Artificial intelligence circuit board production equipment management system

Abstract

The invention discloses an artificial intelligence circuit board production equipment management system, and particularly relates to the technical field of equipment management. Comprising a circuit board production equipment database, a circuit board production equipment area division module, a circuit board production equipment management data acquisition module, a circuit board production equipment management analysis module, a circuit board production equipment management decision module, a circuit board production equipment management comprehensive analysis module and a circuit board production equipment management man-machine interaction module. The circuit board production equipment area division module is used for determining to-be-managed production equipment as a target management area, and dividing the target management area into a plurality of monitoring sub-areas according to each piece of equipment; through a big data technology and a sensor technology, real-time monitoring and intelligent management of the circuit board production equipment are realized, scientific production equipment management data support is provided for an administrator, and the operation efficiency and stability of the equipment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment management, and in particular to an artificial intelligence circuit board production equipment management system. Background Art

[0002] With the rapid development of the electronics industry, the demand for circuit boards is growing, and the efficient management of circuit board production equipment has become the key to improving production efficiency and product quality. With the continuous breakthroughs in artificial intelligence technology, especially the popularization of Internet of Things technology, the interconnection between circuit board production equipment can be achieved, and the operation data of the equipment can be collected in real time. The use of big data technology can deeply mine and analyze these massive data, providing strong decision-making support for circuit board equipment management.

[0003] In the field of circuit board production equipment management technology, traditional equipment management methods mainly rely on manual inspections, regular maintenance and paper records. Inspectors carry necessary tools and equipment to conduct on-site inspections of circuit board production equipment according to the plan; maintenance personnel conduct comprehensive inspections and maintenance of equipment according to the plan; inspection records the results of each inspection, including problems found, treatment methods, treatment results, etc. However, with the continuous development of circuit board production technology, the complexity and automation of production equipment are getting higher and higher.

[0004] Although the traditional equipment management method can ensure the stable operation of the equipment to a certain extent, it also has some obvious disadvantages: it not only consumes a lot of manpower and material resources, but also has difficulty in timely discovering potential abnormalities and problems of the equipment, and has problems such as low efficiency, untimely abnormal discovery, inaccurate maintenance plans, and untimely information updates, which may lead to wrong decisions and make it difficult to meet the high requirements of modern circuit board production. Therefore, it is of great practical significance to develop an intelligent circuit board production equipment management system. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an artificial intelligence circuit board production equipment management system to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above purpose, the present invention provides the following technical solution: an artificial intelligence circuit board production equipment management system, comprising:

[0007] Circuit board production equipment database: Through big data technology, collect and store equipment information data on the circuit board production line and existing public equipment abnormality data, and build a circuit board production equipment management database;

[0008] Circuit board production equipment area division module: used to determine the production equipment in the circuit board production equipment management database as the target management area, and divide the target management area into several monitoring sub-areas according to each equipment, which are recorded as 1, 2, i, ..., n in sequence;

[0009] Circuit board production equipment management data acquisition module: used to collect data from each monitoring sub-area, obtain various monitoring parameters of circuit board production equipment management, and output various monitoring parameters to the circuit board production equipment management module;

[0010] Circuit board production equipment management and analysis module: including production equipment efficiency management and analysis unit, production equipment production quality management and analysis unit, production equipment energy consumption management and analysis unit and production equipment operation status management and analysis unit, and transmits various management indicators obtained by each analysis unit to the circuit board production equipment management decision module;

[0011] Circuit board production equipment management decision module: used to compare the various management indicators of the circuit board production equipment obtained by the management analysis module with the threshold value, and issue an early warning and generate a management decision strategy to the circuit board production equipment management human-computer interaction module based on the abnormal comparison results, and transmit the normal comparison results to the circuit board production equipment management comprehensive analysis module;

[0012] Circuit board production equipment management comprehensive analysis module: used to comprehensively analyze the normal comparison results obtained by the management decision module, obtain the comprehensive management indicators of circuit board production equipment, and transmit them to the circuit board production equipment management human-computer interaction module;

[0013] Circuit board production equipment management human-computer interaction module: used to receive early warning information and management decision strategies from the management decision module, as well as receive comprehensive management indicators of circuit board production equipment from the management comprehensive analysis module, and perform human-computer interaction.

