Intelligent manufacturing production line management system and method

Abstract

The invention discloses an intelligent manufacturing production line management system and method. The system comprises an Internet of Things cloud platform, a data acquisition module and a PLC module. The data acquisition module and the PLC module are wirelessly connected with the Internet of Things cloud platform; the data acquisition module is used for acquiring various types of data in a production line in real time and wirelessly transmitting the acquired data to the Internet of Things cloud platform; the Internet of Things cloud platform is used for analyzing the data acquired by the data acquisition module, evaluating the working state of the production line and transmitting a remote control instruction to the PLC module; and the PLC module is used for realizing automatic control of the production line and automatically adjusting the working state of the production line according to a control instruction received from the Internet of Things cloud platform.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing technology, and in particular to an intelligent manufacturing production line management system and method. Background Art

[0002] In recent years, with the rapid development and increasing maturity of wireless sensor technology, cloud computing, distributed real-time control technology and other fields, cyber-physical fusion systems have become one of the most cutting-edge cross-fields today. With the advancement of Industry 4.0, the research and application of intelligent manufacturing systems have received extensive attention. The realization of intelligent manufacturing production lines is the concentrated embodiment of CPS, which has brought new challenges to data collection, cleaning, fusion, and information interaction quality.

[0003] Existing intelligent manufacturing production lines generally have the following shortcomings: each functional module operates independently, lacking efficient information transmission and coordination; the system integration is low, resulting in high production line deployment and maintenance costs; there is a lack of real-time data collection and feedback mechanism for the production process, resulting in a lack of data support for management decisions, affecting the level of intelligence of the production line. Summary of the invention

[0004] In order to solve the problems raised in the above background technology, the technical solution adopted by the present invention is:

[0005] An intelligent manufacturing production line management system, including an Internet of Things cloud platform, a data acquisition module and a PLC module;

[0006] The data acquisition module and the PLC module are both wirelessly connected to the IoT cloud platform;

[0007] The data acquisition module is used to collect multiple types of data in the production line in real time and wirelessly transmit the collected data to the Internet of Things cloud platform;

[0008] The IoT cloud platform is used to analyze the data collected by the data acquisition module, evaluate the working status of the production line, and transmit remote control instructions to the PLC module;

[0009] The PLC module is used to realize automatic control of the production line and automatically adjust the working state of the production line according to the control instructions received from the Internet of Things cloud platform.

[0010] Furthermore, the data acquisition module includes a camera, an RFID identification device and a sensor device;

[0011] The camera is used to collect video data of the production line;

[0012] The RFID identification device is used to cooperate with RFID tags preset on production equipment, workpieces and work clothes of workers to collect RFID observation data;

[0013] The sensor equipment includes a temperature and humidity sensor for collecting temperature and humidity data of the production line environment, and also includes multiple types of equipment status monitoring sensors for collecting operation data of production equipment in the production line.

[0014] Furthermore, it also includes an early warning module, which is wirelessly connected to the Internet of Things cloud platform;

[0015] When the IoT cloud platform evaluates the working status of the production line, it also determines whether an alarm message needs to be issued, and if so, the alarm message is wirelessly transmitted to the early warning module;

[0016] The early warning module is used to issue an early warning after receiving the alarm information.

[0017] Further, the early warning module includes an acoustic / optical alarm device configured in the factory building;

[0018] The early warning module is also configured on the staff's smart terminal.

[0019] Another aspect of the present invention provides an intelligent manufacturing production line management method, which adopts the above-mentioned intelligent manufacturing production line management system and includes the following steps:

[0020] S1, collect various types of data in the production line through the data acquisition module, and wirelessly transmit the collected data to the Internet of Things cloud platform;

[0021] S2, analyze the collected data on the IoT cloud platform, evaluate the working status of the production line, and transmit remote control instructions to the PLC module;

[0022] S3, PLC module automatically controls the operation of the production line and automatically adjusts the working status of the production line according to the control instructions received from the IoT cloud platform.

[0023] Further, in step S1, the data acquisition module includes a camera, an RFID identification device and a sensor device;

[0024] The camera is used to collect video data of the production line;

[0025] The RFID identification device is used to cooperate with RFID tags preset on production equipment, workpieces and work clothes of workers to collect RFID observation data;

[0026] The sensor equipment includes a temperature and humidity sensor for collecting temperature and humidity data of the production line environment, and also includes multiple types of equipment status monitoring sensors for collecting operation data of production equipment in the production line.

