Intelligent Internet of Things module for MES (Manufacturing Execution System)

Abstract

The invention discloses an intelligent Internet of Things module for an MES manufacturing execution system, and the module comprises a cloud platform which is provided with a plurality of modules, and the modules are used for the wireless connection between a terminal and the Internet of Things module. The coordination module is provided with a unit for enabling the MES to be matched with the networking mode; and the AI model is used for automatic iterative matching of attributes (bandwidth and service agreements) of units in a networking mode, and relates to the technical field of MES and Internet of Things. According to the method, the Internet of Things module conditions are arranged through the cloud platform to complete the module arrangement scheme, the Internet of Things module conditions are selectively processed through the coordination module to be compatible with MES manufacturing execution requirements, and the algorithm of the Internet of Things module is optimized through the steps of updating the processing algorithm through the AI model and obtaining the fastest algorithm protocol. Therefore, the Internet of Things module can respond to the MES more quickly, and the processing time of the MES is effectively prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of MES and the Internet of Things, and in particular to an intelligent Internet of Things module for an MES manufacturing execution system. Background Art

[0002] MES Manufacturing Execution System is a software system used to manage and control the production process. It is combined with the Enterprise Resource Planning (ERP) system and the Planning and Scheduling System (APS) to provide enterprises with comprehensive production management solutions. The MES system is mainly used to monitor and manage key links in the production process, including production scheduling, raw material management, production guidance, quality control, equipment management, etc., so as to help enterprises achieve real-time visualization, intelligence and automation of the production process, improve production efficiency, quality and reliability, and reduce costs and risks.

[0003] The application of smart Internet of Things (IoT) modules in MES manufacturing execution systems may face some specific problems and challenges, which mainly involve technology, security and integration:

[0004] Data collection and transmission efficiency: The smart IoT module is responsible for real-time data collection from devices and sensors, and transmits the data to the MES system for processing and analysis. Problems may arise in the efficiency and stability of data collection, especially in a large-scale production environment, how to ensure the timeliness and integrity of data is a key challenge.

[0005] Equipment compatibility and integration: Different manufacturing equipment and sensors are usually provided by different suppliers, and their communication protocols and data formats may be different. Smart IoT modules need to be able to be effectively compatible and integrated with various devices to ensure unified data collection and seamless connection with the MES system.

[0006] Security and data privacy: Smart IoT modules are connected to the MES system through public or private networks, so data security needs to be guaranteed during transmission and storage. Security measures must cover data encryption, identity authentication, access control, etc. to prevent data leakage and unauthorized access.

[0007] Real-time and responsiveness: Data collection and feedback in the manufacturing process need to be real-time and highly responsive. The design of smart IoT modules needs to take into account the ability to quickly process data and make real-time decisions to support timely adjustments and optimizations in the production process.

[0008] Power consumption management and durability: In embedded devices, smart IoT modules need to manage their energy consumption to ensure long-term stable operation without affecting the normal operation of manufacturing equipment. At the same time, the durability and reliability of the module is also an important consideration, especially in harsh working environments.

[0009] Technology updates and future expansion: IoT technology and related standards are constantly evolving, and smart IoT modules need to be able to adapt to future technology updates and system expansion requirements. The module's upgradeability and scalability need to be considered during design to support the long-term development and transformation of the manufacturing industry.

[0010] Solving these problems requires comprehensive consideration of IoT technology, communication technology, security technology, and the specific needs and standards of the manufacturing industry. Technology suppliers and manufacturing companies need to work closely together to promote the effective application and optimization of smart IoT modules in MES manufacturing execution systems.

[0011] Therefore, the existing IoT modules will affect the response time of the MES manufacturing execution system, and there is room for improvement. Summary of the invention

[0012] The purpose of the present invention is to provide an intelligent Internet of Things module for an MES manufacturing execution system to solve the problems raised in the above-mentioned background technology.

[0013] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent Internet of Things module for an MES manufacturing execution system, comprising a cloud platform, wherein the cloud platform is provided with a plurality of modules, and the plurality of modules are used for wireless connection between a terminal and the Internet of Things module, wherein the cloud platform comprises a data acquisition and transmission execution module, an equipment monitoring execution module, a security execution module, an energy efficiency optimization execution module, an integration execution module and a feedback execution module. In this application,

[0014] Data acquisition execution module and equipment monitoring execution module

[0015] 1. Data acquisition and transmission: Multiple interface support: including modern industrial standard interfaces (such as Modbus, OPC UA), Ethernet interfaces, and wireless communication interfaces (such as Wi-Fi and Bluetooth) to communicate with different types of devices and sensors.

[0016] 2. Real-time data processing: It can instantly collect and process various sensor data, such as temperature, pressure, humidity, current, etc., to achieve high-precision and low-latency data transmission.

[0017] 3. Equipment status monitoring and remote control: Remote data access: Support remote monitoring and control of equipment to view equipment status in real time, adjust equipment parameters, and perform remote maintenance operations.

[0018] Security Execution Module

[0019] 1. Real-time alerts and notifications: Ability to generate alerts and notifications based on set thresholds and conditions, and respond to equipment failures and abnormal situations in a timely manner.

