Metallurgy intelligent factory multi-scale linkage modeling simulation method based on digital twinning

Abstract

The invention relates to the technical field of steel logistics management, and particularly discloses a digital twinning-based metallurgical intelligent factory multi-scale linkage modeling simulation method, which comprises the following steps of: establishing a production management system MES, and establishing butt joint between the production management system MES and all PLC control systems of a factory; data interaction between a production management system MES and a warehouse management system WMS is established, and the production management system MES is directly linked to perform management control of automatic delivery of the steel coils; a production management system MES carries out vehicle entrance inspection and electronic reservation list verification; a production management system MES carries out automatic distribution of storage positions and automatic loading and warehousing; a production management system MES receives the order, automatically generates a warehouse-out task, and automatically completes loading after a single crown block takes the goods; the production management system MES synchronously updates the inventory state; according to the invention, the stability of data transmission is ensured, the security of data transmission is improved, scattered PLC systems are effectively fused, and the functional comprehensiveness of the management system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel logistics management, and in particular to a multi-scale linkage modeling simulation method for a metallurgical intelligent factory based on digital twinning. BACKGROUND

[0002] As an important pillar of the national economy, the steel industry is accelerating its transformation towards intelligence and green. Internationally, Siemens, ThyssenKrupp, POSCO and other enterprises have achieved deep technology integration in logistics scheduling, intelligent steelmaking, environmental control and other aspects, relying on industrial internet platforms and AI algorithms to improve the efficiency and quality of the whole process. Domestic enterprises such as Baowu, Angang, Shougang, Jingtang, and CISDI have also made key technological breakthroughs in steel logistics coordination, precise pollution prediction, ingredient optimization, one-key steelmaking, and intelligent management of quality equipment. Currently, the global steel industry is showing trends such as whole-linkage collaborative optimization, low-carbon intelligent control, multi-modal data fusion, edge intelligence deployment, and platformized module reuse. Domestic steel logistics research is also advancing. Baowu Group relies on the "Ouye Cloud" industrial internet platform to achieve visualized steel logistics throughout the entire process, improving vehicle turnover efficiency. The logistics intelligent scheduling system developed by Shasteel Group optimizes the unloading process with the help of Internet of Things data, significantly shortening unloading time. The steel logistics data platform technology developed by Beijing University of Science and Technology realizes multi-source data fusion within seconds, providing support for the digital transformation of multiple steel enterprises.

[0003] Since 2024, steel logistics intelligence has entered a new stage of "whole-linkage collaboration + scenario depth landing", and the latest developments in the industry have shown characteristics such as whole-linkage collaborative optimization breaking through single-link optimization, equipment intelligence advancing towards "unmanned", and standards and ecology being built at a faster pace. The research on whole-linkage intelligent collaborative optimization of unloading and dispatching based on industrial internet platform will build a "data collection-real-time modeling-intelligent scheduling-dynamic execution" closed-loop intelligent system through technology integration, with broad prospects for development in terms of technological breakthrough, scale popularization, green transformation, and ecological reconstruction.

[0004] Currently, steel enterprises face two main problems in the process of data fusion and management system platform construction. First, the PLC systems, logistics management systems, and other manufacturers and functions used previously are quite chaotic, making effective fusion difficult. Second, during system fusion, data may be subject to software ransom, loss, and transmission errors, causing chaos in system management. Therefore, there is an urgent need in the industry for a multi-scale linkage modeling simulation method for a metallurgical intelligent factory based on digital twinning to address the poor system fusion and poor data transmission stability in the process of building existing management system platforms. SUMMARY

[0005] In view of the problems in the prior art, the purpose of the present application is to provide a multi-scale linkage modeling simulation method for a metallurgical intelligent factory based on digital twinning.