[0014] Preferably, the monitoring parameters in the circuit board production equipment management data acquisition module include target management area information, circuit board production equipment administrator identity authentication information, production equipment efficiency parameters, production equipment production quality parameters, production equipment energy consumption parameters and production equipment operating status parameters, wherein the production equipment efficiency parameters specifically include the total number of circuit board processing completed by each device, the actual production time of each device, the length of each circuit board processing cycle, the total operating time of the production equipment and the target processing quantity of each device; the production equipment production quality parameters specifically include the number of circuit boards with defects processed by each device, the total number of circuit boards processed, the number of defect types and the total number of defect types; the production equipment energy consumption parameters specifically include the energy consumption of each device, the standby energy consumption and the total energy consumption of all equipment; the production equipment operating status parameters specifically include the actual production time of each device, the fault downtime, the number of fault downtimes, the fault repair time, the number of maintenance completed by each device, and Tn_m represents the planned maintenance number.

[0015] Preferably, the production equipment efficiency management and analysis unit in the circuit board production equipment management and analysis module: within the management cycle, firstly, the total number of circuit board processing completed by each device on the circuit board production line P, the actual production time of each device t_s and the length of each circuit board processing cycle t_j are obtained through sensor technology, and the start and end time of each circuit board processing cycle are recorded through timestamp technology to obtain t_j; then, the circuit board production equipment efficiency management index PEI of the monitoring sub-area is obtained through big data analysis technology i , , t0 represents the total operating time of the production equipment during the management cycle, (t_j) j represents the processing cycle length of the jth circuit board, P0 represents the target processing quantity of each device within the management cycle, and c1 and c2 represent the corresponding weights respectively.

[0016] Preferably, the production equipment production quality management and analysis unit in the circuit board production equipment management and analysis module: within the management cycle, firstly, the circuit board defect detection technology is used to detect each circuit board processed by the equipment on the production line, and the number of defective circuit boards processed by each equipment n_d, the total number of circuit boards processed P, and the number of defect types of defective circuit boards n_t are obtained by statistics, and the defective circuit board refers to the circuit board that fails to pass the defect detection; then the production quality management index QMI of the circuit board production equipment in the monitoring sub-area is obtained by big data analysis technology i , , n_t0 represents the total number of defect types that will occur in each device in the circuit board production equipment management database, and b1 and b2 represent the corresponding weights respectively.

[0017] Preferably, the production equipment energy consumption management and analysis unit in the circuit board production equipment management and analysis module: within the management cycle, firstly, the energy consumption W of each device is obtained through sensor technology, including standby energy consumption and production energy consumption, the standby energy consumption refers to the energy consumption of the equipment when it is running but not producing and processing, the production energy consumption refers to the energy consumption of the equipment when it is running and producing and processing, the energy consumption refers to the electric energy used, and the standby energy consumption S_W of the equipment; then, the energy consumption efficiency management index EMI of the circuit board production equipment in the monitoring sub-area is obtained through big data analysis technology i , , T_W represents the total energy consumption of all devices, and S_W represents the standby energy consumption of each device.

[0018] Preferably, the circuit board production equipment management and analysis module production equipment operation status management and analysis unit: within the management cycle, firstly, the actual production time t_s, fault downtime t_t, fault downtime number n_s and fault repair time t_m of each device are obtained through the timestamp technology, and the repair time refers to the time from the occurrence of a fault to the restoration of normal operation of each device; then, the monitoring sub-area circuit board production equipment operation status management index OMI is obtained through the big data analysis technology i , , n_m represents the number of maintenances that have been completed for each equipment, Tn_m represents the number of planned maintenances, and 0.01 is added to avoid the denominator being 0.