[0020] 2. Data encryption and authentication: Use advanced encryption algorithms to protect the security of data transmission and ensure the confidentiality and integrity of data.

[0021] 3. Device authentication and access control: Support device identity authentication and access control mechanisms to prevent unauthorized access and operation.

[0022] Energy efficiency optimization execution module

[0023] 1. Energy efficiency optimization and production efficiency: Energy monitoring and optimization: monitor energy consumption data, analyze and optimize energy usage patterns, and provide energy-saving suggestions and optimization solutions.

[0024] Integrated execution module

[0025] 1. Production data analysis: Real-time analysis and mining of data in the production process to identify factors causing low production efficiency and provide suggestions for improvement.

[0026] 2. Cloud platform integration: supports uploading data to the cloud platform to achieve remote data storage, analysis and visualization.

[0027] Feedback execution module

[0028] 1. Customized reports and analysis: Ability to generate customized reports and analysis results to help managers and engineers make decisions and optimize;

[0029] A coordination module, wherein a unit for matching a networking mode of an MES manufacturing execution system is provided under the coordination module, wherein the units under the coordination module include a software unit, a communication unit, and a data processing unit, wherein the software unit includes one of SAP or Oracle compatible with mainstream MES and ERP systems, and the communication unit includes one of RS485, Ethernet, Wi-Fi, or Bluetooth LE that meets the device access requirements, and wherein the AI ​​model includes a comprehensive CNN neural network, wherein the comprehensive CNN neural network uses a cloud platform as a pooling layer, a module under the cloud platform as a pooling unit, a coordination module as a convolutional layer, and a unit under the coordination module as a convolutional unit for comprehensive learning, iterating and generating a neural network algorithm suitable for bandwidth and service protocol adjustment;

[0030] and an AI model, which is used for automatic iterative matching of properties (bandwidth and service protocol) of units in a networking mode.

[0031] A method for using an intelligent Internet of Things module for an MES manufacturing execution system, comprising:

[0032] Step S1: Deploy IoT module conditions through the cloud platform to complete the module deployment plan;

[0033] Step S2: Selectively process the IoT module conditions through the coordination module to be compatible with the MES manufacturing execution requirements;

[0034] Step S3: Update the processing algorithm through the AI ​​model and obtain the fastest algorithm protocol

[0035] Specifically, the neural network algorithm includes

[0036] F: →(Q, R, N)

[0037] Among them, Q is the convolution layer, R is the pooling layer, N is the learning parameter, and F is the neural network algorithm.

[0038] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the learning parameter N in the neural network algorithm can be relinked with the cloud platform, the fastest network speed protocol in the network protocol is selected and intelligently matched to the AI ​​model, and the fastest algorithm protocol is obtained after iterative learning.

[0039] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the cloud platform includes a data acquisition and transmission execution module, an equipment monitoring execution module, a security execution module, an energy efficiency optimization execution module, an integration execution module and a feedback execution module.

[0040] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the units under the coordination module include a software unit, a communication unit and a data processing unit, the software unit includes one of SAP or Oracle compatible with mainstream MES and ERP systems, and the communication unit includes one of RS485, Ethernet, Wi-Fi or Bluetooth LE that meets device access requirements.

[0041] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the AI ​​model includes a comprehensive CNN neural network, and the comprehensive CNN neural network uses the cloud platform as a pooling layer, the modules under the cloud platform as pooling units, the coordination module as a convolution layer, and the units under the coordination module as convolution units to perform comprehensive learning, iterate and generate a neural network algorithm suitable for bandwidth and service protocol adjustment.

[0042] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the neural network algorithm includes

[0043] F: →(Q, R, N)

[0044] Among them, Q is the convolution layer, R is the pooling layer, N is the learning parameter, and F is the neural network algorithm.

[0045] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the learning parameter N in the neural network algorithm can be relinked with the cloud platform, the fastest network speed protocol in the network protocol is selected and intelligently matched to the AI ​​model, and the fastest algorithm protocol is obtained after iterative learning.

[0046] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system also includes an iterative stimulation module, which performs variance calculation on the neural network algorithm, and selects a matching variance optimization algorithm after filtering out random influencing factors.

[0047] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system also includes an automatic correction system. The automatic correction system uses an error detection unit and a correction unit. The automatic correction system detects variance algorithm errors through the error detection unit and repairs variance algorithm errors through the correction unit.

[0048] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the automatic correction system also includes a log unit, and the log unit generates a work log of the automatic correction system.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] This application deploys the IoT module conditions through the cloud platform to complete the module layout plan, selectively processes the IoT module conditions through the coordination module, optimizes the IoT module algorithm to be compatible with the MES manufacturing execution requirements and updates the processing algorithm through the AI ​​model and obtains the fastest algorithm protocol, so that the IoT module can respond to the MES manufacturing execution system faster, effectively improving the processing time of the MES manufacturing execution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The present invention is a schematic diagram of a method flow in an intelligent Internet of Things module for an MES manufacturing execution system. DETAILED DESCRIPTION

[0052] 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.