[0006] The technical scheme adopted by the present application to solve its technical problems is: a metallurgical intelligent factory multi-scale linkage modeling simulation method based on digital twinning, comprising the following steps:

[0007] S1, build a production management system MES, and establish the docking of the production management system MES and all PLC control systems of the factory;

[0008] S2, establish data interaction between the production management system MES and the warehouse management system WMS, and the production management system MES directly links to manage and control the automatic shipment of steel coils;

[0009] S3, the production management system MES performs vehicle entry inspection and electronic reservation single verification;

[0010] S4, the production management system MES performs automatic allocation of storage positions, automatically labels recommended storage positions, automatically transports steel coils through overhead crane visual navigation, and automatically loads into the warehouse;

[0011] S5, the production management system MES receives an order to automatically generate a delivery task sheet, locks the steel coil position label information and corresponding vehicle information of the overhead crane, and automatically completes loading after the overhead crane picks up the goods;

[0012] S6, the production management system MES synchronously updates the inventory status.

[0013] Specifically, the docking of the production management system MES and the PLC control system in step S1 adopts an HTTP+JSON interface docking form, uses the RESTful API of the MES system, and the PLC control system converts the collected data into JSON format through edge computing equipment or gateway software, and then sends it to the MES system server through the HTTP protocol.

[0014] Specifically, the HTTP+JSON interface docking form writes a communication program for the PLC control system side, the designed interface specification converts data into JSON format and sends HTTP requests; at the same time, the corresponding API interface is developed in the MES system to receive and process these requests; according to the actual application scene and communication requirements, the communication hardware devices of industrial Ethernet switch or wireless gateway are selected, the MES system adopts redundant network design and network monitoring tools to guarantee the normal operation of the communication link, the MES system adopts encryption algorithm for encrypted transmission, and the corresponding threat data model and evaluation data model are established.

[0015] Specifically, the threat data model constructs ICS ransomware ICS-BROCK, which completes a ransomware attack on the monitoring layer and PLC, scans the local network for PLC control systems and PC devices on the monitoring layer ICS-BROCK, encrypts files and data on the PC, locks the PLC control system and injects a logic bomb on the PLC control system, and all operations are completed without any prior information, using BadUSB as an attack carrier in the spread of the ransomware.

[0016] Specifically, the evaluation data model uses ICS-BROCK to encrypt files using a randomly generated symmetric key, and after encryption, the symmetric key is encrypted by a public key and cleared memory data, the attacker will use the private key to decrypt the key and send it to the victim along with the decryption program, ICS-BROCK will not have any impact on the ICS environment within the planned time, the evaluation of the PLC control system detects whether ICS-BROCK will have an impact on the production environment, and the detection of the impact on the production environment includes the execution time and the memory consumption of the PLC control system, after establishing the warehouse management system WMS environment and evaluating ICS-BROCK, a ransomware attack is carried out in the ICS environment to test the combat capability of ICS-BROCK, ICS is infected through BadUSB on the workstation, ICS-BROCK will automatically perform further attacks, infect other monitoring computers, and finally write a logic bomb to the PLC control system and lock it.

[0017] Specifically, the data interaction mode between the production management system MES and the PLC control system after the docking in step S1 adopts a secondary interaction mode.

[0018] Specifically, the data interaction between the production management system MES and the warehouse management system WMS in step S2 adopts a database direct docking mode, the warehouse management system WMS directly or indirectly uses the database used by the production management system MES, the database includes but is not limited to MySQL, Oracle, writes data or reads instructions from the database, the database direct docking designs the database table structure, the database table structure includes field name, data type and primary key, and the database table structure stores the data uploaded by the PLC control system to the warehouse management system WMS and the instructions issued by the production management system MES.

[0019] Specific is, the vehicle in the step S3 of the entrance examination, the vehicle of the factory area must be registered and license plate matching, the vehicle with order needs the vehicle management personnel to make an appointment in advance, the production management system MES gives the vehicle matching code after submitting the application, the matching code is consistent with the parking position of the warehouse, the vehicle enters the designated parking space according to the designated matching code, the video recognition system of the warehouse reads whether the vehicle photograph and the parking space are matched, carries out electronic reservation single check, does not match, the production management system MES does not send the loading command to the overhead crane and notifies the vehicle management personnel to match the loading information, after matching, the production management system MES sends the loading instruction to the overhead crane.

