Unmanned workshop data processing system based on data analysis

Abstract

The invention discloses an unmanned workshop data processing system based on data analysis, particularly relates to the technical field of big data, and comprises a monitoring area determination module, a data acquisition module, a data preprocessing module, a data analysis module, a quality evaluation module, a judgment module and a man-machine interaction module. The monitoring area determination module is used for determining a single sub-time monitoring area and a single PCB monitoring area; the data acquisition module is used for acquiring a first unmanned workshop key information value; the data preprocessing module is used for obtaining a second unmanned workshop key information value; the data analysis module is used for performing data processing on the second unmanned workshop key information value to obtain a third unmanned workshop key information value; the quality evaluation module is used for constructing a quality evaluation model to obtain a PCB manufacturing comprehensive evaluation value; the judgment module judges whether the manufacturing of the PCB meets the standard or not; and the man-machine interaction module is used for providing a visual interface. The production efficiency of an unmanned workshop is effectively improved, and the qualified rate of PCBs is improved.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and more specifically, to an unmanned workshop data processing system based on data analysis. Background Art

[0002] With the intensification of globalization and market competition, industrial manufacturing has higher and higher requirements for production efficiency, product quality and cost control. Traditional manual inspection and quality control methods can no longer meet the needs of modern industrial manufacturing. The development of information technology provides technical support for the realization of unmanned workshop data processing systems. The rapid development of technologies such as sensors, the Internet of Things, cloud computing, and big data has made data collection, storage, analysis, and application more convenient and efficient. With the popularization of information and intelligent products, the electronic information industry has developed rapidly. As one of the core components of electronic products, the demand for PCB has also increased.

[0003] A traditional data processing system for unmanned workshops based on data analysis includes data acquisition module, data storage module, data processing module, data monitoring and alarm module, production scheduling module and quality management module. The data acquisition module is used to collect various types of data in the PCB manufacturing process; the data storage module is used to store the collected data to ensure the integrity and security of the data; the data processing module is used to clean, organize and analyze the collected data; the data monitoring and alarm module is used to monitor the key data in the production process in real time; the production scheduling module is used to automatically adjust the production line schedule and resource allocation according to real-time data and production plans; the quality management module is used to monitor and analyze the quality data in the production process to ensure that the product quality meets the standards. It has the advantages of clear data structure, fast and stable processing speed, relatively low cost and easy implementation and management.

[0004] However, in actual use, it still has some shortcomings, such as the collected data is not comprehensive enough. The parameters in the unmanned workshop collected by the traditional unmanned workshop data processing system based on data analysis are not comprehensive enough and cannot accurately reflect the actual situation of PCB production, resulting in inaccurate subsequent parameter analysis; the comprehensive capabilities of PCB production and performance are not evaluated, and it is impossible to provide timely feedback on the PCB production situation and whether the PCB board meets the standards. 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 unmanned workshop data processing system based on data analysis, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solutions: a data processing system for an unmanned workshop based on data analysis, comprising a system operation database, a system central processor and a user information terminal, and also comprising: a monitoring area determination module, a data acquisition module, a data preprocessing module, a data analysis module, a quality assessment module, a judgment module and a human-computer interaction module;

[0007] The system operation database includes all data information of the unmanned workshop data processing system, and collects data information output by each module in real time; the system central processor is used to centrally control the information text instructions output by each module; the user information terminal is a device for receiving information output by the unmanned workshop data processing system;

[0008] The monitoring area determination module is used to determine a single sub-time monitoring area and a single PCB board monitoring area, and divides the time of monitoring the unmanned workshop into single sub-time monitoring areas according to equal time lengths, which are marked as 1, 2, ..., i, ..., n in sequence, and the monitored PCB boards are marked as 1, 2, ..., j, ..., k in sequence;

[0009] The data acquisition module is used to collect key information values ​​of the first unmanned workshop, including a production and manufacturing parameter acquisition unit and a process performance parameter acquisition unit. The key information values ​​of the first unmanned workshop include production and manufacturing parameters and process performance parameters, and the collected data are transmitted to the data preprocessing module;

