Production control method, system and device for corrugated paper and storage medium

Abstract

According to the corrugated paper production control method and system, pressure and paper thickness parameters are collected in real time by installing a sensor, real-time data and virtual instructions are displayed through the augmented reality technology, visual adjustment of voice and gesture operation is achieved, the production trend and potential problems are predicted through a machine learning algorithm, and the production efficiency is improved. Real-time feedback is carried out through an AR interface, an AR tag is installed to identify the equipment state, an AR auxiliary troubleshooting guide is automatically generated, in addition, production data is encrypted and stored in a cloud storage medium for subsequent analysis and learning, and the production efficiency is improved. The system comprises a sensor module, an augmented reality display module, a voice and gesture recognition module, a machine learning analysis module, an AR tag recognition module, a troubleshooting guide generation module and a cloud storage and data processing module, the automation and intelligence level of corrugated paper production is effectively improved, manual intervention is reduced, and the production efficiency and quality are improved.

Description

Technical Field

[0001] The present invention relates to the field of papermaking industry, and more specifically, to a production control method, system, device and storage medium for corrugated paper. Background Art

[0002] As a material widely used in the packaging field, corrugated paper has the characteristics of being light, pressure-resistant, and shock-resistant. With the rapid development of e-commerce, logistics and other industries, its demand continues to grow. China is the world's largest producer and consumer of corrugated paper, with a huge market size and diverse application scenarios. However, the corrugated paper industry is also facing challenges such as stricter environmental protection policies, changing market demand, and rapid technological updates.

[0003] The existing technology of corrugated paper production has a low level of automation, involves much manual intervention, and cannot achieve intelligent management. Summary of the invention

[0004] In order to overcome the problems of low automation level, much manual intervention and inability to realize intelligent management in the prior art corrugated paper production, the present invention designs a corrugated paper production control method, system, device and storage medium which can effectively solve the above problems.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A corrugated paper production control method is characterized by comprising the following steps:

[0007] Install sensors on the production line to collect pressure parameters and paper thickness parameters in each process in real time;

[0008] Using augmented reality technology, real-time data and virtual instructions from the production line are superimposed and displayed in the operator's field of view;

[0009] Receive operator's voice commands and gestures through AR devices to achieve intuitive adjustment of production parameters;

[0010] Based on real-time data analysis, production trends and potential problems are predicted through machine learning algorithms, and real-time feedback is provided to operators through the AR interface;

[0011] Install AR tags on production equipment to identify equipment status and provide maintenance guidance;

[0012] When equipment anomalies or production deviations are detected, AR-assisted troubleshooting guides are automatically generated to guide operators to quickly handle them;

[0013] Store production data, operation records, and optimization strategies in encrypted cloud storage media for subsequent analysis and learning.

[0014] Preferably, the step of installing sensors on the production line to collect pressure parameters and paper thickness parameters in each process in real time specifically includes:

[0015] Pressure sensors are installed on both sides of the pressing roller to measure the pressure of the paper during the corrugation process;

[0016] Thickness sensors are installed at multiple key points along the paper transport path to measure the thickness of the paper in a non-contact manner.

[0017] Preferably, the step of receiving the operator's voice instructions and gesture operations through the AR device to achieve intuitive adjustment of the real-time data of the production line specifically includes:

[0018] Use the voice recognition system to identify the operator's voice commands and convert them into corresponding production parameter adjustment commands;

[0019] Use the gesture recognition system to identify the operator's gesture operations and convert them into corresponding production parameter adjustment commands;

[0020] Adjustment commands are sent to the production line's central control system via a wireless network.

[0021] Preferably, the steps of predicting production trends and potential problems based on real-time data analysis through machine learning algorithms and providing real-time feedback to operators through an AR interface specifically include:

[0022] Linear regression is used to predict the changing trend of production speed;

[0023] Decision trees are used to identify conditions that may lead to production problems;

[0024] Neural networks are used to learn and predict complex production patterns.

[0025] Preferably, the step of installing AR tags on production equipment to identify equipment status and provide maintenance guidance specifically includes:

[0026] The AR tag in the step includes a QR code and an RFID tag;

[0027] The QR code is used to store basic information and maintenance logs of production equipment;

[0028] The RFID tag is used to wirelessly identify the status and location of the production equipment.

[0029] Preferably, when equipment abnormality or production deviation is detected, the steps of automatically generating an AR-assisted troubleshooting guide to guide the operator to quickly handle the problem specifically include:

[0030] When production equipment anomalies or production deviations are detected, relevant data, including temperature, pressure, and vibration data, are automatically collected;

[0031] Analyze the collected data using fault diagnosis algorithms to determine the cause of the fault;

[0032] Generates a troubleshooting guide and guides operators through the steps in the AR interface for quick processing.