[0020] Specific is, the production management system MES in the step S4 carries out automatic allocation of the storage position, specifically, after the production of the steel coil, the steel coil is coded according to the specific steel grade and purpose model, the steel coil code is printed on the steel coil band by a laser printer, the steel coil band is bound to the steel coil to carry out automatic steel coil code printing, the steel coil is placed according to the code position corresponding to the warehouse landmark, a visual camera is installed on the clamp crane of the steel coil, the camera of the crane identifies the steel coil code and places it on the corresponding 'U' type placement position.

[0021] Specific is, the production management system MES in the step S5 receives the order and completes the electronic reservation single check, and automatically generates the warehouse task sheet, and sends the loading instruction to the crane, the crane automatically hoists and loads the vehicle according to the steel coil number and vehicle parking position information on the task sheet, after loading is completed, the vehicle license information and steel coil number information are checked again through the video recognition system of the warehouse, after checking, the production management system MES informs the access control system of each factory area to release.

[0022] The present application has the following beneficial effects:

[0023] The metallurgical intelligent factory multi-scale linkage modeling simulation method based on digital twinning designed by the present application adopts the HTTP+JSON interface docking form, threat data models and evaluation data models are set, malicious code interference training for effective data transmission is carried out, the stability of data transmission is ensured, packet loss is avoided, the security of data transmission is improved, the scattered PLC system is effectively fused, the functional comprehensiveness of the management system is improved, and the efficiency and the stability of automatic coil loading and unloading are greatly improved for specific logistics transportation and warehouse management models. BRIEF DESCRIPTION OF DRAWINGS

[0024] Fig. 1 It is the system fusion architecture diagram of the steel coil unloading of the embodiment of the present application.

[0025] Fig. 2 It is the training flow chart of the threat data model of the embodiment of the present application.

[0026] Fig. 3This is a flowchart of attack training of a threat data model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely further describe the technical solutions in the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] like Figs. 1-3 As shown in FIG, a multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twins includes the following steps:

[0029] 1. Build a production management system (MES) and establish a connection between the MES and all PLC control systems in the factory. This connection uses an HTTP+JSON interface. Using the MES system's RESTful API, the PLC control system converts collected data into JSON format via edge computing devices or gateway software and then sends it to the MES system server via HTTP. In this warehouse management system embodiment, the PLC control system includes, but is not limited to, data collection and control of the overhead crane's power system, vehicle identification cameras, overhead crane cameras, warehouse video recognition systems, and coil code printers.

[0030] The communication program on the PLC control system side is written in the form of HTTP+JSON interface docking. The designed interface specification converts data into JSON format and sends HTTP requests. At the same time, the corresponding API interface is developed in the MES system to receive and process these requests. According to the actual application scenario and communication requirements, the communication hardware equipment of industrial Ethernet switch or wireless gateway is selected. The MES system adopts redundant network design and network monitoring tools to ensure the normal operation of the communication link. The MES system uses encryption algorithm for encrypted transmission, and establishes corresponding threat data model and assessment data model.

[0031] Data interaction format design: HTTP+JSON interface connection form is clear API endpoint, request parameter, return data format, such as defining an API to get device status, its request URL is / api / device / status, request method is GET, and the JSON format of return data is {"deviceId":"xxx","status":"running"} and so on. For direct connection with database, reasonable database table structure should be designed, including field name, data type, primary key, etc., to store the data uploaded by PLC and the instructions issued by MES. System joint debugging is carried out for comprehensive system joint debugging to check whether the data transmission between PLC control system and MES system is correct and complete. Various actual production scenarios are simulated. Compatibility consideration: different brands and models of PLC control systems may require specific drivers or protocol support. When selecting the control system and MES system for connection, ensure that they can be compatible with each other. Some old models of PLC control system may not support the latest communication protocol, which needs to be upgraded or a protocol converter is used to realize the connection with MES system. Performance monitoring: regularly check the load and response time of communication link, and timely find and solve performance problems. For example, use network monitoring tools to monitor network traffic, packet loss rate and other indicators in real time; record data processing time and communication exception events in PLC control system and MES system for analysis and optimization.