[0010] The data preprocessing module is used to perform data preprocessing on the key information value of the first unmanned workshop to obtain the key information value of the second unmanned workshop, including a production parameter preprocessing unit and a process performance parameter preprocessing unit, and transmit the result to the data analysis module;

[0011] The data analysis module is used to process the key information value of the second unmanned workshop to obtain the key information value of the third unmanned workshop, including a production parameter analysis unit and a process performance parameter analysis unit, and transmit the result to the quality assessment module;

[0012] The quality assessment module is used to construct a quality assessment model, comprehensively process and analyze the key information values ​​of the third unmanned workshop, obtain a comprehensive assessment value of PCB manufacturing, and pass the result to the judgment module;

[0013] The judgment module is used to construct a PCB manufacturing comprehensive evaluation standard value, compare the PCB manufacturing comprehensive evaluation value with the PCB manufacturing comprehensive evaluation standard value, judge whether the PCB manufacturing meets the standard, and pass the result to the human-computer interaction module;

[0014] The human-computer interaction module is used to provide a visual interface, display the parameter information monitored by the unmanned workshop in real time, and send it to the user information terminal at the same time.

[0015] Preferably, the production and manufacturing parameters include equipment status parameters and production environment parameters. The equipment status parameters specifically include production efficiency, equipment energy consumption, equipment vibration frequency, equipment operating time and fault occurrence frequency, which are marked as η, W, f1, t1 and f2 respectively; the production environment parameters specifically include workshop temperature, workshop humidity, dust particle concentration and light intensity, which are marked as T1, RH, C and E respectively.

[0016] Preferably, the process performance parameters include process material parameters and quality performance parameters. The process material parameters specifically include copper foil thickness, hole size, hole position accuracy and welding time, which are marked as D, l, Δ and t2 respectively; and specifically include thermal expansion coefficient, PCB decomposition temperature, dielectric constant and loss factor, which are marked as α, T2, ε and tanδ respectively.

[0017] Preferably, the manufacturing parameter preprocessing unit is used to establish a manufacturing parameter preprocessing model, import the equipment state parameters and the production environment parameters into the manufacturing parameter preprocessing model, calculate the equipment state evaluation value and the production environment evaluation value, and the equipment state evaluation value is specifically expressed as: , y1 represents the equipment status evaluation value of the target monitoring unmanned workshop, η represents the production efficiency of the target monitoring unmanned workshop, W i represents the equipment energy consumption of the i-th sub-time monitoring area of ​​the target monitoring unmanned workshop, f1 represents the equipment vibration frequency of the target monitoring unmanned workshop, t1 represents the equipment running time of the target monitoring unmanned workshop, f2 represents the fault frequency of the target monitoring unmanned workshop, a1, a2, a3, a4 and a5 represent the influence coefficients of production efficiency, equipment energy consumption, equipment vibration frequency, equipment running time and fault frequency on the equipment status evaluation value respectively, c1 is a known constant; the production environment evaluation value is specifically expressed as: , y2 represents the production environment assessment value of the target monitored unmanned workshop, T1 represents the workshop temperature of the target monitored unmanned workshop, RH represents the workshop humidity of the target monitored unmanned workshop, C represents the dust particle concentration of the target monitored unmanned workshop, E represents the light intensity of the target monitored unmanned workshop, b1, b2, b3 and b4 represent the influence coefficients of workshop temperature, workshop humidity, dust particle concentration and light intensity on the production environment assessment value respectively, and c2, c3 and c4 are known constants.

