knowledge base includes a quality prediction knowledge base and a self-configuration knowledge base;

[0013] The quality prediction knowledge base, through data mining and analysis, predicts the quality of a specific product under the configuration of specific equipment parameters and specific process parameters;

[0014] The self-configuring knowledge base realizes the automatic configuration knowledge base of equipment participation and process parameters in the production process.

[0015] As a preferred technical solution, the intelligent manufacturing unit database autonomously senses and receives multi-source heterogeneous data through data acquisition to form a process basic database and a production information database;

[0016] The intelligent manufacturing unit database includes a data acquisition unit, a process basic database and a production information database;

[0017] The data acquisition unit is used for autonomously sensing and receiving multi-source heterogeneous data and processing them to form structured data;

[0018] The process basic database is a database for storing processing parameters, equipment information, material parameters and basic product quality information;

[0019] The production information database is a database used to store processing equipment status, material processing status and product quality detection information.

[0020] As a preferred technical solution, the process parameter self-sensing and self-configuration unit of the intelligent manufacturing unit makes decisions through the intelligent manufacturing unit knowledge base, autonomously perceives the reasonable processing parameters of the product's directional processing, and autonomously perceives the expected production capacity and continuous service life status information of the manufacturing unit's processing equipment. At the same time, based on the equipment status information regularly collected in the process information database, the self-sensing status information of the processing equipment is fed back and supplemented to achieve optimal self-sensing of the process parameters of the intelligent manufacturing unit. Based on the relevant process parameter information obtained by self-sensing, the trained physical system autonomous control method is used to automatically configure the reasonable selection results of the product's processing process parameters and processing equipment.

[0021] As a preferred technical solution, the process parameter self-sensing and self-configuring unit of the intelligent manufacturing unit includes a parameter processing module, an expected production capacity module, a life state module, and a control module;

[0022] The parameter processing module is used to configure equipment parameters and process parameters for specific product production during daily production;

[0023] The expected production capacity module is used to estimate the production capacity within the daily production process;

[0024] The life status module is used to monitor the life status of equipment in daily production processes;

[0025] The control module is used for automatic configuration of processing parameters and processing equipment, and can obtain configuration parameter experience through the manufacturing unit knowledge base.

[0026] As a preferred technical solution, the intelligent manufacturing unit product quality information prediction unit, based on the input production materials, auxiliary materials performance parameters and product design information, based on the product basic quality information contained in the process basic database in the knowledge base, uses the quality prediction knowledge base constructed through learning and training to make a preliminary prediction of product quality information. Based on the material processing information, processing equipment status, and product quality inspection information data modules contained in the knowledge base, the product quality information is supplemented and fed back, and the corresponding rules, logic and algorithms are used to achieve product quality prediction in the production process, determine the expected quality of the product obtained under the process parameters and processing equipment configuration, and trace the cause of the waste.

[0027] As a preferred technical solution, the intelligent manufacturing unit product quality information prediction unit includes a material parameter configuration module, a product basic quality information module, and a knowledge base update module;

[0028] The material parameter configuration module is used for various materials and auxiliary materials required in the daily production process;

[0029] The product basic quality information module is used to trace the cause of scrap by comparing the basic information of materials and auxiliary materials, the configuration information of processing equipment and process parameters with the information in the knowledge base, to reversely infer the cause of scrap, or form a new knowledge base.