[0033] Preferably, the step of storing the production data, operation records and optimization strategies in an encrypted cloud storage medium for subsequent analysis and learning specifically includes:

[0034] Generate a unique authentication token in the central control system of the production line, the authentication token containing the operator's identity information, authority level, token validity period, and a digital signature for verifying the integrity of the token;

[0035] Encrypting the production data, operation records and optimization strategies using a symmetric encryption algorithm or an asymmetric encryption algorithm;

[0036] Bind the generated authentication token to the encrypted data to ensure that only users with a valid authentication token can decrypt and use the data, store the authentication token as metadata with the encrypted data, or embed the authentication token into the structure of the encrypted data;

[0037] Upload the encrypted data and the authentication token to a cloud storage service using a secure file transfer protocol, ensuring that the cloud storage service supports encrypted data storage and provides an option for encrypted data transmission;

[0038] Set up access control policies in the cloud storage service to ensure that only users holding valid authentication tokens can access the stored data. Implement an authentication token verification mechanism. When a user tries to access data, the cloud storage service will verify the validity of the token.

[0039] When a user requests access to data by providing a valid authentication token, the cloud storage service verifies the authentication token and allows the user to download the encrypted data. The user uses the key information contained in the authentication token to decrypt the data for subsequent analysis and learning.

[0040] A corrugated paper production control system, characterized by comprising:

[0041] Sensor module, used to collect pressure parameters and paper thickness parameters in real time in each process on the production line;

[0042] An augmented reality display module that overlays real-time data from the production line and virtual instructions on the operator’s field of view;

[0043] Voice and gesture recognition module, used to receive the operator's voice commands and gesture operations to achieve intuitive adjustment of production parameters;

[0044] A machine learning analysis module that predicts production trends and potential problems based on real-time data analysis and provides real-time feedback to operators through an AR interface;

[0045] AR tag recognition module, used to identify AR tags on production equipment to identify the status of production equipment and provide maintenance guidance;

[0046] The troubleshooting guide generation module is used to automatically generate AR-assisted troubleshooting guides when production equipment anomalies or production deviations are detected, guiding operators to quickly handle them;

[0047] The cloud storage and data processing module is used to store production data, operation records and optimization strategies in encrypted cloud storage media for subsequent analysis and learning.

[0048] A control device comprises a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned corrugated paper production control method.

[0049] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the corrugated paper production control method described above is implemented.

[0050] Compared with the prior art, the beneficial effects of the present invention are as follows: by installing sensors on the production line, the present invention can collect pressure parameters and paper thickness parameters in each process in real time, thus solving the problem of untimely and inaccurate manual monitoring. These sensors can accurately measure at multiple key points on both sides of the pressure roller and the paper transmission path without manual intervention. By using augmented reality technology, the real-time data of the production line and virtual indication information are superimposed and displayed in the operator's field of vision, so that the operator can intuitively see all necessary information without leaving the work position, thereby improving work efficiency and accuracy. The AR device receives the operator's voice instructions and gesture operations, realizes intuitive adjustment of production parameters, reduces the operator's dependence on the traditional control panel, simplifies the operation process, and improves the flexibility and efficiency of the operation. Based on real-time data analysis, machine learning algorithms can predict production trends and potential problems, and provide real-time feedback to operators through the AR interface, so that operators can take timely measures to prevent problems from occurring, rather than solving them after they occur. AR tags are installed on production equipment to identify equipment status and provide maintenance guidance, which makes equipment maintenance more efficient and accurate. When equipment abnormalities or production deviations are detected, the system can automatically generate AR-assisted troubleshooting guides to guide operators for quick processing, reducing fault handling time and improving the stability of the production line. Production data, operation records and optimization strategies are stored in encrypted cloud storage media, which not only ensures data security, but also facilitates subsequent analysis and learning, while supporting remote access and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0052] Figure 1 A step diagram of a corrugated paper production control method;

[0053] Figure 2 This is a structural diagram of a corrugated paper production control system. DETAILED DESCRIPTION

[0054] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0055] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0056] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0057] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0058] Example

[0059] A corrugated paper production control method, such as Figure 1 As shown, the following steps are included:

[0060] Install sensors on the production line to collect pressure parameters and paper thickness parameters in each process in real time;

[0061] Pressure parameters: specifically refers to the data related to pressure in each process on the production line, such as the pressure of the pressure roller, the pressure of glue coating, etc.