[0019] Preferably, the circuit board production equipment management decision in the circuit board production equipment management decision module includes the following steps:

[0020] Step 1: Monitor the sub-area circuit board production equipment efficiency management index PEI i Compare with the threshold PEI0 to obtain the abnormal coefficient η(PEI) of the efficiency management of the circuit board production equipment in the monitoring sub-area i , , if η(PEI) i ≥0, indicating that the efficiency management of circuit board production equipment is good; otherwise, it is judged that |η(PEI) i |Whether it is within the abnormal threshold range, if it is, it means that the efficiency management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling plan. Otherwise, it means that the efficiency management of the circuit board production equipment is good;

[0021] Step 2: Monitor the sub-area circuit board production equipment production quality management index QMI i Compare with the threshold QMI0 to obtain the abnormal coefficient η(QMI) of the production quality management of the circuit board production equipment in the monitoring sub-area i , , if η(QMI)i ≥0, indicating that the production quality management of the circuit board production equipment is good; otherwise, it is judged that |η(QMI) i |Whether it is within the abnormal threshold range, if it is, it means that the production quality management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the production quality management of the circuit board production equipment is good;

[0022] Step 3: Monitor the EMI of the energy efficiency management index of the circuit board production equipment in the sub-area i Compare with the threshold EMI0 to obtain the abnormal coefficient η(EMI) of the energy efficiency management of the circuit board production equipment in the monitoring sub-area i , , if η(EMI) i ≥0, indicating that the efficiency management of circuit board production equipment is good; otherwise, it is judged that |η(EMI) i |Whether it is within the abnormal threshold range, if it is, it means that the efficiency management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the energy efficiency management of the circuit board production equipment is good;

[0023] Step 4: Monitor the sub-area circuit board production equipment operation status management index OMI i Compare with the threshold OMI0 to obtain the abnormal coefficient η(OMI) of the operation status management of the circuit board production equipment in the monitoring sub-area i , , if η(OMI) i ≥0, indicating that the operation status of the circuit board production equipment is well managed; otherwise, it is judged that |η(OMI) i |Whether it is within the abnormal threshold range, if so, it means that the circuit board production equipment operation status management is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the circuit board production equipment operation status management is good.

[0024] Preferably, the comprehensive analysis model in the circuit board production equipment management comprehensive analysis module is: , CMI represents the comprehensive management index of circuit board production equipment, a1, a2, a3 and a4 represent the efficiency management index of circuit board production equipment in the monitoring sub-area PEI i , monitor the production quality management index QMI of the circuit board production equipment in the sub-area i , monitor the energy efficiency management index EMI of the circuit board production equipment in the sub-areai And monitor the sub-area circuit board production equipment operation status management index OMI i The weight of .

[0025] Technical effects and advantages of the present invention:

[0026] 1. The present invention realizes real-time monitoring and intelligent management of circuit board production equipment through big data technology and sensor technology, comprehensively collects multiple dimensional parameters such as equipment production efficiency, equipment production product quality, equipment production energy consumption cost and equipment production status, and provides administrators with scientific production equipment management data support, which helps to improve the operation efficiency and stability of the equipment;

[0027] 2. The present invention uses big data analysis technology to analyze the efficiency parameters of production equipment, the production quality parameters of production equipment, the energy consumption parameters of production equipment, and the operating status parameters of production equipment. The artificial intelligence system can fully and accurately understand the operating status of production equipment and the production process, thereby realizing intelligent and automated production management;

[0028] 3. The present invention uses the circuit board production equipment management decision module to timely discover anomalies and potential problems, facilitate the operation and decision-making of managers, and carry out maintenance in advance, which helps to avoid production interruptions caused by equipment failures, improve production efficiency and product quality, thereby reducing unnecessary maintenance work and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0031] See also Figure 1 As shown, the present invention provides an artificial intelligence circuit board production equipment management system, including a circuit board production equipment database, a circuit board production equipment area division module, a circuit board production equipment management data acquisition module, a circuit board production equipment management analysis module, a circuit board production equipment management decision module, a circuit board production equipment management comprehensive analysis module and a circuit board production equipment management human-computer interaction module.