[0018] Preferably, the process performance parameter preprocessing unit is used to establish a process performance parameter preprocessing model, import process material parameters and quality performance parameters into the process performance parameter preprocessing model, calculate the process material evaluation value and the quality performance evaluation value, and the process material evaluation value is specifically expressed as: , y3 represents the process material evaluation value of the target monitoring unmanned workshop, D represents the copper foil thickness of the target monitoring PCB board, l represents the aperture size of the target monitoring PCB board, l 标 represents the standard aperture size of the target monitoring PCB board, Δ represents the hole position accuracy of the target monitoring PCB board, and t 2j represents the welding time of the jth target monitoring board, μ1, μ2, μ3 and μ4 respectively represent the influence coefficients of copper foil thickness, hole size, hole position accuracy and welding time on the process material evaluation value, and d1 is a known constant; the quality performance evaluation value is specifically expressed as: , y4 represents the quality performance evaluation value of the target monitoring unmanned workshop, α i represents the thermal expansion coefficient of the i-th sub-time monitoring area of ​​the target monitored unmanned workshop, T2 represents the PCB decomposition temperature of the target monitored unmanned workshop, ε represents the dielectric constant of the target monitored unmanned workshop, tanδ represents the loss factor of the target monitored unmanned workshop, σ1, σ2, σ3 and σ4 respectively represent the influence coefficients of thermal expansion coefficient, PCB decomposition temperature, dielectric constant and loss factor on the quality performance evaluation value.

[0019] Preferably, the manufacturing parameter analysis unit is used to establish a manufacturing parameter analysis model, import the equipment status evaluation value and the production environment evaluation value into the manufacturing parameter analysis model, and calculate the manufacturing evaluation value, which is specifically expressed as: ,y p represents the production and manufacturing evaluation value of the target monitored unmanned workshop, y1 represents the equipment status evaluation value of the target monitored unmanned workshop, y2 represents the production environment evaluation value of the target monitored unmanned workshop, ρ1 and ρ2 respectively represent the influence coefficients of the equipment status evaluation value and the production environment evaluation value on the production and manufacturing evaluation value.

[0020] Preferably, the process performance parameter analysis unit is used to establish a process performance parameter analysis model, import the process material evaluation value and the quality performance evaluation value into the process performance parameter analysis model, and calculate the process performance evaluation value, which is specifically expressed as: ,y c represents the process performance evaluation value of the target monitoring unmanned workshop, y3 represents the process material evaluation value of the target monitoring unmanned workshop, y4 represents the quality performance evaluation value of the target monitoring unmanned workshop, ω1 and ω2 represent the influence coefficients of the process material evaluation value and the quality performance evaluation value on the process performance evaluation value, respectively.

[0021] Preferably, the acquisition of the PCB manufacturing comprehensive evaluation value is to import the production and manufacturing evaluation value and the process performance evaluation value into the quality evaluation model to calculate the PCB manufacturing comprehensive evaluation value, which is specifically expressed as: , φ represents the comprehensive evaluation value of PCB manufacturing in the unmanned workshop under target monitoring, y p represents the production and manufacturing evaluation value of the target monitoring unmanned workshop, y c represents the process performance evaluation value of the target monitoring unmanned workshop, y p标 represents the production and manufacturing evaluation standard value of the target monitoring unmanned workshop, y c标 It represents the standard value of process performance evaluation of the target monitored unmanned workshop.

[0022] Preferably, the PCB manufacturing comprehensive evaluation standard value is marked as φ 标 , when φ>φ 标 When φ<φ, it means that the comprehensive evaluation value of PCB manufacturing is greater than the standard value of comprehensive evaluation of PCB manufacturing, and the production process and quality of PCB meet the standards; when φ<φ 标 When , it means that the comprehensive evaluation value of PCB manufacturing is less than the standard value of comprehensive evaluation of PCB manufacturing, and the production process and quality of PCB do not meet the standards.

[0023] Preferably, the visualization interface should include a menu bar, a toolbar, a status bar and a work area, wherein the work area should display the parameters of the target monitoring workshop and the production parameters of the PCB in real time, and send the information to the user information terminal synchronously.

[0024] Technical effects and advantages of the present invention:

[0025] 1. The present invention collects the key information values ​​of the first unmanned workshop through the production and manufacturing parameter collection unit and the process performance parameter collection unit of the data collection module, specifically including equipment status parameters, production environment parameters, process material parameters and quality performance parameters, and determines the single sub-time monitoring area and the single PCB board monitoring area through the monitoring area determination module, and comprehensively collects the parameters in the process of making PCB boards in the unmanned workshop, providing effective data support for subsequent analysis and processing;

[0026] 2. The present invention calculates the equipment status evaluation value, production environment evaluation value, process material evaluation value, quality performance evaluation value, production manufacturing evaluation value, process performance evaluation value and PCB manufacturing comprehensive evaluation value through the data preprocessing module, the data analysis module and the quality evaluation module, accurately reflects the real-time status of the PCB board manufacturing process in the unmanned workshop, and judges whether the PCB board meets the standards through the judgment and early warning module, thereby improving the accuracy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the system structure of the present invention.