[0062] Paper thickness parameter: refers to the thickness data of paper during the production process, which is an important indicator to measure the quality and consistency of paper.

[0063] Real-time data: usually refers to the data continuously generated on the production line. This data can be of any type and is used to monitor the status and performance of the production line. Real-time data can include but is not limited to pressure parameters, paper thickness parameters, temperature, humidity, speed, production rate, etc.

[0064] Using augmented reality technology, real-time data and virtual instructions from the production line are superimposed and displayed in the operator's field of view;

[0065] Receive operator's voice commands and gestures through AR devices to achieve intuitive adjustment of production parameters;

[0066] Based on real-time data analysis, production trends and potential problems are predicted through machine learning algorithms, and real-time feedback is provided to operators through the AR interface;

[0067] Install AR tags on production equipment to identify equipment status and provide maintenance guidance;

[0068] When equipment anomalies or production deviations are detected, AR-assisted troubleshooting guides are automatically generated to guide operators to quickly handle them;

[0069] Store production data, operation records, and optimization strategies in encrypted cloud storage media for subsequent analysis and learning.

[0070] The step of installing sensors on the production line to collect pressure parameters and paper thickness parameters in each process in real time specifically includes:

[0071] Pressure sensors are installed on both sides of the pressing roller to measure the pressure of the paper during the corrugation process;

[0072] Thickness sensors are installed at multiple key points along the paper transport path to measure the thickness of the paper in a non-contact manner.

[0073] The steps of receiving the operator's voice instructions and gesture operations through the AR device to achieve intuitive adjustment of the real-time data of the production line specifically include:

[0074] Use the voice recognition system to identify the operator's voice commands and convert them into corresponding production parameter adjustment commands;

[0075] Use the gesture recognition system to identify the operator's gesture operations and convert them into corresponding production parameter adjustment commands;

[0076] Adjustment commands are sent to the production line's central control system via a wireless network.

[0077] The steps of predicting production trends and potential problems based on real-time data analysis through machine learning algorithms and providing real-time feedback to operators through an AR interface specifically include:

[0078] Linear regression is used to predict the changing trend of production speed;

[0079] Decision trees are used to identify conditions that may lead to production problems;

[0080] Neural networks are used to learn and predict complex production patterns.

[0081] The steps of installing AR tags on production equipment to identify equipment status and provide maintenance guidance specifically include:

[0082] The AR tag in the step includes a QR code and an RFID tag;

[0083] The QR code is used to store basic information and maintenance logs of production equipment;

[0084] The RFID tag is used to wirelessly identify the status and location of the production equipment.

[0085] When an equipment anomaly or production deviation is detected, the AR-assisted troubleshooting guide is automatically generated to guide the operator to quickly handle the problem. Specifically, the steps include:

[0086] When production equipment anomalies or production deviations are detected, relevant data, including temperature, pressure, and vibration data, are automatically collected;

[0087] Analyze the collected data using fault diagnosis algorithms to determine the cause of the fault;

[0088] Generates a troubleshooting guide and guides operators through the steps in the AR interface for quick processing.

[0089] The steps of storing the production data, operation records and optimization strategies in an encrypted cloud storage medium for subsequent analysis and learning specifically include:

[0090] Generate a unique authentication token in the central control system of the production line, the authentication token containing the operator's identity information, authority level, token validity period and a digital signature for verifying the integrity of the token;

[0091] Encrypt the production data, operation records and optimization strategies using a symmetric encryption algorithm (such as AES) or an asymmetric encryption algorithm (such as RSA); select a strong key, which will be protected by an authentication token and will not be stored directly in the cloud storage medium.

[0092] Bind the generated authentication token to the encrypted data to ensure that only users with a valid authentication token can decrypt and use the data, store the authentication token as metadata with the encrypted data, or embed the authentication token into the structure of the encrypted data;

[0093] Upload the encrypted data and the authentication token to a cloud storage service using a secure file transfer protocol (such as SFTP or HTTPS), ensuring that the cloud storage service supports encrypted data storage and provides an option for encrypted data transmission;

[0094] Set up access control policies in the cloud storage service to ensure that only users holding valid authentication tokens can access the stored data and implement the authentication token verification mechanism. When a user tries to access data, the cloud storage service will verify the validity of the token.

[0095] When a user requests access to data by providing a valid authentication token, the cloud storage service verifies the authentication token and allows the user to download the encrypted data. The user uses the key information contained in the authentication token to decrypt the data for subsequent analysis and learning.