[0032] The circuit board production equipment database is connected to all modules, the circuit board production equipment area division module is connected to the circuit board production equipment management data acquisition module, the circuit board production equipment management analysis module is respectively connected to the circuit board production equipment management decision module and the circuit board production equipment management data acquisition module, the circuit board production equipment management comprehensive analysis module is respectively connected to the circuit board production equipment management human-computer interaction module and the circuit board production equipment management decision module, and the circuit board production equipment management human-computer interaction module is connected to the circuit board production equipment management decision module.

[0033] Circuit board production equipment database: Through big data technology, collect and store equipment information data on the circuit board production line and existing public equipment abnormality data, and build a circuit board production equipment management database;

[0034] What needs to be specifically explained in this embodiment is that the circuit board production equipment information data includes equipment name, number, production design parameters, defect parameters, energy consumption parameters, fault parameters, and maintenance parameters; equipment abnormality data includes abnormality cause parameters and abnormality handling measures. The circuit board production equipment database is connected to the remaining modules in the system to receive and store data from each module and update the circuit board production equipment database in real time. Only authorized personnel can monitor, access and modify the parameters in the database.

[0035] Circuit board production equipment area division module: used to determine the production equipment in the circuit board production equipment management database as the target management area, and divide the target management area into several monitoring sub-areas according to each equipment, which are recorded as 1, 2, i, ..., n in sequence;

[0036] What needs to be specifically explained in this embodiment is that each device is divided into several monitoring sub-areas to obtain a unique device number for each production device, which helps to more clearly analyze the function and operating status of each device and locate the faulty device.

[0037] Circuit board production equipment management data acquisition module: used to collect data from each monitoring sub-area, obtain various monitoring parameters of circuit board production equipment management, and output various monitoring parameters to the circuit board production equipment management module;

[0038] What needs to be specifically explained in this embodiment is that the various monitoring parameters include target management area information, circuit board production equipment administrator identity authentication information, production equipment efficiency parameters, production equipment production quality parameters, production equipment energy consumption parameters and production equipment operation status parameters, among which the production equipment efficiency parameters specifically include the total number of circuit board processing completed by each device, the actual production time of each device, the length of each circuit board processing cycle, the total operation time of the production equipment and the target processing quantity of each device; the production equipment production quality parameters specifically include the number of circuit boards with defects processed by each device, the total number of circuit boards processed, the number of defect types and the total number of defect types; the production equipment energy consumption parameters specifically include the energy consumption of each device, the standby energy consumption and the total energy consumption of all devices; the production equipment operation status parameters specifically include the actual production time of each device, the fault downtime, the number of fault downtimes, the fault repair time, the number of maintenance completed by each device, and Tn_m represents the planned maintenance number.

[0039] Circuit board production equipment management and analysis module: including production equipment efficiency management and analysis unit, production equipment production quality management and analysis unit, production equipment energy consumption management and analysis unit and production equipment operation status management and analysis unit, and transmits various management indicators obtained by each analysis unit to the circuit board production equipment management decision module. Its management analysis includes the following steps:

[0040] What needs to be specifically explained in this embodiment is that the production equipment efficiency management and analysis unit is used to calculate the production equipment efficiency parameters, the production equipment production quality management and analysis unit is used to calculate the production quality parameters of the production equipment, the production equipment energy consumption management and analysis unit is used to calculate the production equipment energy consumption parameters, and the production equipment operation status management and analysis unit is used to calculate the production equipment operation status parameters.

[0041] Step 1: Production equipment efficiency management and analysis unit: During the management cycle, firstly, the total number of circuit boards processed by each device on the circuit board production line (for example, the number of circuit boards completed by the cutting machine), the actual production time of each device t_s and the length of each circuit board processing cycle t_j are obtained through sensor technology. Through the timestamp technology, the start and end time of each circuit board processing cycle is recorded to obtain t_j; then, the big data analysis technology is used to obtain the circuit board production equipment efficiency management index PEI of the monitoring sub-area i , , t0 represents the total operating time of the production equipment during the management cycle, (t_j) j represents the processing cycle time of the jth circuit board, t_T represents the management cycle time, P0 represents the target processing quantity of each device within the management cycle, c1 and c2 represent the corresponding weights, for example, c1=0.5 and c2=0.5;

[0042] What needs to be specifically explained in this embodiment is that by analyzing the production equipment efficiency parameters, the production efficiency and capacity of each device in circuit board production can be reflected. Improving equipment utilization indicates that the equipment is fully utilized; by analyzing equipment utilization and production rate, the stability and failure rate of the equipment can be indirectly evaluated.