[0032] Threat data model construction ICS ransomware ICS-BROCK, ICS-BROCK completes ransomware attack on monitoring layer and PLC, ICS-BROCK scans local network to find PLC control system and PC device, ICS-BROCK encrypts files and data on PC, ICS-BROCK locks PLC control system and injects logic bomb on PLC control system, all operations are completed without any prior information, BadUSB is used as attack carrier in the spread of ransomware, as shown in Fig. 1 .

[0033] Evaluation data model uses ICS-BROCK to encrypt files with randomly generated symmetric key, after encryption, symmetric key is encrypted with public key and memory data is encrypted, attacker uses private key to decrypt key and sends it to victim together with decryption program, ICS-BROCK does not have any impact on ICS environment within planned time, PLC control system evaluates whether ICS-BROCK will have impact on production environment, detection of impact on production environment includes execution time and PLC control system memory consumption, after establishing WMS environment and evaluating ICS-BROCK, ransomware attack experiment is carried out in ICS environment, as shown in Fig. 3As shown, the upper layer first step is for the attacker to infect the workstation, the middle layer second step is to infect other hosts, and the lower layer third step is to infect the PLC control system to test the practical ability of ICS-BROCK, and through BadUSB to infect ICS in the workstation, ICS-BROCK will automatically perform further attacks, infect other monitoring computers, and finally write a logic bomb into the PLC control system and lock it.

[0034] The data interaction mode after the docking of the production management system MES and the PLC control system adopts a secondary interaction mode, and the specific interaction process is as follows by taking the steel coil release as an example:

[0035] 1) The PLC control system prepares the steel coil release position information.

[0036] 2) The PLC control system sets the steel coil release position.

[0037] 3) The MES system feeds back information.

[0038] 4) The MES system feeds back the action result, and the PLC control system resets the steel coil release position after receiving the feedback result from the MES system.

[0039] 5) The PLC control system sets the reset steel coil release position, and the MES system resets the feedback information and the release result after receiving the reset release position from the PLC control system.

[0040] 6) The PLC control system resets the steel coil release position after receiving the release result reset from the MES system.

[0041] 2. Establish data interaction between the production management system MES and the warehouse management system WMS, and the production management system MES directly links to manage and control the automatic release of steel coils; the data interaction between the production management system MES and the warehouse management system WMS adopts a database direct docking mode, and the warehouse management system WMS directly or indirectly uses the database used by the production management system MES, the database includes but is not limited to MySQL, Oracle, writes data or reads instructions from the database, the database directly docks the database table structure, the database table structure includes field name, data type and primary key, and the database table structure stores the data uploaded by the PLC control system to the warehouse management system WMS and the instructions issued by the production management system MES. Use the encryption function of the database to store and encrypt the data. When the database is directly docked, data conflicts should be avoided, and the consistency and integrity of the data are ensured through locking mechanism, transaction processing and other technical means. For example, when multiple PLCs write data to the database at the same time, row-level locking or table-level locking is used to prevent errors caused by concurrent data writing.

[0042] 3. The production management system MES performs vehicle entry inspection, and electronic reservation single verification; vehicle entry inspection, vehicles entering and leaving the factory area must be registered and license plate matched, vehicles with orders need to be pre-arranged by vehicle management personnel, after submitting the application, the production management system MES matches the code with the vehicle, the matching code is consistent with the parking position of the warehouse, the vehicle enters the designated parking space according to the specified matching code, the video recognition system of the warehouse reads the vehicle and whether the parking position is matched, and performs electronic reservation single verification, if not matched, the production management system MES does not send the loading command to the overhead crane and notifies the vehicle management personnel to match the loading information by itself, after matching, the production management system MES sends the loading instruction to the overhead crane.

[0043] 4. The production management system MES performs automatic allocation of storage positions, automatically labels recommended storage positions, automatically transports steel coils through overhead crane visual navigation, and automatically loads into the warehouse; the production management system MES performs automatic allocation of storage positions, specifically, after the production of the steel coil is completed, the steel coil is coded according to the specific steel grade and purpose model, the steel coil code is printed on the steel coil band by a laser printer, the steel coil band binds the steel coil for automatic steel coil code printing, the steel coil is placed in the corresponding warehouse according to the coded position marker, and a visual camera is installed on the clamping overhead crane of the steel coil, the camera of the overhead crane recognizes the steel coil code and places it in the corresponding "U" shaped placement position.