[0027] Furthermore, in step S2, when the IoT cloud platform evaluates the working status of the production line, it also determines whether it is necessary to issue an alarm message. If so, the alarm message is wirelessly transmitted to the early warning module, and the early warning module issues an alarm after receiving the alarm message.

[0028] Further, the early warning module includes an acoustic / optical alarm device configured in the factory building;

[0029] The early warning module is also configured on the staff's smart terminal.

[0030] Furthermore, in step S2, the IoT cloud platform evaluates the working status of the production line specifically by the following method:

[0031] S21. According to the data collected by the data collection module, n evaluation indicators are selected and a data set is established. The evaluation indicator data set is represented as C = {c1, c2, ..., c i ,…,c n}, i = 1, 2, ..., n, any element c in the data set i Indicates the index value after normalization;

[0032] S22. Establish a general linear regression model:

[0033] y i =c i x i β+ε i ;

[0034] Among them, y i is the dependent variable, x i =(x i1 ,x i2 ,…,x ip ) is the p-dimensional covariate row vector, β=(β1,β2,…,β p ) T is the regression coefficient vector, ε i is a random error;

[0035] S23. Establish the following LAD-LASSO objective function:

[0036]

[0037] Among them, w i is the weight, λ j is the regularization parameter, j=1,2,…,p;

[0038] S24. Establishing Dataset

[0039] Among them, when i=1,2,…,n, we have

[0040] When i=n+1,…,n+p, define e j is a p-dimensional vector whose j-th element is 1 and the other elements are 0;

[0041] S25. The important feature selection results are obtained by the following formula:

[0042]

[0043] The important feature selection result W is compared with the preset state function to evaluate the working state of the production line, which is expressed as follows:

[0044]

[0045] Among them, d(t) is used to evaluate the working status of the current production line, f represents the state function, m1,m2,…,m n are preset parameters corresponding to the n evaluation indicators respectively.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The intelligent manufacturing production line management system and method provided by the present invention integrate technologies such as the Internet of Things, cloud computing, PLC, and RFID, and solve the problems existing in traditional intelligent manufacturing production lines, such as lack of efficient information transmission and coordination, low system integration, low intelligence level, low monitoring efficiency, and weak risk prediction capabilities; it realizes efficient coordination and data integration between different modules, and combines intelligent algorithms to evaluate the working status of the production line, which is conducive to improving production efficiency and flexibility, and enhancing the safety management and control capabilities of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of the process flow of the intelligent manufacturing production line management method provided by the present invention. DETAILED DESCRIPTION

[0049] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the following further describes how the present invention is implemented in conjunction with the accompanying drawings and specific implementation methods.

[0050] The present invention provides an intelligent manufacturing production line management system, comprising an Internet of Things cloud platform, a data acquisition module and a PLC module; the data acquisition module and the PLC module are both wirelessly connected to the Internet of Things cloud platform; the data acquisition module is used for real-time acquisition of multiple types of data in the production line, and wirelessly transmits the collected data to the Internet of Things cloud platform; the Internet of Things cloud platform is used for analyzing the data collected by the data acquisition module, evaluating the working status of the production line, and transmitting remote control instructions to the PLC module; the PLC module is used for realizing automatic control of the production line, and automatically adjusting the working status of the production line according to the control instructions received from the Internet of Things cloud platform.

[0051] Furthermore, the data acquisition module includes a camera, an RFID identification device and a sensor device; the camera is used to collect video data of the production line; the RFID identification device is used to cooperate with RFID tags preset on production equipment, workpieces and staff's work clothes to collect RFID observation data; the sensor device includes a temperature and humidity sensor for collecting temperature and humidity data of the production line environment, and also includes multiple types of equipment status monitoring sensors for collecting operation data of production equipment in the production line.

[0052] Furthermore, it also includes an early warning module, which is wirelessly connected to the Internet of Things cloud platform; when the Internet of Things cloud platform evaluates the working status of the production line, it also determines whether it is necessary to issue an alarm message. If so, the alarm message is wirelessly transmitted to the early warning module; the early warning module is used to issue an early warning after receiving the alarm message.

[0053] Furthermore, the early warning module includes an audio / visual alarm device configured in the factory building; the early warning module is also configured in the smart terminal of the staff.