[0043] Step 2: Production equipment production quality management and analysis unit: During the management cycle, firstly, each circuit board processed by the equipment on the production line is inspected through the circuit board defect detection technology, and the number of circuit boards with defects processed by each equipment n_d is obtained by counting, for example, the cutting machine equipment causes defects such as line gaps and dents on the circuit board, the total number of circuit boards processed P, and the number of defect types n_t on the defective circuit boards. The defective circuit boards refer to the circuit boards that fail to pass the defect detection, so as to evaluate the reliability of the production quality of each production equipment, so as to locate the faulty equipment according to the defect type and quantity; then, the production quality management index QMI of the circuit board production equipment in the monitoring sub-area is obtained through big data analysis technology. i , , n_t0 represents the total number of defect types that will occur in each device in the circuit board production equipment management database, b1 and b2 represent the corresponding weights, for example, b1=0.5 and b2=0.5;

[0044] What needs to be specifically explained in this embodiment is that by analyzing the production quality parameters of the production equipment, the quality management level of the circuit board production equipment can be evaluated. The circuit board defect rate helps managers to find problems in time, adjust equipment production parameters, and reduce the number of defective circuit boards; by carefully classifying and counting defect types, managers can fully understand the quality management status of production equipment, discover potential problems in time, and take corresponding improvement measures.

[0045] Step 3: Production equipment energy consumption management and analysis unit: During the management cycle, firstly, the energy consumption W of each device is obtained through sensor technology, including standby energy consumption and production energy consumption. The standby energy consumption refers to the energy consumption of the equipment when it is running but not producing and processing, and the production energy consumption refers to the energy consumption of the equipment when it is running and producing and processing. Energy consumption refers to the electric energy used, and the standby energy consumption S_W of the equipment is obtained; then, the energy consumption efficiency management index EMI of the circuit board production equipment in the monitoring sub-area is obtained through big data analysis technology. i , , T_W represents the total energy consumption of all devices, S_W represents the standby energy consumption of each device;

[0046] What needs to be specifically explained in this embodiment is that by analyzing the energy consumption parameters of production equipment, the energy efficiency level of the equipment can be evaluated and the reasons for low energy efficiency can be found out; by monitoring the energy consumption of each device, high-energy consumption equipment can be identified, and then energy-saving measures can be taken or production arrangements can be optimized, signs of equipment failure can be discovered in time, maintenance can be carried out in advance, and production interruptions can be avoided.

[0047] Step 4: Production equipment operation status management and analysis unit: During the management cycle, firstly, the actual production time t_s, fault downtime t_t, fault downtime number n_s and fault repair time t_m of each device are obtained through timestamp technology. The repair time refers to the time from the occurrence of a fault to the restoration of normal operation of each device; then, the operation status management index OMI of the circuit board production equipment in the monitoring sub-area is obtained through big data analysis technology. i , , n_m represents the number of maintenances completed for each equipment, Tn_m represents the number of planned maintenances, and 0.01 is added to avoid the denominator being 0;

[0048] What needs to be specifically explained in this embodiment is that by analyzing the operating status parameters of the production equipment, real-time monitoring and early warning of the equipment operating status can be achieved, and potential faults can be discovered in time; by analyzing the number and time of fault downtime, the weak links in equipment maintenance can be identified, and targeted maintenance strategies can be formulated, thereby improving the level of intelligence of equipment management.

