End-to-end connections in distributed manufacturing automation systems

Abstract

The present subject matter relates to a distributed manufacturing automation system comprising a plurality of sets of devices, where each of the sets of devices is configured to perform a respective type of control of a manufacturing process. The distributed manufacturing automation system includes a first device in a particular device group of the plurality of groups. The first device comprises means configured to make an end-to-end connection with the data network using a first network slice, the first network slice being assigned exclusively to the particular group of devices.

Description

Technical Field

[0001] Various example embodiments relate to automation systems, and more particularly to an apparatus and method for end-to-end connectivity in a distributed manufacturing automation system. Background Art

[0002] The next generation of radio systems and network architectures promises to provide higher bit rates and coverage than current systems. They also promise to increase network scalability to hundreds of thousands of connections. Summary of the invention

[0003] An example embodiment provides a distributed manufacturing automation system, the distributed manufacturing automation system comprising multiple groups of devices, wherein each group of devices in each group of devices is configured to perform a corresponding type of control of a manufacturing process. The distributed manufacturing automation system includes a first device in a specific device group in the multiple groups. The first device includes a device configured to use a first network slice to connect to a data network end-to-end, wherein the first network slice is assigned to the specific device group. In the example, the first network slice is specifically assigned to the specific device group, and in particular is assigned to the data_item generated by the first device in the specific device group.

[0004] The device of the first device in the group of devices is further configured to extract the sub-data item and use the second network slice and / or the third network slice for the extracted sub-data item. The second network slice and / or the third network slice and any other additional network slice may be different from the first network slice. In an example, the device may include an extraction device, wherein the extraction device is configured to extract the sub-data item and use the second network slice and / or the third network slice different from the first network slice for the extracted data item.

[0005] In other words, the first device can generate a data item including at least a first sub-data item and a second sub-data item. One of the sub-data items can be extracted from data_item, and the sub-data item can be flexibly transmitted to another network slice different from the other sub-data item.

[0006] The sub-data item may be a portion of the data_item generated by the first device. Extraction of the sub-data item may allow a specific portion of the data item generated by the first device to be routed to a network slice different from the network slice used by the first network device.

[0007] Example embodiments provide a method for a distributed manufacturing automation system, the distributed manufacturing automation system comprising a plurality of groups of devices, wherein each group of devices in the groups of devices is configured to perform a respective type of control of a manufacturing process. The method comprises connecting, by a first device in a particular group of the groups, end-to-end with a data network using a first network slice, wherein the first network slice is assigned to the particular group of devices.

[0008] The method may further include extracting a sub-data item from the data item generated by the first device. The method also includes using, by the first device, a second network slice and / or a third network slice for the extracted sub-data item.

[0009] The second network slice and / or the third network slice and any other further network slice may be different from the first network slice.In an example, the apparatus may include an extracting means, wherein the extracting means is configured to extract the sub-data item.

[0010] Sub-data items may be processed differently from the rest of the data item. A standard data item may be routed to a first network slice. However, an extracted portion of a data item may be routed to another network slice. All sub-data items may be part of an end-to-end connection via the corresponding network slice.

[0011] A device for a specific device group of a distributed manufacturing automation system may be provided. The device includes a device configured to use a first network slice to make an end-to-end connection with a data network, wherein, in an example, the first network slice is specifically assigned to the specific group.

[0012] According to an example embodiment, the apparatus of the first device in the group of devices is further configured to determine which of the second network slice and / or the third network slice is suitable for use.

[0013] In another example embodiment, it is determined which of the second network slice and / or the third network slice is suitable for use based on a monitoring operation.

[0014] In an example, a configuration of the first device may be detected. The configuration of the first device may indicate that a data type of the sub-data item is routed to a specific network slice. The first device may be adapted to store an association and / or relationship between the data type of the sub-data item and a corresponding type of the network slice.

[0015] In other words, a profile of the sub-data item can be detected. The profile can be associated with a specific characteristic of the network slice. If it is determined that there is indeed a significant difference in the association between the sub-data item and the characteristics of the network slice, a more suitable network slice can be determined and the sub-data item can be routed to the network slice.

[0016] In a specific example, the first device and the data_item generated by the first device can be associated with a network slice according to the device type of the first device. The device type can be determined according to the intended use of the first device. For example, a camera can be assigned to a network slice with high throughput, for example, to the field device level of the automation pyramid. The field device level and / or the field device slice can have the characteristics of high throughput but low reliability.

[0017] However, it may be determined that the device also generates different data types. For example, a camera may be used to detect a person and generate an alert. For such an alert, high reliability may be useful. The alert may be processed field device data. The alert or trigger signal may be a sub-data item in a general data item generated by the camera. Thus, the alert sub-data item may be routed to a different network slice, such as a network slice with high reliability characteristics.

[0018] In a further example embodiment, it is determined which of the second network slice and / or the third network slice is suitable for use based on a monitoring operation.

[0019] In one example, the first device may monitor different configurations of user settings and may be adapted to detect a pattern of settings of a sub-data item. In another example, the first device may determine a configuration file of a sub-data item and upon detecting a change and / or deviation from a configuration file of another data item, the first device may initiate a reconfiguration and may again attempt to determine the pattern of configuration. This pattern may be used when new devices of the same type may be connected to a distributed manufacturing automation system.

[0020] In yet another example, the monitoring operation includes machine learning.

[0021] Different profiles of sub-data items may be distinguished and assigned to network slices with different characteristics. The characteristics of a network slice may be defined by slice parameters, such as quality of service (QOS), reliability, latency, bandwidth, etc. Data from a group of devices may have substantially the same attributes and / or profiles and may also have the same or similar requirements for the characteristics of the slice.