[0030] The present invention provides an intelligent manufacturing unit control device based on a flexible circuit board SMT workshop, 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;

[0031] The system management and control layer includes intelligent management and control system, MES system and 4G module;

[0032] The intelligent management and control system collects key information on parameters related to manufacturing equipment for important parameters in the SMT production line of PCB manufacturing, and establishes an intelligent manufacturing unit database based on big data analysis; for structured post-processing of the database, the system uses database and data mining, and from the perspectives of expert decision-making, algorithm analysis, and database management and maintenance, under the condition of inputting specific material parameters and target product parameters, realizes intelligent perception and self-configuration of processing parameters of processing equipment of intelligent manufacturing units for each key intelligent manufacturing unit;

[0033] The MES system is used to control the entire production process of flexible circuit boards from the formulation of work order plans to the storage of finished products;

[0034] The 4G module is used for data exchange between 4G base stations, and at the same time, the commands of the intelligent management and control system are conveyed to the AGV through the 4G module and the 4G base station;

[0035] The network layer includes switches, Ethernet and 4G base stations;

[0036] The switch is used for data exchange between various devices and systems;

[0037] The Ethernet is an independent local area network, which is completely separated from the office network and the outside world, reducing the invasion of external viruses and Trojans;

[0038] The 4G base station is used for data transmission between the AGV and the system control layer;

[0039] The application layer includes RTU, virtual RTU and application equipment, and the application equipment is connected to the switch through RTU.

[0040] As a preferred technical solution, the RTU has Ethernet, RS 232, RS485 and DP interfaces, and can realize TCP / IP, MODBUS RTU and PROFIBUS protocol communications. The specific indicators are as follows:

[0041] Input voltage: AC 220V;

[0042] Power frequency: 50HZ;

[0043] Power consumption: less than 100W;

[0044] CPU process image size: 1024 bytes input / 1024 bytes output;

[0045] Bit memory size: 8192 bytes;

[0046] I / O quantity: 14 input points / 10 output points, expandable via modules;

[0047] AI quantity: 2 channels (0-10V), accuracy: 10-bit resolution;

[0048] 6 high-speed counters; 3 with 100kHz and 3 with 30kHz clock frequency

[0049] Pulse output: 2 channels;

[0050] Supported communication interfaces: 1 Ethernet; 1 RS 232; 1 RS 485;

[0051] Supported communication protocols: MODBUS TCP, S7 protocol, Profitbus DP, ProfitNet;

[0052] Data collection period: 0.1s.

[0053] As a preferred technical solution, the virtual RTU obtains production data by reading the data records of the controller through software, and then communicates and transmits data with the monitoring PC and MES system through its own communication capabilities;

[0054] Virtual RTU parameters:

[0055] Polling cycle: ≤1min;

[0056] Data reading time: ≤1s;

[0057] Features: It has the functions of automatic start-up and automatic start-up in case of failure;

[0058] Continuous trouble-free operation time: ≥1000 hours.

[0059] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0060] The present invention is based on the intelligent manufacturing unit management and control system of the SMT workshop, including an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing and self-configuration unit, and an intelligent manufacturing unit product quality information prediction unit. The system of the present invention can improve the intelligence level of the SMT workshop, establish a database and knowledge base based on big data, dynamically adjust the product quality inspection results according to the perception status of the manufacturing unit, and intelligently configure the process parameters under specific input raw materials and target product conditions, thereby greatly improving production efficiency and realizing intelligent production in the SMT workshop.

[0061] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is the overall hierarchical diagram of the system of the present invention;

[0063] Figure 2 It is a flow chart of establishing a database of the present invention;

[0064] Figure 3 It is a flow chart of establishing the knowledge base of the present invention;

[0065] Figure 4 It is a schematic diagram of the self-sensing and self-configuration method of the present invention;

[0066] Figure 5 It is a schematic diagram of product quality information prediction of the present invention;

[0067] Figure 6 It is a network structure diagram of the present invention. DETAILED DESCRIPTION

[0068] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0069] As used in the embodiments of the present application, "electronic devices" and "communication terminals" (or simply "terminals") include, but are not limited to, devices configured to receive / send communication signals via a wired line 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 (for example, 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). Communication terminals configured to communicate via a wireless interface may be referred to as "wireless communication terminals", "wireless terminals", "mobile terminals" and / or "electronic devices". Examples of electronic devices include, but are not limited to satellite or cellular phones; personal communication system (PCS) terminals that can combine cellular radiotelephones with data processing, fax, and data communication capabilities; PDAs that can 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 radiotelephone transceivers.