[0049] Circuit board production equipment management decision module: used to compare the various management indicators of circuit board production equipment obtained by the management analysis module with the threshold value, and issue an early warning and generate a management decision strategy to the circuit board production equipment management human-computer interaction module based on the abnormal comparison results, and transmit the normal comparison results to the circuit board production equipment management comprehensive analysis module. The circuit board production equipment management decision includes the following steps:

[0050] Step 1: Monitor the sub-area circuit board production equipment efficiency management index PEI i Compare with the threshold PEI0 to obtain the abnormal coefficient η(PEI) of the efficiency management of the circuit board production equipment in the monitoring sub-area i , , if η(PEI) i ≥0, indicating that the efficiency management of circuit board production equipment is good; otherwise, it is judged that |η(PEI) i |Whether it is within the abnormal threshold range. If so, it indicates that the efficiency management of the circuit board production equipment is abnormal. An early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling plan. For example, if the abnormal cause is a decrease in the processing quantity, the abnormal handling plan is to increase the equipment running speed. Otherwise, it means that the efficiency management of the circuit board production equipment is good;

[0051] Step 2: Monitor the sub-area circuit board production equipment production quality management index QMI i Compare with the threshold QMI0 to obtain the abnormal coefficient η(QMI) of the production quality management of the circuit board production equipment in the monitoring sub-area i , , if η(QMI) i ≥0, indicating that the production quality management of the circuit board production equipment is good; otherwise, it is judged that |η(QMI) i |Whether it is within the abnormal threshold range, if it is, it means that the production quality management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the production quality management of the circuit board production equipment is good;

[0052] Step 3: Monitor the EMI of the energy efficiency management index of the circuit board production equipment in the sub-area i Compare with the threshold EMI0 to obtain the abnormal coefficient η(EMI) of the energy efficiency management of the circuit board production equipment in the monitoring sub-area i , , if η(EMI) i ≥0, indicating that the efficiency management of circuit board production equipment is good; otherwise, it is judged that |η(EMI) i |Whether it is within the abnormal threshold range, if it is, it means that the efficiency management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the energy efficiency management of the circuit board production equipment is good;

[0053] Step 4: Monitor the sub-area circuit board production equipment operation status management index OMI i Compare with the threshold OMI0 to obtain the abnormal coefficient η(OMI) of the operation status management of the circuit board production equipment in the monitoring sub-area i , , if η(OMI) i ≥0, indicating that the operation status of the circuit board production equipment is well managed; otherwise, it is judged that |η(OMI) i |Whether it is within the abnormal threshold range. If so, it means that the operation status management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the operation status management of the circuit board production equipment is good;

[0054] Circuit board production equipment management comprehensive analysis module: used to comprehensively analyze the normal comparison results obtained by the management decision module, obtain the comprehensive management indicators of circuit board production equipment, and transmit them to the circuit board production equipment management human-computer interaction module. Its comprehensive analysis model is: , CMI represents the comprehensive management index of circuit board production equipment, a1, a2, a3 and a4 represent the efficiency management index of circuit board production equipment in the monitoring sub-area PEIi , monitor the production quality management index QMI of the circuit board production equipment in the sub-area i , monitor the energy efficiency management index EMI of the circuit board production equipment in the sub-area i And monitor the sub-area circuit board production equipment operation status management index OMI i weights, for example, a1=0.3, a2=0.2, a3=0.3, and a4=0.2;

[0055] Circuit board production equipment management human-computer interaction module: used to receive early warning information and management decision strategies from the management decision module, as well as the comprehensive management indicators of circuit board production equipment from the management comprehensive analysis module, and conduct human-computer interaction, and perform corresponding equipment maintenance according to the early warning information and management decision strategies; according to the comprehensive management indicators of circuit board production equipment, judge whether it belongs to the threshold range, if so, it means that the circuit board production equipment is well managed, otherwise, the administrator is prompted to take timely measures, such as conducting a comprehensive inspection of the equipment, adjusting the production plan and equipment configuration, so as to improve the overall production efficiency.