[0096] A corrugated paper production control system, such as Figure 2 As shown, including:

[0097] Sensor module 1, used to collect pressure parameters and paper thickness parameters in each process on the production line in real time;

[0098] An augmented reality (AR) display module 2, used to overlay and display the real-time data of the production line and virtual indication information in the operator's field of view;

[0099] Voice and gesture recognition module 3, used to receive voice commands and gesture operations from operators to achieve intuitive adjustment of production parameters;

[0100] Machine learning analysis module 4, used to predict production trends and potential problems based on real-time data analysis, and provide real-time feedback to operators through the AR interface;

[0101] AR tag recognition module 5, used to recognize AR tags on production equipment to identify the status of production equipment and provide maintenance guidance;

[0102] The troubleshooting guide generation module 6 is used to automatically generate an AR-assisted troubleshooting guide when a production equipment anomaly or production deviation is detected, to guide the operator to quickly handle the problem;

[0103] The cloud storage and data processing module 7 is used to store production data, operation records and optimization strategies in an encrypted cloud storage medium for subsequent analysis and learning.

[0104] A control device comprises a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned corrugated paper production control method.

[0105] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the corrugated paper production control method as described above is implemented.

[0106] In a specific implementation, high-precision pressure sensors (such as strain gauge sensors) are installed on both sides of the pressing rollers of the corrugated paper production line to measure the pressure of the paper during the corrugating process in real time, and non-contact thickness sensors (such as ultrasonic or laser sensors) are installed at multiple key points of the paper transmission path to measure the thickness of the paper in a non-contact manner.

[0107] Develop a dedicated augmented reality (AR) application that interprets sensor data and displays it graphically and numerically in the operator’s field of view, using a head-mounted display to overlay key production parameters including pressure, thickness, temperature and humidity as transparent layers.

[0108] The integrated voice recognition system enables operators to quickly adjust production settings through voice commands, such as "increasing roller pressure", and the gesture recognition system allows operators to adjust roller pressure or change paper delivery speed through preset gestures.

[0109] The operator's instructions are sent to the central control system of the production line via a wireless network.

[0110] The pressure parameters and paper thickness parameters of the production line are collected and stored in the central processing unit.

[0111] The collected data is analyzed using machine learning algorithms, such as random forests or neural networks, to predict production trends and potential problems.

[0112] The analysis results are fed back to operators in real time through an AR interface, including predicted production trends and warnings of potential problems.

[0113] Install QR codes or RFID tags on key components of production equipment, containing the equipment's identification information and maintenance instructions.

[0114] Scan the AR tag with an AR device to display the real-time status and maintenance instructions of the equipment.

[0115] The integrated fault diagnosis module automatically diagnoses the cause of equipment abnormality by analyzing equipment logs and real-time data.

[0116] Generates a troubleshooting guide and guides operators through the steps in the AR interface for quick processing.

[0117] A unique authentication token is generated in the production line’s central control system, containing the operator’s identity information, permission level, token validity period, and a digital signature to verify the integrity of the token.

[0118] Use the AES-256 encryption algorithm to perform end-to-end encryption on production data, upload the encrypted data to cloud storage media, and use a secure file transfer protocol to ensure the security of data during transmission.

[0119] Integrate all the above modules into a unified control system to ensure seamless connection and processing of data, conduct system testing in the actual production environment, and evaluate the performance and accuracy of the system.

[0120] Operators are trained to familiarize them with the operation and troubleshooting process of AR equipment, and detailed user manuals and online tutorials are provided to support operators in their daily operations.

[0121] Data is regularly extracted from cloud storage media for subsequent analysis and learning to optimize the production process, and production parameters and maintenance plans are adjusted based on the analysis results to improve production efficiency and product quality.

[0122] The same or similar reference numerals correspond to the same or similar components;

[0123] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0124] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A corrugated paper production control method, characterized in that: The following steps are involved: Install sensors on the production line to collect pressure parameters and paper thickness parameters in each process in real time; Using augmented reality technology, real-time data and virtual instructions from the production line are superimposed and displayed in the operator's field of view; Receive operator's voice commands and gestures through AR devices to achieve intuitive adjustment of production parameters; Based on real-time data analysis, production trends and potential problems are predicted through machine learning algorithms, and real-time feedback is provided to operators through the AR interface; Install AR tags on production equipment to identify equipment status and provide maintenance guidance; When equipment anomalies or production deviations are detected, AR-assisted troubleshooting guides are automatically generated to guide operators to quickly handle them; Store production data, operation records, and optimization strategies in encrypted cloud storage media for subsequent analysis and learning.