[0054] Reference Figure 1 As shown, another aspect of the present invention provides a smart manufacturing production line management method, which adopts the above-mentioned smart manufacturing production line management system and includes the following steps:

[0055] S1, collect various types of data in the production line through the data acquisition module, and wirelessly transmit the collected data to the Internet of Things cloud platform;

[0056] S2, analyze the collected data on the IoT cloud platform, evaluate the working status of the production line, and transmit remote control instructions to the PLC module;

[0057] S3, PLC module automatically controls the operation of the production line and automatically adjusts the working status of the production line according to the control instructions received from the IoT cloud platform.

[0058] Further, in step S1, the data acquisition module includes a camera, an RFID identification device and a sensor device;

[0059] The camera is used to collect video data of the production line;

[0060] The RFID identification device is used to cooperate with the RFID tags preset on the production equipment, workpieces and the work clothes of the staff to collect RFID observation data;

[0061] Sensor equipment includes temperature and humidity sensors, which are used to collect temperature and humidity data of the production line environment, and also includes various types of equipment status monitoring sensors, which are used to collect operating data of production equipment in the production line.

[0062] Furthermore, in step S2, when the IoT cloud platform evaluates the working status of the production line, it also determines whether it is necessary to issue an alarm message. If so, the alarm message is wirelessly transmitted to the early warning module, and the early warning module issues an alarm after receiving the alarm message.

[0063] Further, the early warning module includes an acoustic / optical alarm device configured in the plant;

[0064] The early warning module is also configured on the staff's smart terminal.

[0065] Furthermore, in step S2, the IoT cloud platform evaluates the working status of the production line specifically by the following method:

[0066] S21. According to the data collected by the data collection module, n evaluation indicators are selected and a data set is established. The evaluation indicator data set is represented as C = {c1, c2, ..., c i ,…,c n}, i = 1, 2, ..., n, any element c in the data set i Indicates the index value after normalization;

[0067] S22. Establish a general linear regression model:

[0068] y i =c i x i β+ε i ;

[0069] Among them, y i is the dependent variable, x i =(x i1 ,x i2 ,…,x ip ) is the p-dimensional covariate row vector, β=(β1,β2,…,β p ) T is the regression coefficient vector, ε i is a random error;

[0070] S23. Establish the following LAD-LASSO objective function:

[0071]

[0072] Among them, w i is the weight, λ j is the regularization parameter, j=1,2,…,p;

[0073] S24. Establishing Dataset

[0074] Among them, when i=1,2,…,n, we have

[0075] When i=n+1,…,n+p, define e j is a p-dimensional vector whose j-th element is 1 and the other elements are 0;

[0076] S25. The important feature selection results are obtained by the following formula:

[0077]

[0078] The important feature selection result W is compared with the preset state function to evaluate the working state of the production line, which is expressed as follows:

[0079]

[0080] Among them, d(t) is used to evaluate the working status of the current production line, f represents the state function, m1,m2,…,m n are preset parameters corresponding to the n evaluation indicators respectively.

[0081] It is understandable that the selected evaluation indicators and the corresponding thresholds and state functions can be set according to the actual application scenarios combined with expert experience. For example, for the safety status of the production line, the evaluation indicators may include temperature and humidity data at different locations of the production line collected by temperature and humidity sensors; multiple types of operation data related to production safety collected by equipment status monitoring sensors; and video data of each worker on the production line collected by cameras. Each type of data collected is calculated by a preset algorithm and compared with a preset threshold to obtain a corresponding score. For sensor data, the corresponding score can be calculated directly based on the degree of proximity to the preset threshold; for the video data of the staff, it can first be trained with a deep learning algorithm model through a large number of preset video samples, and the video data can be scored by the trained model. The score value is used as the indicator value of the item, and all indicator values ​​are normalized to obtain the indicator data set C. Then, the safety status of the current production line is evaluated based on d(t) calculated by the above method.

[0082] In summary, the intelligent manufacturing production line management system and method provided by the present invention integrates technologies such as the Internet of Things, cloud computing, PLC, RFID, etc., and solves the problems existing in traditional intelligent manufacturing production lines, such as lack of efficient information transmission and coordination, low system integration, low intelligence level, low monitoring efficiency, and weak risk prediction ability; it realizes efficient coordination and data integration between different modules, and combines intelligent algorithms to evaluate the working status of the production line, which is conducive to improving production efficiency and flexibility, and enhancing the safety management and control capabilities of the production line.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. An intelligent manufacturing production line management system, characterized in that: Including IoT cloud platform, data acquisition module and PLC module; The data acquisition module and the PLC module are both wirelessly connected to the IoT cloud platform; The data acquisition module is used to collect multiple types of data in the production line in real time and wirelessly transmit the collected data to the Internet of Things cloud platform; The IoT cloud platform is used to analyze the data collected by the data acquisition module, evaluate the working status of the production line, and transmit remote control instructions to the PLC module; The PLC module is used to realize automatic control of the production line and automatically adjust the working state of the production line according to the control instructions received from the Internet of Things cloud platform.