[0056] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0057] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An artificial intelligence circuit board production equipment management system, characterized by: include: Circuit board production equipment database: Through big data technology, collect and store equipment information data on the circuit board production line and existing public equipment abnormality data, and build a circuit board production equipment management database; Circuit board production equipment area division module: used to determine the production equipment in the circuit board production equipment management database as the target management area, and divide the target management area into several monitoring sub-areas according to each equipment, which are recorded as 1, 2, i, ..., n in sequence; Circuit board production equipment management data acquisition module: used to collect data from each monitoring sub-area, obtain various monitoring parameters of circuit board production equipment management, and output various monitoring parameters to the circuit board production equipment management module; Circuit board production equipment management and analysis module: including production equipment efficiency management and analysis unit, production equipment production quality management and analysis unit, production equipment energy consumption management and analysis unit and production equipment operation status management and analysis unit, and transmits various management indicators obtained by each analysis unit to the circuit board production equipment management decision module; Circuit board production equipment management decision module: used to compare the various management indicators of the circuit board production equipment obtained by the management analysis module with the threshold value, and issue an early warning and generate a management decision strategy to the circuit board production equipment management human-computer interaction module based on the abnormal comparison results, and transmit the normal comparison results to the circuit board production equipment management comprehensive analysis module; Circuit board production equipment management comprehensive analysis module: used to comprehensively analyze the normal comparison results obtained by the management decision module, obtain the comprehensive management indicators of circuit board production equipment, and transmit them to the circuit board production equipment management human-computer interaction module; Circuit board production equipment management human-computer interaction module: used to receive early warning information and management decision strategies from the management decision module, as well as receive comprehensive management indicators of circuit board production equipment from the management comprehensive analysis module, and perform human-computer interaction.

2. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The monitoring parameters in the circuit board production equipment management data acquisition module include target management area information, circuit board production equipment administrator identity authentication information, production equipment efficiency parameters, production equipment production quality parameters, production equipment energy consumption parameters and production equipment operation status parameters, among which the production equipment efficiency parameters specifically include the total number of circuit board processing completed by each device, the actual production time of each device, the length of each circuit board processing cycle, the total operating time of the production equipment and the target processing quantity of each device; the production equipment production quality parameters specifically include the number of circuit boards with defects processed by each device, the total number of circuit boards processed, the number of defect types and the total number of defect types; the production equipment energy consumption parameters specifically include the energy consumption of each device, the standby energy consumption and the total energy consumption of all devices; the production equipment operation status parameters specifically include the actual production time of each device, the fault downtime, the number of fault downtimes, the fault repair time, the number of maintenance completed by each device, and Tn_m represents the planned maintenance number.

3. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The production equipment efficiency management and analysis unit in the circuit board production equipment management and analysis module: within the management cycle, firstly, the total number of circuit board processing completed by each device on the circuit board production line P, the actual production time of each device t_s and the length of each circuit board processing cycle t_j are obtained through sensor technology, and the start and end time of each circuit board processing cycle are recorded through timestamp technology to obtain t_j; then, the circuit board production equipment efficiency management index PEI of the monitoring sub-area is obtained through big data analysis technology. i , , t0 represents the total operating time of the production equipment during the management cycle, (t_j) j represents the processing cycle length of the jth circuit board, P0 represents the target processing quantity of each device within the management cycle, and c1 and c2 represent the corresponding weights respectively.

4. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The production equipment production quality management and analysis unit in the circuit board production equipment management and analysis module: within the management cycle, firstly, each circuit board processed by the equipment on the production line is detected by the circuit board defect detection technology, and the number of circuit boards with defects processed by each equipment n_d, the total number of circuit boards processed P, and the number of defect types of defective circuit boards n_t are obtained by statistics, and the defective circuit board refers to the circuit board that fails to pass the defect detection; then the production quality management index QMI of the circuit board production equipment in the monitoring sub-area is obtained by big data analysis technology. i , , n_t0 represents the total number of defect types that will occur in each device in the circuit board production equipment management database, and b1 and b2 represent the corresponding weights respectively.

5. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The production equipment energy consumption management and analysis unit in the circuit board production equipment management and analysis module: during the management cycle, firstly, the energy consumption W of each device is obtained through sensor technology, including standby energy consumption and production energy consumption. The standby energy consumption refers to the energy consumption of the equipment when it is running but not producing and processing, and the production energy consumption refers to the energy consumption of the equipment when it is running and producing and processing. Energy consumption refers to the electric energy used, and the standby energy consumption S_W of the equipment is obtained; then, the energy consumption efficiency management index EMI of the circuit board production equipment in the monitoring sub-area is obtained through big data analysis technology i , , T_W represents the total energy consumption of all devices, and S_W represents the standby energy consumption of each device.

6. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The circuit board production equipment management and analysis module production equipment operation status management and analysis unit: within the management cycle, firstly, the actual production time t_s, fault downtime t_t, fault downtime number n_s and fault repair time t_m of each device are obtained through the timestamp technology, and the repair time refers to the time from the occurrence of a fault to the restoration of normal operation of each device; then, the monitoring sub-area circuit board production equipment operation status management index OMI is obtained through the big data analysis technology. i , , n_m represents the number of maintenances that have been completed for each equipment, Tn_m represents the number of planned maintenances, and 0.01 is added to avoid the denominator being 0.

7. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The circuit board production equipment management decision module includes the following steps: Step 1: Monitor the sub-area circuit board production equipment efficiency management index PEI i Compare with the threshold PEI0 to obtain the abnormal coefficient η(PEI) of the efficiency management of the circuit board production equipment in the monitoring sub-area i , , if η(PEI) i ≥0, indicating that the efficiency management of circuit board production equipment is good; otherwise, it is judged that |η(PEI) i |Whether it is within the abnormal threshold range, if it is, it means that the efficiency management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling plan. Otherwise, it means that the efficiency management of the circuit board production equipment is good; Step 2: Monitor the sub-area circuit board production equipment production quality management index QMI i Compare with the threshold QMI0 to obtain the abnormal coefficient η(QMI) of the production quality management of the circuit board production equipment in the monitoring sub-area i , , if η(QMI) i ≥0, indicating that the production quality management of the circuit board production equipment is good; otherwise, it is judged that |η(QMI) i |Whether it is within the abnormal threshold range, if it is, it means that the production quality management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the production quality management of the circuit board production equipment is good; Step 3: Monitor the EMI of the energy efficiency management index of the circuit board production equipment in the sub-area i Compare with the threshold EMI0 to obtain the abnormal coefficient η(EMI) of the energy efficiency management of the circuit board production equipment in the monitoring sub-area i , , if η(EMI) i ≥0, indicating that the efficiency management of circuit board production equipment is good; otherwise, it is judged that |η(EMI) i |Whether it is within the abnormal threshold range, if it is, it means that the efficiency management of the circuit board production equipment is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the energy efficiency management of the circuit board production equipment is good; Step 4: Monitor the sub-area circuit board production equipment operation status management index OMI i Compare with the threshold OMI0 to obtain the abnormal coefficient η(OMI) of the operation status management of the circuit board production equipment in the monitoring sub-area i , , if η(OMI) i ≥0, indicating that the operation status of the circuit board production equipment is well managed; otherwise, it is judged that |η(OMI) i |Whether it is within the abnormal threshold range, if so, it means that the circuit board production equipment operation status management is abnormal, an early warning is issued, and the management decision strategy is obtained from the circuit board production equipment management database. The management decision strategy includes the equipment name, number, abnormal cause and abnormal handling measures. Otherwise, it means that the circuit board production equipment operation status management is good.

8. The artificial intelligence circuit board production equipment management system according to claim 1, characterized in that: The comprehensive analysis model in the circuit board production equipment management comprehensive analysis module is: , CMI represents the comprehensive management index of circuit board production equipment, a1, a2, a3 and a4 represent the efficiency management index of circuit board production equipment in the monitoring sub-area PEI i , monitor the production quality management index QMI of the circuit board production equipment in the sub-area i , monitor the energy efficiency management index EMI of the circuit board production equipment in the sub-area i And monitor the sub-area circuit board production equipment operation status management index OMI i The weight of .

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