[0028] Figure 2 It is a schematic diagram of the process steps of the present invention. DETAILED DESCRIPTION

[0029] 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.

[0030] As attached Figure 1 The unmanned workshop data processing system based on data analysis shown includes a system operation database, a system central processing unit and a user information terminal, and also includes a monitoring area determination module, a data acquisition module, a data preprocessing module, a data analysis module, a quality assessment module, a judgment module and a human-computer interaction module.

[0031] The output end of the monitoring area determination module is telecommunication connected to the input end of the data acquisition module, the output end of the data acquisition module is telecommunication connected to the input end of the data preprocessing module, the output end of the data preprocessing module is telecommunication connected to the input end of the data analysis module, the output end of the data analysis module is telecommunication connected to the input end of the quality assessment module, the output end of the quality assessment module is telecommunication connected to the input end of the judgment module, the output end of the judgment module is telecommunication connected to the input end of the human-computer interaction module, the output end of the system central processing unit is telecommunication connected to the input end of each module, and the output end of each module is telecommunication connected to the input end of the system operation database.

[0032] The system operation database includes all data information of the unmanned workshop data processing system, and collects data information output by each module in real time; the system central processor is used to control the information text instructions output by each module; the user information terminal is an information output device for receiving the unmanned workshop data processing system.

[0033] Monitoring area determination module: Determine a single sub-time monitoring area and a single PCB board monitoring area, divide the time for monitoring the unmanned workshop into single sub-time monitoring areas according to equal time lengths, mark them as 1, 2, ..., i, ..., n in sequence, and mark the monitored PCB boards as 1, 2, ..., j, ..., k in sequence.

[0034] Data acquisition module: collects key information values ​​of the first unmanned workshop, including a production and manufacturing parameter acquisition unit and a process performance parameter acquisition unit. The key information values ​​of the first unmanned workshop include production and manufacturing parameters and process performance parameters, and passes the collected data to the data preprocessing module.

[0035] Furthermore, the production and manufacturing parameters include equipment status parameters and production environment parameters. The equipment status parameters specifically include production efficiency, equipment energy consumption, equipment vibration frequency, equipment operating time and fault occurrence frequency, which are marked as η, W, f1, t1 and f2 respectively; the production environment parameters specifically include workshop temperature, workshop humidity, dust particle concentration and light intensity, which are marked as T1, RH, C and E respectively.

[0036] What needs to be specifically explained in this embodiment is that the production efficiency is calculated by production efficiency = actual output / standard output; the equipment energy consumption of the target monitored unmanned workshop is calculated by equipment energy consumption = equipment power × usage time; the calculation of the frequency of faults requires measuring the number of faults and the total operating time. The number of faults refers to the total number of equipment failures in the unmanned workshop within a specific time period, and the total operating time refers to the total operating time of all equipment in the unmanned workshop within a specific time period.

[0037] Furthermore, the process performance parameters include process material parameters and quality performance parameters. The process material parameters specifically include copper foil thickness, hole size, hole position accuracy and welding time, which are marked as D, l, Δ and t2 respectively; specifically include thermal expansion coefficient, PCB decomposition temperature, dielectric constant and loss factor, which are marked as α, T2, ε and tanδ respectively.

[0038] What needs to be specifically explained in this embodiment is that the dimensional change of the PCB board under temperature change is measured by an experimental method to obtain its thermal expansion coefficient. The experimental method includes an expansion cantilever beam method and a thermal expansion coefficient meter method, which requires professional equipment and precise experimental steps; a network analyzer is used to measure the dielectric constant of the PCB board, a test sample of standard size is prepared, and the test parameters are set. By measuring the S parameters of the circuit, the transmission line parameters of the sample can be obtained and the dielectric constant can be calculated.