[0053] In the description of the present invention, it should be noted that, for those skilled in the art, the specific meanings of the above terms in the present invention can be understood in specific situations. The following describes an embodiment of the present invention based on its overall structure.

[0054] See also Figure 1 In an embodiment of the present invention, an intelligent Internet of Things module for an MES manufacturing execution system includes a cloud platform, wherein the cloud platform is provided with a plurality of modules, and the plurality of modules are used for wireless connection between a terminal and the Internet of Things module; a coordination module, wherein the coordination module is provided with a unit for the MES manufacturing execution system to match a networking mode; and an AI model, wherein the AI ​​model is used for automatic iterative matching of attributes (bandwidth and service protocol) of units in the networking mode.

[0055] A method for using an intelligent Internet of Things module for an MES manufacturing execution system, comprising:

[0056] Step S1: Deploy IoT module conditions through the cloud platform to complete the module deployment plan;

[0057] Step S2: Selectively process the IoT module conditions through the coordination module to be compatible with the MES manufacturing execution requirements;

[0058] Step S3: Update the processing algorithm through the AI ​​model and obtain the fastest algorithm protocol.

[0059] As a further solution of the present invention: an intelligent Internet of Things module for an MES manufacturing execution system, the cloud platform includes a data acquisition and transmission execution module, an equipment monitoring execution module, a security execution module, an energy efficiency optimization execution module, an integration execution module and a feedback execution module.

[0060] Other embodiments of the present invention also include an iterative stimulation module and an automatic correction system, wherein the iterative stimulation module performs variance calculation on the neural network algorithm, selects a matching variance optimization algorithm after filtering out random influencing factors, and the automatic correction system uses an error detection unit and a correction unit. The automatic correction system detects variance algorithm errors through the error detection unit, and the automatic correction system repairs variance algorithm errors through the correction unit. The automatic correction system also includes a log unit, which generates a work log of the automatic correction system.

[0061] The working principle of the present invention is: to deploy the IoT module conditions through the cloud platform, to complete the module layout plan, to selectively process the IoT module conditions through the coordination module, to be compatible with the MES manufacturing execution requirements and to optimize the algorithm of the IoT module through the AI ​​model to update the processing algorithm and obtain the fastest algorithm protocol, so that the IoT module can respond to the MES manufacturing execution system faster, effectively improving the processing time of the MES manufacturing execution system.

[0062] What has been described above are only preferred specific implementations of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, can make equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent IoT module for MES manufacturing execution system, It is characterized in that It includes a cloud platform, under which a number of modules are provided, and the number of modules are used for wireless connection between the terminal and the Internet of Things module; A coordination module, wherein the coordination module is provided with a unit for matching the networking mode of the MES manufacturing execution system; and An AI model is provided for automatic iterative matching of attributes of units in a networking mode.

2. According to claim 1, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that The cloud platform includes a data collection and transmission execution module, an equipment monitoring execution module, a security execution module, an energy efficiency optimization execution module, an integration execution module and a feedback execution module.

3. According to claim 2, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that The units under the coordination module include a software unit, a communication unit and a data processing unit. The software unit includes one of SAP or Oracle compatible with mainstream MES and ERP systems, and the communication unit includes one of RS485, Ethernet, Wi-Fi or Bluetooth LE that meets device access requirements.

4. According to claim 3, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that The AI ​​model includes a comprehensive CNN neural network, which uses the cloud platform as a pooling layer, the modules under the cloud platform as pooling units, the coordination module as a convolution layer, and the units under the coordination module as convolution units for comprehensive learning, iteratively, and generates a neural network algorithm suitable for bandwidth and service protocol adjustment.

5. According to claim 4, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that The neural network algorithm includes F: →(Q, R, N) Among them, Q is the convolution layer, R is the pooling layer, N is the learning parameter, and F is the neural network algorithm.

6. According to claim 5, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that The learning parameter N in the neural network algorithm can be relinked with the cloud platform, the fastest network speed protocol in the network protocol is selected and intelligently matched to the AI ​​model, and then the fastest algorithm protocol is obtained after iterative learning.

7. According to claim 6, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that It also includes an iterative stimulation module, which performs variance calculation on the neural network algorithm, selects a matching variance optimization algorithm after filtering out random influencing factors.

8. According to claim 7, a smart Internet of Things module for a MES manufacturing execution system, It is characterized in that The invention also includes an automatic correction system. The automatic correction system includes an error detection unit and a correction unit. The automatic correction system detects the variance algorithm error through the error detection unit and repairs the variance algorithm error through the correction unit.

9. The intelligent Internet of Things module for an MES manufacturing execution system according to claim 8, It is characterized in that The automatic correction system further comprises a log unit, which generates a work log of the automatic correction system.

10. A method for using an intelligent Internet of Things module for an MES manufacturing execution system according to claim 9, It is characterized in that include Step S1: Deploy IoT module conditions through the cloud platform to complete the module deployment plan; Step S2: Selectively process the IoT module conditions through the coordination module to be compatible with the MES manufacturing execution requirements; Step S3: Update the processing algorithm through the AI ​​model and obtain the fastest algorithm protocol.

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