[0070] For example, certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that hardware manufacturers may use different terms to refer to the same component. The specification and claims do not use differences in names as a way to distinguish components, but use differences in the functions of components as the criteria for distinction. For example, "including" mentioned throughout the specification and claims is an open term, so it should be interpreted as "including but not limited to"; "substantially" means that those skilled in the art can solve technical problems within a certain error range and basically achieve technical effects.

[0071] Example

[0072] like Figure 1-Figure 5 As shown, this embodiment is based on the intelligent manufacturing unit management and control system of the flexible circuit board SMT workshop, including an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing and self-configuration unit, and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-sensing and self-configuration unit is implemented through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is implemented through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base.

[0073] The intelligent manufacturing unit knowledge base is used for processing structured databases, and uses big data mining technology to train input and output information in the database to form a reasonable and usable knowledge base.

[0074] The intelligent manufacturing unit database is used to dynamically collect and maintain typical key processes, important process parameters, key information of manufacturing equipment, and product quality information of a flexible circuit board SMT workshop to form a structured manufacturing unit database.

[0075] The intelligent manufacturing unit process parameter self-sensing and self-configuration unit is used for intelligent division of the states of the intelligent manufacturing unit, automatic state perception of the intelligent manufacturing unit under specific working conditions, and self-configuration of process parameters based on the intelligent manufacturing unit knowledge base, to achieve intelligent configuration of process parameters under specific input raw materials and target product conditions.

[0076] The intelligent manufacturing unit product quality information prediction unit is used to detect product quality under the input conditions of specific raw materials and processes, and dynamically adjust the product quality detection results according to the perception status of the manufacturing unit.

[0077] Further, such as Figure 2 As shown, the intelligent manufacturing unit database autonomously senses and receives multi-source heterogeneous data through data acquisition to form a process basic database and a production information database.

[0078] The intelligent manufacturing unit database includes a data acquisition unit, a process basic database and a production information database.

[0079] The data acquisition unit is used for autonomously sensing and receiving multi-source heterogeneous data and forming structured data after processing.

[0080] The process basic database is a database used to store processing parameters, equipment information, material parameters and basic product quality information.

[0081] The production information database is a database used to store processing equipment status, material processing status and product quality detection information.

[0082] Further, such as Figure 3 As shown, the intelligent manufacturing unit knowledge base, through daily experience, combines rules and algorithms to establish a machine learning model, repeatedly trains the modular information of the database, conducts data mining and analysis, and stores the information model obtained by data mining as new knowledge in the knowledge base, forming a quality prediction knowledge base and a self-configuration knowledge base.

[0083] The daily experience described is the production experience accumulated by people in the daily production process.

[0084] The rules are used for parameter adjustment rules of equipment in daily production process.

[0085] The algorithm is a learning algorithm used to establish a machine learning model.

[0086] The training is used for mining and analyzing modular information of the database.

[0087] Furthermore, the intelligent manufacturing unit knowledge base includes a quality prediction knowledge base and a self-configuration knowledge base.

[0088] The quality prediction knowledge base, through data mining and analysis, predicts the quality of a specific product under the configuration of specific equipment parameters and specific process parameters.

[0089] The self-configuring knowledge base realizes the automatic configuration knowledge base of equipment participation and process parameters in the production process.

[0090] Further, such as Figure 4 As shown, the process parameter self-sensing and self-configuration unit of the intelligent manufacturing unit makes decisions through the intelligent manufacturing unit knowledge base, autonomously perceives reasonable processing parameters for product-oriented processing, and autonomously perceives status information such as expected production capacity and continuous service life of the manufacturing unit processing equipment. At the same time, based on the equipment status information regularly collected in the process information database, the self-sensing status information of the processing equipment is fed back and supplemented to achieve optimal self-sensing of the process parameters of the intelligent manufacturing unit. Based on the relevant process parameter information obtained by self-sensing, the trained physical system autonomous control method is used to automatically configure the reasonable selection results of the product's processing process parameters and processing equipment.