[0039] Data preprocessing module: perform data preprocessing on the key information values ​​of the first unmanned workshop to obtain the key information values ​​of the second unmanned workshop, including a production and manufacturing parameter preprocessing unit and a process performance parameter preprocessing unit, and pass the results to the data analysis module.

[0040] Furthermore, the manufacturing parameter preprocessing unit is used to establish a manufacturing parameter preprocessing model, import the equipment state parameters and the production environment parameters into the manufacturing parameter preprocessing model, and calculate the equipment state evaluation value and the production environment evaluation value. The equipment state evaluation value is specifically expressed as: , y1 represents the equipment status evaluation value of the target monitoring unmanned workshop, η represents the production efficiency of the target monitoring unmanned workshop, W irepresents the equipment energy consumption of the i-th sub-time monitoring area of ​​the target monitoring unmanned workshop, f1 represents the equipment vibration frequency of the target monitoring unmanned workshop, t1 represents the equipment running time of the target monitoring unmanned workshop, f2 represents the fault frequency of the target monitoring unmanned workshop, a1, a2, a3, a4 and a5 represent the influence coefficients of production efficiency, equipment energy consumption, equipment vibration frequency, equipment running time and fault frequency on the equipment status evaluation value respectively, c1 is a known constant; the production environment evaluation value is specifically expressed as: , y2 represents the production environment assessment value of the target monitored unmanned workshop, T1 represents the workshop temperature of the target monitored unmanned workshop, RH represents the workshop humidity of the target monitored unmanned workshop, C represents the dust particle concentration of the target monitored unmanned workshop, E represents the light intensity of the target monitored unmanned workshop, b1, b2, b3 and b4 represent the influence coefficients of workshop temperature, workshop humidity, dust particle concentration and light intensity on the production environment assessment value respectively, and c2, c3 and c4 are known constants.

[0041] Furthermore, the process performance parameter preprocessing unit is used to establish a process performance parameter preprocessing model, import process material parameters and quality performance parameters into the process performance parameter preprocessing model, and calculate the process material evaluation value and the quality performance evaluation value. The process material evaluation value is specifically expressed as: , y3 represents the process material evaluation value of the target monitoring unmanned workshop, D represents the copper foil thickness of the target monitoring PCB board, l represents the aperture size of the target monitoring PCB board, l 标 represents the standard aperture size of the target monitoring PCB board, Δ represents the hole position accuracy of the target monitoring PCB board, and t 2j represents the welding time of the jth target monitoring board, μ1, μ2, μ3 and μ4 respectively represent the influence coefficients of copper foil thickness, hole size, hole position accuracy and welding time on the process material evaluation value, and d1 is a known constant; the quality performance evaluation value is specifically expressed as: , y4 represents the quality performance evaluation value of the target monitoring unmanned workshop, α i represents the thermal expansion coefficient of the i-th sub-time monitoring area of ​​the target monitored unmanned workshop, T2 represents the PCB decomposition temperature of the target monitored unmanned workshop, ε represents the dielectric constant of the target monitored unmanned workshop, tanδ represents the loss factor of the target monitored unmanned workshop, σ1, σ2, σ3 and σ4 respectively represent the influence coefficients of thermal expansion coefficient, PCB decomposition temperature, dielectric constant and loss factor on the quality performance evaluation value.

[0042] Data analysis module: Process the key information values ​​of the second unmanned workshop to obtain the key information values ​​of the third unmanned workshop, including the production and manufacturing parameter analysis unit and the process performance parameter analysis unit, and pass the results to the quality assessment module.

[0043] Furthermore, the manufacturing parameter analysis unit is used to establish a manufacturing parameter analysis model, import the equipment status evaluation value and the production environment evaluation value into the manufacturing parameter analysis model, and calculate the manufacturing evaluation value, which is specifically expressed as: ,y p represents the production and manufacturing evaluation value of the target monitored unmanned workshop, y1 represents the equipment status evaluation value of the target monitored unmanned workshop, y2 represents the production environment evaluation value of the target monitored unmanned workshop, ρ1 and ρ2 respectively represent the influence coefficients of the equipment status evaluation value and the production environment evaluation value on the production and manufacturing evaluation value.