2. A corrugated paper production control method according to claim 1, characterized in that: The step of installing sensors on the production line to collect pressure parameters and paper thickness parameters in each process in real time specifically includes: Pressure sensors are installed on both sides of the pressing roller to measure the pressure of the paper during the corrugation process; Thickness sensors are installed at multiple key points along the paper transport path to measure the thickness of the paper in a non-contact manner.

3. A corrugated paper production control method according to claim 1, characterized in that: The steps of receiving the operator's voice instructions and gesture operations through the AR device to achieve intuitive adjustment of the real-time data of the production line specifically include: Use the voice recognition system to identify the operator's voice commands and convert them into corresponding production parameter adjustment commands; Use the gesture recognition system to identify the operator's gesture operations and convert them into corresponding production parameter adjustment commands; Adjustment commands are sent to the production line's central control system via a wireless network.

4. A corrugated paper production control method according to claim 1, characterized in that: The steps of predicting production trends and potential problems based on real-time data analysis through machine learning algorithms and providing real-time feedback to operators through an AR interface specifically include: Linear regression is used to predict the changing trend of production speed; Decision trees are used to identify conditions that may lead to production problems; Neural networks are used to learn and predict complex production patterns.

5. A corrugated paper production control method according to claim 1, characterized in that: The steps of installing AR tags on production equipment to identify equipment status and provide maintenance guidance specifically include: The AR tag in the steps includes a QR code and an RFID tag; The QR code is used to store basic information and maintenance logs of production equipment; The RFID tag is used to wirelessly identify the status and location of the production equipment.

6. A corrugated paper production control method as claimed in claim 1, characterized in that: When an equipment anomaly or production deviation is detected, the AR-assisted troubleshooting guide is automatically generated to guide the operator to quickly handle the problem. Specifically, the steps include: When production equipment anomalies or production deviations are detected, relevant data, including temperature, pressure, and vibration data, are automatically collected; Analyze the collected data using fault diagnosis algorithms to determine the cause of the fault; Generates a troubleshooting guide and guides operators through the steps in the AR interface for quick processing.

7. A corrugated paper production control method according to claim 1, characterized in that: The steps of storing the production data, operation records and optimization strategies in an encrypted cloud storage medium for subsequent analysis and learning specifically include: Generate a unique authentication token in the central control system of the production line, the authentication token containing the operator's identity information, authority level, token validity period, and a digital signature for verifying the integrity of the token; Encrypting the production data, operation records and optimization strategies using a symmetric encryption algorithm or an asymmetric encryption algorithm; Bind the generated authentication token to the encrypted data to ensure that only users holding valid authentication tokens can decrypt and use the data, store the authentication token as metadata together with the encrypted data, or embed the authentication token into the structure of the encrypted data; Upload the encrypted data and the authentication token to a cloud storage service using a secure file transfer protocol, ensuring that the cloud storage service supports encrypted data storage and provides an option for encrypted data transmission; Set up access control policies in the cloud storage service to ensure that only users holding valid authentication tokens can access stored data and implement authentication token verification mechanisms. When a user tries to access data, the cloud storage service will verify the validity of the authentication token. When a user requests access to data by providing a valid authentication token, the cloud storage service verifies the authentication token and allows the user to download the encrypted data. The user uses the key information contained in the authentication token to decrypt the data for subsequent analysis and learning.

8. A corrugated paper production control system, characterized in that: include: A sensor module (1) is used to collect pressure parameters and paper thickness parameters in each process on the production line in real time; An augmented reality display module (2) is used to superimpose real-time data of the production line and virtual indication information on the operator's field of view; A voice and gesture recognition module (3) for receiving voice commands and gesture operations from operators to enable intuitive adjustment of production parameters; A machine learning analysis module (4) is used to predict production trends and potential problems based on real-time data analysis and provide real-time feedback to operators through an AR interface; An AR tag recognition module (5) is used to recognize AR tags on production equipment to identify the status of the production equipment and provide maintenance guidance; A troubleshooting guide generation module (6) is used to automatically generate an AR-assisted troubleshooting guide when a production equipment anomaly or a production deviation is detected, to guide the operator to quickly handle the problem; The cloud storage and data processing module (7) is used to store production data, operation records and optimization strategies in an encrypted cloud storage medium for subsequent analysis and learning.

9. A control device, comprising a memory and a processor, wherein the memory stores a code, characterized in that: The processor is configured to obtain the code and execute a corrugated paper production control method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a corrugated paper production control method as described in any one of claims 1 to 7 is implemented.

Images