[0091] Furthermore, the process parameter self-sensing and self-configuring unit of the intelligent manufacturing unit includes a parameter processing module, an expected production capacity module, a life status module, and a control module.

[0092] The parameter processing module is used to configure equipment parameters and process parameters for the production of specific products during daily production.

[0093] The expected production capacity module is used to estimate the production capacity within the daily production process.

[0094] The life status module is used to monitor the life status of equipment in daily production processes.

[0095] The control module is used for automatic configuration of processing parameters and processing equipment, and can obtain configuration parameter experience through the manufacturing unit knowledge base.

[0096] Further, such as Figure 5As shown in the figure, the product quality information prediction unit of the intelligent manufacturing unit makes a preliminary prediction of the product quality information based on the input performance parameters of production materials and auxiliary materials and product design information, based on the basic product quality information contained in the process basic database in the knowledge base, and using the quality prediction knowledge base constructed through learning and training. Based on the data modules such as material processing information, processing equipment status, and product quality inspection information contained in the knowledge base, the product quality information is supplemented and fed back, and the corresponding rules, logic and algorithms are used to realize the product quality prediction of the production process, judge the expected quality of the product obtained under the process parameters and processing equipment configuration, and realize the traceability of the cause of waste.

[0097] Furthermore, the intelligent manufacturing unit product quality information prediction unit includes a material parameter configuration module, a product basic quality information module, and a knowledge base update module.

[0098] The material parameter configuration module is used for various materials and auxiliary materials required in daily production processes.

[0099] The product basic quality information module is used to trace the cause of scrap by comparing the basic information of materials and auxiliary materials, the configuration information of processing equipment and process parameters with the information in the knowledge base, to reversely infer the cause of scrap, or form a new knowledge base.

[0100] like Figure 6 As shown, in another embodiment of the present invention, an intelligent manufacturing unit control device based on a flexible circuit board SMT workshop includes a system control layer, a network layer and an application layer, and the system control layer and the application layer exchange data through the network layer; the specific scheme is as follows:

[0101] (1) The system management and control layer includes an intelligent management and control system, an MES system and a 4G module.

[0102] The intelligent management and control system targets important parameters in the SMT production line equipment of PCB manufacturing, collects key information such as manufacturing equipment related parameters, and establishes an intelligent manufacturing unit database based on big data analysis; for structured post-processing of the database, using database and data mining, from the perspectives of expert decision-making, algorithm analysis, database management and maintenance, under the condition of inputting specific material parameters and target product parameters, for each key intelligent manufacturing unit, the intelligent perception and self-configuration of the processing parameters of the intelligent manufacturing unit processing equipment are realized.

[0103] The MES system is used to control the entire production process of flexible circuit boards from the formulation of work order plans to the warehousing of finished products; including tracking and recording of production resources (people, machines, materials, methods, and environment), analysis and early warning of production quality, production scheduling, process scheduling, and analysis of key indicators.

[0104] The 4G module is used for data exchange between 4G base stations, and at the same time conveys the commands of the intelligent management and control system to AGV through the 4G module and the 4G base station.

[0105] (2) The network layer includes switches, Ethernet, and 4G base stations.

[0106] The switch is used for data exchange between various devices and systems.

[0107] The Ethernet is an independent local area network, which is completely separated from the office network and the outside world, thereby reducing the invasion of external viruses and Trojans.

[0108] The 4G base station is used for data transmission between the AGV and the system management and control layer.

[0109] (3) The application layer includes RTU, virtual RTU and application equipment, and the application equipment is connected to the switch through RTU.