[0044] Furthermore, the process performance parameter analysis unit is used to establish a process performance parameter analysis model, import the process material evaluation value and the quality performance evaluation value into the process performance parameter analysis model, and calculate the process performance evaluation value, which is specifically expressed as: ,y c represents the process performance evaluation value of the target monitoring unmanned workshop, y3 represents the process material evaluation value of the target monitoring unmanned workshop, y4 represents the quality performance evaluation value of the target monitoring unmanned workshop, ω1 and ω2 respectively represent the influence coefficients of the process material evaluation value and the quality performance evaluation value on the process performance evaluation value.

[0045] Quality assessment module: Build a quality assessment model, comprehensively process and analyze the key information values ​​of the third unmanned workshop, obtain the comprehensive assessment value of PCB manufacturing, and pass the results to the judgment module.

[0046] Furthermore, the comprehensive evaluation value of PCB manufacturing is obtained by importing the production evaluation value and the process performance evaluation value into the quality evaluation model to calculate the comprehensive evaluation value of PCB manufacturing, which is specifically expressed as: , φ represents the comprehensive evaluation value of PCB manufacturing in the unmanned workshop under target monitoring, y p represents the production and manufacturing evaluation value of the target monitoring unmanned workshop, y c represents the process performance evaluation value of the target monitoring unmanned workshop, y p标 represents the production and manufacturing evaluation standard value of the target monitoring unmanned workshop, y c标 It represents the standard value of process performance evaluation of the target monitored unmanned workshop.

[0047] Judgment module: constructs the PCB manufacturing comprehensive evaluation standard value, compares the PCB manufacturing comprehensive evaluation value with the PCB manufacturing comprehensive evaluation standard value, judges whether the PCB manufacturing meets the standard, and passes the result to the human-computer interaction module.

[0048] Furthermore, the PCB manufacturing comprehensive evaluation standard value is marked as φ 标 , when φ>φ 标 When φ<φ, it means that the comprehensive evaluation value of PCB manufacturing is greater than the standard value of comprehensive evaluation of PCB manufacturing, and the production process and quality of PCB meet the standards; when φ<φ 标 When , it means that the comprehensive evaluation value of PCB manufacturing is less than the standard value of PCB manufacturing comprehensive evaluation, and the production process and quality of PCB do not meet the standards.

[0049] Human-computer interaction module: provides a visual interface to display the parameter information monitored by the unmanned workshop in real time and send it to the user information terminal at the same time.

[0050] Furthermore, the visualization interface should include a menu bar, a toolbar, a status bar, and a work area, wherein the work area should display the parameters of the target monitoring workshop and the production parameters of the PCB in real time, and send the information to the user information terminal synchronously.

[0051] What needs to be specifically explained in this embodiment is that the menu bar of the visualization interface provides user navigation and setting options, including file operations, view control, and file import and export. The toolbar includes commonly used tool buttons to facilitate users to interact with the interface, and displays in real time the parameters of the target monitoring workshop and the production parameters of the PCB, including equipment status parameters, production environment parameters, process material parameters, and quality performance parameters, as well as equipment status evaluation values, production environment evaluation values, process material evaluation values, quality performance evaluation values, production and manufacturing evaluation values, process performance evaluation values, and PCB manufacturing comprehensive evaluation values.