2. The intelligent manufacturing production line management system according to claim 1 is characterized in that: The data acquisition module includes a camera, an RFID identification device and a sensor device; The camera is used to collect video data of the production line; The RFID identification device is used to cooperate with the RFID tags preset on the production equipment, workpieces and the work clothes of the staff to collect RFID observation data; The sensor equipment includes a temperature and humidity sensor for collecting temperature and humidity data of the production line environment, and also includes multiple types of equipment status monitoring sensors for collecting operation data of production equipment in the production line.

3. The intelligent manufacturing production line management system according to claim 1 is characterized in that: It also includes an early warning module, which is wirelessly connected to the Internet of Things cloud platform; When the IoT cloud platform evaluates the working status of the production line, it also determines whether an alarm message needs to be issued, and if so, the alarm message is wirelessly transmitted to the early warning module; The early warning module is used to issue an early warning after receiving the alarm information.

4. The intelligent manufacturing production line management system according to claim 3 is characterized in that: The early warning module includes an acoustic / optical alarm device configured in the factory building; The early warning module is also configured on the staff's smart terminal.

5. A method for managing an intelligent manufacturing production line, characterized in that: The intelligent manufacturing production line management system according to any one of claims 1 to 4 is adopted, and comprises the following steps: S1, collect various types of data in the production line through the data acquisition module, and wirelessly transmit the collected data to the Internet of Things cloud platform; S2, analyze the collected data on the IoT cloud platform, evaluate the working status of the production line, and transmit remote control instructions to the PLC module; S3, PLC module automatically controls the operation of the production line and automatically adjusts the working status of the production line according to the control instructions received from the IoT cloud platform.

6. The intelligent manufacturing production line management method according to claim 5 is characterized in that: In step S1, the data acquisition module includes a camera, an RFID identification device and a sensor device; The camera is used to collect video data of the production line; The RFID identification device is used to cooperate with the RFID tags preset on the production equipment, workpieces and the work clothes of the staff to collect RFID observation data; The sensor equipment includes a temperature and humidity sensor for collecting temperature and humidity data of the production line environment, and also includes multiple types of equipment status monitoring sensors for collecting operation data of production equipment in the production line.

7. The intelligent manufacturing production line management method according to claim 5, characterized in that: In step S2, when the IoT cloud platform evaluates the working status of the production line, it also determines whether it is necessary to issue an alarm message. If so, the alarm message is wirelessly transmitted to the early warning module, and the early warning module issues an alarm after receiving the alarm message.

8. The intelligent manufacturing production line management method according to claim 7 is characterized in that: The early warning module includes an acoustic / optical alarm device configured in the factory building; The early warning module is also configured on the staff's smart terminal.

9. The intelligent manufacturing production line management method according to claim 5, characterized in that: In step S2, the IoT cloud platform evaluates the working status of the production line specifically by the following method: S21. According to the data collected by the data collection module, n evaluation indicators are selected and a data set is established. The evaluation indicator data set is represented as C = {c1, c2, ..., c i ,…,c n }, i = 1, 2, ..., n, any element c in the data set i Indicates the index value after normalization; S22. Establish a general linear regression model: y i =c i x i b+e i ; Among them, y i is the dependent variable, x i =(x i1 ,x i2 ,…,x ip ) is the p-dimensional covariate row vector, β=(β1,β2,…,β p ) T is the regression coefficient vector, ε i is a random error; S23. Establish the following LAD-LASSO objective function: Among them, w i is the weight, λ j is the regularization parameter, j=1,2,…,p; S24. Establishing Dataset Among them, when i=1,2,…,n, we have When i=n+1,…,n+p, define e j is a p-dimensional vector whose j-th element is 1 and the other elements are 0; S25. The important feature selection results are obtained by the following formula: The important feature selection result W is compared with the preset state function to evaluate the working state of the production line, which is expressed as follows: Among them, d(t) is used to evaluate the working status of the current production line, f represents the state function, m1,m2,…,m n are preset parameters corresponding to the n evaluation indicators respectively.

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