[0110] (1)RTU:

[0111] The data communication interfaces of the equipment, environmental equipment and workshop material warehouse on the production line are not unified, and some equipment does not have communication functions. It is necessary to add communication functions to the corresponding equipment for data collection. There are mainly two ways: RTU and virtual RTU.

[0112] ①RTU equipment:

[0113] like Figure 6 As shown in the figure, the equipment and environmental equipment in production line 1 and production line 2 are controlled by programmable controllers (different brands and models), which do not have LAN ports and have different protocols. In this case, RTU is used to communicate with the programmable controller and perform protocol conversion.

[0114] RTU has Ethernet, RS 232, RS485 and DP interfaces, and can realize TCP / IP, MODBUS RTU and PROFIBUS protocol communications. The specific indicators are as follows:

[0115] Input voltage: AC 220V;

[0116] Power frequency: 50HZ;

[0117] Power consumption: less than 100W;

[0118] CPU process image size: 1024 bytes input / 1024 bytes output;

[0119] Bit memory size: 8192 bytes;

[0120] I / O quantity: 14 input points / 10 output points, expandable via modules;

[0121] AI quantity: 2 channels (0-10V), accuracy: 10-bit resolution;

[0122] 6 high-speed counters; 3 with 100kHz and 3 with 30kHz clock frequency

[0123] Pulse output: 2 channels;

[0124] Supported communication interfaces: 1 Ethernet; 1 RS 232; 1 RS 485;

[0125] Supported communication protocols: MODBUS TCP, S7 protocol, Profitbus DP, ProfitNet, etc. Data collection cycle: 0.1s.

[0126] ②Virtual RTU

[0127] like Figure 6 As shown in the figure, the workshop material controller is a computer with an Ethernet port that can be connected to the production network, but it does not have the ability to generate real-time data or communicate with the workshop monitoring PC and MES system. In actual production, the production data of these three workshops is mainly historical data, and real-time data is not very useful. Therefore, the virtual RTU method is used to upload data. In addition, the virtual RTU method does not require additional hardware and has lower costs.

[0128] The virtual RTU obtains production data by reading the data records of the controller through software, and then communicates and transmits data with the monitoring PC and MES system through its own communication capabilities.

[0129] Virtual RTU parameters:

[0130] Polling cycle: ≤1min;

[0131] Data reading time: ≤1s;

[0132] Features: It has the functions of automatic start-up and automatic start-up in case of failure;

[0133] Continuous trouble-free operation time: ≥1000 hours;

[0134] (2) AGV, an unmanned guided vehicle. When there is a shortage of materials on the production line, the intelligent management and control system sends instructions to it through the 4G base station. The AGV receives the instructions and moves to the workshop material warehouse to obtain the corresponding materials and transports them to the production line that is short of materials.

[0135] (3) Data dashboard, which is used to display information from the MES system, monitoring system or video system. Production managers can understand the production status of the workshop without entering the workshop.

[0136] (4) Environmental equipment: equipment used to monitor workshop environmental information, such as humidity, temperature, cleanliness, etc., and feed it back to the intelligent management and control system through RTU. When the environment deviates from the environment required for normal production, the intelligent management and control system will adjust the corresponding control equipment.

[0137] (5) The workshop material warehouse is used to store materials to ensure the normal production of the production line. It is equipped with a robot to automatically pick up materials. When the AGV moves to the workshop material warehouse, the material warehouse distributes the corresponding materials to the AGV through the instructions of the intelligent management and control system.