[0052] 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;

[0053] 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 unmanned workshop data processing system based on data analysis, comprising a system operation database, a system central processor and a user information terminal, characterized in that: Also includes: Monitoring area determination module, data acquisition module, data preprocessing module, data analysis module, quality assessment module, judgment module and human-computer interaction module; The system operation database includes all data information of the unmanned workshop data processing system, and collects data information output by each module in real time; the system central processor is used to centrally control the information text instructions output by each module; the user information terminal is a device for receiving information output by the unmanned workshop data processing system; The monitoring area determination module is used to determine a single sub-time monitoring area and a single PCB board monitoring area, and divides the time of monitoring the unmanned workshop into single sub-time monitoring areas according to equal time lengths, which are marked as 1, 2, ..., i, ..., n in sequence, and the monitored PCB boards are marked as 1, 2, ..., j, ..., k in sequence; The data acquisition module is used to collect key information values ​​of the first unmanned workshop, including a production and manufacturing parameter acquisition unit and a process performance parameter acquisition unit. The key information values ​​of the first unmanned workshop include production and manufacturing parameters and process performance parameters, and the collected data are transmitted to the data preprocessing module; The data preprocessing module is used to perform data preprocessing on the key information value of the first unmanned workshop to obtain the key information value of the second unmanned workshop, including a production parameter preprocessing unit and a process performance parameter preprocessing unit, and transmit the result to the data analysis module; The data analysis module is used to process the key information value of the second unmanned workshop to obtain the key information value of the third unmanned workshop, including a production parameter analysis unit and a process performance parameter analysis unit, and transmit the result to the quality assessment module; The quality assessment module is used to construct a quality assessment model, comprehensively process and analyze the key information values ​​of the third unmanned workshop, obtain a comprehensive assessment value of PCB manufacturing, and pass the result to the judgment module; The judgment module is used to construct a PCB manufacturing comprehensive evaluation standard value, compare the PCB manufacturing comprehensive evaluation value with the PCB manufacturing comprehensive evaluation standard value, judge whether the PCB manufacturing meets the standard, and pass the result to the human-computer interaction module; The human-computer interaction module is used to provide a visual interface, display the parameter information monitored by the unmanned workshop in real time, and send it to the user information terminal at the same time.

2. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The production and manufacturing parameters include equipment status parameters and production environment parameters. The equipment status parameters specifically include production efficiency, equipment energy consumption, equipment vibration frequency, equipment operating time and fault occurrence frequency, which are marked as η, W, f1, t1 and f2 respectively; the production environment parameters specifically include workshop temperature, workshop humidity, dust particle concentration and light intensity, which are marked as T1, RH, C and E respectively.

3. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The process performance parameters include process material parameters and quality performance parameters. The process material parameters specifically include copper foil thickness, hole size, hole position accuracy and welding time, which are marked as D, l, Δ and t2 respectively; specifically include thermal expansion coefficient, PCB decomposition temperature, dielectric constant and loss factor, which are marked as α, T2, ε and tanδ respectively.

4. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The manufacturing parameter preprocessing unit is used to establish a manufacturing parameter preprocessing model, import the equipment state parameters and the production environment parameters into the manufacturing parameter preprocessing model, and calculate the equipment state evaluation value and the production environment evaluation value. The equipment state evaluation value is specifically expressed as: , y1 represents the equipment status evaluation value of the target monitoring unmanned workshop, η represents the production efficiency of the target monitoring unmanned workshop, W i represents the equipment energy consumption of the i-th sub-time monitoring area of ​​the target monitoring unmanned workshop, f1 represents the equipment vibration frequency of the target monitoring unmanned workshop, t1 represents the equipment running time of the target monitoring unmanned workshop, f2 represents the fault frequency of the target monitoring unmanned workshop, a1, a2, a3, a4 and a5 represent the influence coefficients of production efficiency, equipment energy consumption, equipment vibration frequency, equipment running time and fault frequency on the equipment status evaluation value respectively, c1 is a known constant; the production environment evaluation value is specifically expressed as: , y2 represents the production environment assessment value of the target monitored unmanned workshop, T1 represents the workshop temperature of the target monitored unmanned workshop, RH represents the workshop humidity of the target monitored unmanned workshop, C represents the dust particle concentration of the target monitored unmanned workshop, E represents the light intensity of the target monitored unmanned workshop, b1, b2, b3 and b4 represent the influence coefficients of workshop temperature, workshop humidity, dust particle concentration and light intensity on the production environment assessment value respectively, and c2, c3 and c4 are known constants.

5. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The process performance parameter preprocessing unit is used to establish a process performance parameter preprocessing model, import process material parameters and quality performance parameters into the process performance parameter preprocessing model, and calculate the process material evaluation value and the quality performance evaluation value. The process material evaluation value is specifically expressed as: , y3 represents the process material evaluation value of the target monitoring unmanned workshop, D represents the copper foil thickness of the target monitoring PCB board, l represents the aperture size of the target monitoring PCB board, l 标 represents the standard aperture size of the target monitoring PCB board, Δ represents the hole position accuracy of the target monitoring PCB board, and t 2j represents the welding time of the jth target monitoring board, μ1, μ2, μ3 and μ4 respectively represent the influence coefficients of copper foil thickness, hole size, hole position accuracy and welding time on the process material evaluation value, and d1 is a known constant; the quality performance evaluation value is specifically expressed as: , y4 represents the quality performance evaluation value of the target monitoring unmanned workshop, α i represents the thermal expansion coefficient of the i-th sub-time monitoring area of ​​the target monitored unmanned workshop, T2 represents the PCB decomposition temperature of the target monitored unmanned workshop, ε represents the dielectric constant of the target monitored unmanned workshop, tanδ represents the loss factor of the target monitored unmanned workshop, σ1, σ2, σ3 and σ4 respectively represent the influence coefficients of thermal expansion coefficient, PCB decomposition temperature, dielectric constant and loss factor on the quality performance evaluation value.

6. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The manufacturing parameter analysis unit is used to establish a manufacturing parameter analysis model, import the equipment status evaluation value and the production environment evaluation value into the manufacturing parameter analysis model, and calculate the manufacturing evaluation value, which is specifically expressed as: ,y p represents the production and manufacturing evaluation value of the target monitored unmanned workshop, y1 represents the equipment status evaluation value of the target monitored unmanned workshop, y2 represents the production environment evaluation value of the target monitored unmanned workshop, ρ1 and ρ2 respectively represent the influence coefficients of the equipment status evaluation value and the production environment evaluation value on the production and manufacturing evaluation value.

7. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The process performance parameter analysis unit is used to establish a process performance parameter analysis model, import the process material evaluation value and the quality performance evaluation value into the process performance parameter analysis model, and calculate the process performance evaluation value, which is specifically expressed as: ,y c represents the process performance evaluation value of the target monitoring unmanned workshop, y3 represents the process material evaluation value of the target monitoring unmanned workshop, y4 represents the quality performance evaluation value of the target monitoring unmanned workshop, ω1 and ω2 represent the influence coefficients of the process material evaluation value and the quality performance evaluation value on the process performance evaluation value, respectively.

8. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The PCB manufacturing comprehensive evaluation value is obtained by importing the production and manufacturing evaluation value and the process performance evaluation value into the quality evaluation model to calculate the PCB manufacturing comprehensive evaluation value, which is specifically expressed as: , φ represents the comprehensive evaluation value of PCB manufacturing in the unmanned workshop under target monitoring, y p represents the production and manufacturing evaluation value of the target monitoring unmanned workshop, y c represents the process performance evaluation value of the target monitoring unmanned workshop, y p标 represents the production and manufacturing evaluation standard value of the target monitoring unmanned workshop, y c标 It represents the standard value of process performance evaluation of the target monitored unmanned workshop.

9. The unmanned workshop data processing system based on data analysis according to claim 1 is characterized in that: The PCB manufacturing comprehensive evaluation standard value is marked as φ 标 , when φ>φ 标 When φ<φ, it means that the comprehensive evaluation value of PCB manufacturing is greater than the standard value of comprehensive evaluation of PCB manufacturing, and the production process and quality of PCB meet the standards; when φ<φ 标 When , it means that the comprehensive evaluation value of PCB manufacturing is less than the standard value of PCB manufacturing comprehensive evaluation, and the production process and quality of PCB do not meet the standards.

10. The unmanned workshop data processing system based on data analysis according to claim 1, characterized in that: The visualization interface should include a menu bar, a toolbar, a status bar and a work area, wherein the work area should display the parameters of the target monitoring workshop and the production parameters of the PCB in real time, and send the information to the user information terminal synchronously.

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