[0044] 5. The production management system MES receives orders to automatically generate a delivery task sheet, the overhead crane locks the steel coil position marker information and corresponding vehicle information, and the overhead crane automatically completes loading after picking up the goods; after the production management system MES receives orders and completes electronic reservation single verification, it automatically generates a delivery task sheet and sends a loading instruction to the overhead crane, the overhead crane automatically hoists and loads the vehicle according to the steel coil number and vehicle parking position information on the task sheet, after loading is completed, the vehicle license plate information and steel coil number information are checked again through the video recognition system of the warehouse, and after the check is correct, the production management system MES notifies the access control system of each factory area to release.

[0045] 6. The production management system MES synchronously updates the inventory status.

[0046] The present application forms a steel logistics full-link intelligent collaborative system, realizes closed-loop management from logistics demand management, intelligent scheduling to operation execution, improves the automation level of logistics decision-making, solves the problem of production demand and transportation demand fragmentation and inefficient logistics transportation scheduling in the traditional mode. Output technical landing experience and industry standards, refine the replicable "platform + algorithm + process" optimization mode, reduce the intelligent transformation cost of small and medium-sized steel enterprises, and promote the overall digital transformation of the industry.

[0047] Direct economic benefits: Shorten the vehicle stay time, improve the efficiency of loading and unloading operation, realize the low inventory and fast turnover management mode of warehouse logistics. The time consumption of vehicles entering and leaving the factory is shortened by more than 30%, the steel material per capita delivery volume is increased by more than 20%, the material unloading efficiency is increased by more than 10%, and it is expected to save warehouse transportation cost of 30 million yuan per year.

[0048] Indirect economic benefits: Promote the transformation of steel logistics from traditional manpower driving to ''digital twin + intelligent decision-making'', and force logistics equipment suppliers to upgrade the technology route.

[0049] Social benefits: Promote the information construction of the steel logistics industry from the automatic control of the execution level to the intelligent scheduling of the management level, closely combine logistics transportation with steel production, reduce unnecessary waiting time of vehicles, improve the utilization rate of social transportation resources, also help to reduce energy consumption and pollutant emission, and realize the efficient and green development of logistics transportation industry.

[0050] The present application is not limited to the above-mentioned embodiments, and anyone should know that the structural changes made under the inspiration of the present application fall within the protection scope of the present application.

[0051] The technical, shape and structure parts not described in detail in the present application are all known technologies.

Claims

1. A multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin, characterized in that: The following steps are involved: S1. Build a production management system (MES) and establish a connection between the production management system (MES) and all PLC control systems in the factory; S2. Establish data interaction between the production management system (MES) and the warehouse management system (WMS). The production management system (MES) is directly linked to control the automatic shipment of steel coils. S3, the production management system MES conducts vehicle entry inspection and electronic appointment form verification; S4, the production management system MES automatically allocates storage locations, automatically marks recommended storage locations, and automatically transports steel coils through visual navigation of the overhead crane and automatically loads them into the warehouse; S5. The production management system (MES) automatically generates a delivery order upon receiving the order. The overhead crane locks the steel coil location number and the corresponding vehicle information, and automatically completes loading after the overhead crane picks up the coil. S6. The production management system MES synchronously updates the inventory status.

2. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 1 is characterized in that: The connection between the production management system MES and the PLC control system in step S1 adopts the HTTP+JSON interface connection form. By using the RESTful API of the MES system, the PLC control system converts the collected data into JSON format through the edge computing device or gateway software, and then sends it to the MES system server through the HTTP protocol.

3. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 2 is characterized in that: The HTTP+JSON interface docking form is used to write the communication program on the PLC control system side. The designed interface specification converts data into JSON format and sends HTTP requests. At the same time, a corresponding API interface is developed in the MES system to receive and process these requests. According to the actual application scenario and communication requirements, communication hardware equipment such as industrial Ethernet switches or wireless gateways are selected. The MES system adopts redundant network design and network monitoring tools to ensure the normal operation of the communication link. The MES system uses encryption algorithms for encrypted transmission and establishes corresponding threat data models and assessment data models.

4. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 3 is characterized in that: The threat data model constructs the ICS ransomware ICS-BROCK. ICS-BROCK completes ransomware attacks at the monitoring layer and PLC. At the monitoring layer, ICS-BROCK scans the local network and searches for PLC control systems and PC devices. On the PC, ICS-BROCK encrypts files and data. On the PLC control system, ICS-BROCK locks the PLC control system and injects a logic bomb. All operations are completed without any prior information except the device type. BadUSB is used as an attack vector in the spread of the ransomware.

5. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 4 is characterized in that: The evaluation data model uses ICS-BROCK to encrypt files using a randomly generated symmetric key. After encryption, the symmetric key is encrypted with the public key and cleared memory data. The attacker decrypts the key using the private key and sends it to the victim along with the decryption program. Within the planned timeframe, ICS-BROCK will not have any impact on the ICS environment. The PLC control system assessment tests whether ICS-BROCK will have any impact on the production environment. The impact on the production environment is tested, including execution time and PLC control system memory consumption. After establishing a warehouse management system (WMS) environment and evaluating ICS-BROCK, a ransomware attack was conducted in the ICS environment to test ICS-BROCK's operational capabilities. ICS was infected on a workstation via a BadUSB. ICS-BROCK will automatically execute further attacks, infecting other monitoring computers, and finally write a logic bomb into the PLC control system and lock it.

6. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 1 is characterized in that: The data interaction mode after the docking of the production management system MES and the PLC control system in step S1 adopts a secondary interaction mode.

7. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 1 is characterized in that: The data interaction between the production management system MES and the warehouse management system WMS in step S2 adopts a direct database docking method. The warehouse management system WMS directly or indirectly uses the database used by the production management system MES. The database includes but is not limited to MySQL and Oracle. Data is written or instructions are read from the database. The database table structure is designed by direct database docking. The database table structure includes field names, data types and primary keys. The database table structure stores the data uploaded by the PLC control system to the instructions issued by the warehouse management system WMS and the production management system MES.

8. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 1 is characterized in that: The vehicle entry inspection in step S3 requires that vehicles entering and leaving the factory must be registered and have license plates matched. Vehicles with orders require vehicle management personnel to make an appointment for loading in advance. After submitting the application, the production management system MES gives the vehicle a matching code. The matching code is consistent with the parking position of the warehouse. The vehicle enters the designated parking space according to the specified matching code. The warehouse's video recognition system reads the vehicle photo and whether the parking space matches, and performs electronic reservation verification. If there is no match, the production management system MES will not send a loading command to the overhead crane and will notify the vehicle management personnel to match the loading information by themselves. After matching, the production management system MES sends a loading instruction to the overhead crane.

9. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 8 is characterized in that: The automatic storage location allocation performed by the production management system MES in step S4 is specifically as follows: after the steel coil is produced, it is coded according to the specific steel type and usage model, and the steel coil code is printed on the steel coil strapping by a laser printer. The steel coil strapping is used to bundle the steel coil to automatically print the steel coil code, and the steel coil is marked with the placement position of the warehouse according to the coding position. A visual camera is installed on the steel coil clamping crane, and the camera of the crane recognizes the steel coil code and places it on the corresponding "U"-shaped placement position.

10. The multi-scale linkage modeling and simulation method for a metallurgical intelligent factory based on digital twin according to claim 9 is characterized in that: The production management system MES in step S5 automatically generates a delivery task order after receiving the order and verifying the electronic appointment order, and sends a loading instruction to the overhead crane. The overhead crane automatically lifts and loads the steel coil according to the steel coil number and vehicle parking position information on the task order. After the loading is completed, the vehicle license plate information and steel coil number information are checked again through the warehouse's video recognition system. After the verification is correct, the production management system MES notifies the access control system of each factory area to release the goods.

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