[0138] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. Intelligent manufacturing unit management and control system based on flexible circuit board SMT workshop, characterized by: It includes an intelligent manufacturing unit knowledge base, an intelligent manufacturing unit database, an intelligent manufacturing unit process parameter self-sensing and self-configuring unit, and an intelligent manufacturing unit product quality information prediction unit; the intelligent manufacturing unit process parameter self-sensing and self-configuring unit is implemented through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base, and the intelligent manufacturing unit product quality information prediction unit is implemented through the intelligent manufacturing unit database and the intelligent manufacturing unit knowledge base; The intelligent manufacturing unit knowledge base is used for processing structured databases, and uses big data mining technology to train input and output information in the database to form a reasonable and usable knowledge base; The intelligent manufacturing unit database is used to dynamically collect and maintain typical key processes, important process parameters, key information of manufacturing equipment, and product quality information of the flexible circuit board SMT workshop to form a structured manufacturing unit database; The process parameter self-sensing and self-configuring unit of the intelligent manufacturing unit is used for intelligent division of the states of the intelligent manufacturing unit, automatic state perception of the intelligent manufacturing unit under specific working conditions, and self-configuration of process parameters based on the intelligent manufacturing unit knowledge base, so as to realize intelligent configuration of process parameters under specific input raw materials and target product conditions; the process parameter self-sensing and self-configuring unit of the intelligent manufacturing unit makes decisions through the intelligent manufacturing unit knowledge base, autonomously perceives reasonable processing parameters for directional processing of products, autonomously perceives expected production capacity and continuous service life status information of the processing equipment of the manufacturing unit, and at the same time, based on the equipment status information regularly collected in the process information database, feeds back and supplements the self-sensing status information of the processing equipment, so as to realize the optimal self-sensing of the process parameters of the intelligent manufacturing unit, and based on the relevant process parameter information obtained by self-sensing, uses the trained physical system autonomous control method to automatically configure the reasonable selection results of the processing parameters of the product and the processing equipment; The intelligent manufacturing unit product quality information prediction unit is used to detect product quality under the input conditions of specific raw materials and processes, and dynamically adjust the product quality detection results according to the perception status of the manufacturing unit; the intelligent manufacturing unit product quality information prediction unit, based on the input performance parameters of production materials and auxiliary materials and product design information, uses the product basic quality information contained in the process basic database in the knowledge base, and uses the quality prediction knowledge base constructed through learning and training to make a preliminary prediction of product quality information; based on the material processing information, processing equipment status, and product quality detection information data modules contained in the knowledge base, the product quality information is supplemented and fed back, and the corresponding rules, logic and algorithms are used to realize product quality prediction of the production process, judge the expected quality of the product obtained under the process parameters and processing equipment configuration, and trace the cause of scrap.

2. According to claim 1, the intelligent manufacturing unit management and control system based on the flexible circuit board SMT workshop is characterized in that: The intelligent manufacturing unit knowledge base uses daily experience, combined with rules and algorithms to establish a machine learning model, repeatedly trains the database modular information, conducts data mining and analysis, and stores the information model obtained from data mining as new knowledge in the knowledge base to form a quality prediction knowledge base and a self-configuration knowledge base; The intelligent manufacturing unit knowledge base includes a quality prediction knowledge base and a self-configuration knowledge base; The quality prediction knowledge base, through data mining and analysis, predicts the quality of a specific product under the configuration of specific equipment parameters and specific process parameters; The self-configuring knowledge base realizes the automatic configuration knowledge base of equipment participation and process parameters in the production process.

3. According to the intelligent manufacturing unit management and control system based on the flexible circuit board SMT workshop according to claim 1, it is characterized in that: The intelligent manufacturing unit database autonomously senses and receives multi-source heterogeneous data through data acquisition to form a process basic database and a production information database; The intelligent manufacturing unit database includes a data acquisition unit, a process basic database and a production information database; The data acquisition unit is used for autonomously sensing and receiving multi-source heterogeneous data and processing them to form structured data; The process basic database is a database for storing processing parameters, equipment information, material parameters and basic product quality information; The production information database is a database used to store processing equipment status, material processing status and product quality detection information.

4. According to the intelligent manufacturing unit management and control system based on the flexible circuit board SMT workshop according to claim 1, it is characterized in that: The process parameter self-sensing and self-configuring unit of the intelligent manufacturing unit includes a parameter processing module, an expected production capacity module, a life state module, and a control module; The parameter processing module is used to configure equipment parameters and process parameters for specific product production during daily production; The expected production capacity module is used to estimate the production capacity within the daily production process; The life status module is used to monitor the life status of equipment in daily production processes; The control module is used for automatic configuration of processing parameters and processing equipment, and can obtain configuration parameter experience through the manufacturing unit knowledge base.

5. According to the intelligent manufacturing unit management and control system based on the flexible circuit board SMT workshop according to claim 1, it is characterized in that: The intelligent manufacturing unit product quality information prediction unit includes 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 to trace the cause of scrap by comparing the basic information of materials and auxiliary materials, the configuration information of processing equipment and process parameters with the information in the knowledge base, to reversely infer the cause of scrap, or form a new knowledge base.

6. Intelligent manufacturing unit control device based on flexible circuit board SMT workshop, characterized in that: An intelligent manufacturing unit control system based on a flexible circuit board SMT workshop applied to any one of claims 1 to 5, 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 management and control layer includes intelligent management and control system, MES system and 4G module; The intelligent management and control system is an intelligent manufacturing unit management and control system based on a flexible circuit board SMT workshop. It targets important parameters in the SMT production line equipment of PCB manufacturing, collects key information on manufacturing equipment parameters, and establishes an intelligent manufacturing unit database based on big data analysis. For structured post-processing of the database, it uses database and data mining, and from the perspectives of expert decision-making, algorithm analysis, and database management and maintenance, under the condition of inputting specific material parameters and target product parameters, for each key intelligent manufacturing unit, it realizes intelligent perception and self-configuration of processing parameters of intelligent manufacturing unit processing equipment. The MES system is used to control the entire production process of flexible circuit boards from the formulation of work order plans to the storage of finished products; The 4G module is used for data exchange between 4G base stations, and at the same time, the commands of the intelligent management and control system are conveyed to the AGV through the 4G module and the 4G base station; The network layer includes switches, Ethernet and 4G base stations; The switch is used for data exchange between various devices and systems; The Ethernet is an independent local area network, which is completely separated from the office network and the outside world, reducing the invasion of external viruses and Trojans; The 4G base station is used for data transmission between the AGV and the system control layer; The application layer includes RTU, virtual RTU and application equipment, and the application equipment is connected to the switch through RTU.

7. The intelligent manufacturing unit control device based on the flexible circuit board SMT workshop according to claim 6 is characterized in that: The RTU has Ethernet, RS232, RS485 and DP interfaces, and can realize TCP / IP, MODBUS RTU and PROFIBUS protocol communications. The specific indicators are as follows: Input voltage: AC 220V; Power frequency: 50HZ; Power consumption: less than 100W; CPU process image size: 1024 bytes input / 1024 bytes output; Bit memory size: 8192 bytes; I / O quantity: 14 input points / 10 output points, expandable via modules; AI quantity: 2 channels (0-10V), accuracy: 10-bit resolution; 6 high-speed counters; 3 with 100kHz and 3 with 30kHz clock frequency Pulse output: 2 channels; Supported communication interfaces: 1 Ethernet; 1 RS232; 1 RS 485; Supported communication protocols: MODBUS TCP, S7 protocol, Profitbus DP, ProfitNet; Data collection period: 0.1s.

8. The intelligent manufacturing unit control device based on the flexible circuit board SMT workshop according to claim 6 is characterized in that: The virtual RTU obtains production data by reading the data records of the controller through software, and then communicates and transmits data with the monitoring PC and MES system through its own communication capabilities; Virtual RTU parameters: Polling cycle: ≤1min; Data reading time: ≤1s; Features: It has the functions of automatic start-up and automatic start-up in case of failure; Continuous trouble-free operation time: ≥1000 hours.

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