[0022] However, at least one device in the group of devices may generate different data types with different profiles and may therefore be allocated to at least two network slices. The allocation may be performed by a scheduling device and / or manually configured by an operator. The scheduling device identifies different data transmission properties of different data from a single device in the group of devices and extracts relevant data to be allocated to slices with different characteristics.

[0023] This rescheduling and / or extraction and / or reconfiguration can be detected by the scheduling device. The scheduling device can have a machine learning device that can use the detected data type pattern, the profile of the data flow and / or the allocation of the network slice to configure the device newly added to the device group. The scheduling device can make configuration suggestions so that the data items generated by the newly added device are allocated to the corresponding slice. In other words, the scheduling device can analyze the data source so as to dynamically schedule the data flow generated by the device to the appropriate slice.

[0024] Example embodiments provide a distributed manufacturing automation system configured as an automation pyramid. The distributed manufacturing automation system includes a first device at a specific level of the automation pyramid. The first device includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the device to connect end-to-end with a data network using at least a first network slice, wherein the first network slice is specifically assigned to the specific level of the automation pyramid.

[0025] In an example, an apparatus of the distributed manufacturing automation system includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first device to perform use of the first network slice.

[0026] According to a further example embodiment, a method is provided. A distributed manufacturing automation system is provided. The distributed manufacturing automation system is configured as an automation pyramid. The method includes connecting, by a first device at a specific level of the automation pyramid, end-to-end with a data network using a first network slice, wherein the first network slice is specifically assigned to the specific level of the automation pyramid.

[0027] The extraction of sub-data items may allow the use of a different level of the automation pyramid than that used by the first device.

[0028] According to a further exemplary embodiment, a computer program product is provided. The computer program product includes a computer-readable storage medium having a computer-readable program code embodied therein. The computer-readable program code is configured to implement the method described in any of the aforementioned embodiments.

[0029] According to a further example embodiment, there is provided an apparatus for a distributed manufacturing automation system. The distributed manufacturing automation system is configured as an automation pyramid. The apparatus includes means configured to connect end-to-end with a data network using a first network slice, wherein the first network slice is specifically assigned to a specific level of the automation pyramid.

[0030] The apparatus comprises: at least one processor; and at least one memory, the at least one memory comprising computer program code, the at least one memory and the computer program code being configured to, together with the at least one processor, enable the device to make an end-to-end connection with a data network using a first network slice, wherein the first network slice is specifically assigned to a specific level of the automation pyramid.

[0031] In other words, the device comprises: at least one processor; and at least one memory storing instructions which, when executed by the at least one processor, cause the device to perform use of the first network slice.

[0032] A computer program product may include a computer program. A computer program product may refer to any set of one or more storage media (also referred to as "media") collectively included in a set of one or more storage devices that collectively include machine-readable code corresponding to instructions and / or data for performing computer operations specified in the computer program product claims. A "storage device" may be any tangible device that can retain and store instructions for use by a computer processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] These accompanying drawings are included to provide a further understanding of the examples and are incorporated into and constitute a part of this specification. In the drawings:

[0034] Figure 1 A distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0035] Figure 2 A distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0036] Figure 3 A distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0037] Figure 4 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0038] Figure 5 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0039] Figure 6 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0040] Figure 6aA system for implementing data communications at a distributed manufacturing automation system having a scheduling device according to an example of the present subject matter is depicted;

[0041] Figure 7 is a flow chart of a method for communication in a distributed manufacturing automation system according to an example of the present subject matter;

[0042] Figure 8 is a flow chart of a method for communication in a distributed manufacturing automation system according to an example of the present subject matter;

[0043] Fig. 9 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted;

[0044] Fig.10 An automated device according to examples of the present subject matter is depicted. DETAILED DESCRIPTION

[0045] In the following description, specific details (such as specific architectures, interfaces, techniques, etc.) are set forth for purposes of explanation rather than limitation in order to provide a thorough understanding of the examples. However, it will be apparent to those skilled in the art that the disclosed subject matter may be practiced in other illustrative examples that deviate from these specific details. In some cases, detailed descriptions of well-known devices and / or methods are omitted to avoid obscuring the description with unnecessary detail.

[0046] Embodiments of the present subject matter may be advantageous because they may improve access to radio systems and network architectures in the field of manufacturing automation systems.

[0047] In the context of manufacturing, automation can refer to the use of devices such as sensors, actuators, robots and computers to achieve automation of manufacturing processes. For example, a manufacturing process can refer to the steps of a method for preparing a composition. A manufacturing process can involve the use of manufacturing facilities such as equipment, raw materials, machinery, tools, factories, etc. A manufacturing process can have one or more attributes (referred to herein as manufacturing attributes). Examples of manufacturing attributes can include temperature, pressure, process time, melting point of a substance, flexural strength of steel, resistance of an electrical conductor, etc. A manufacturing process can have one or more parameters (referred to herein as manufacturing parameters) that can control the manufacturing process. Examples of manufacturing parameters can include mixing rate, temperature, etc. Automation and control of a manufacturing process can be achieved by acquiring process data, analyzing the process data, and automatically adjusting the manufacturing parameters based on the analysis. The process data can include the values ​​of one or more manufacturing attributes of a manufacturing process. Depending on the type of process data acquired and / or analysis and / or the type of manufacturing parameters controlled, different types of control can be provided. For example, one type of control can check the attribute value against a threshold value and adjust one or more manufacturing parameters accordingly. Another type of control can perform a more complex (time-consuming) analysis of the manufacturing attributes in order to adjust one or more manufacturing parameters. Different types of control may have different control time ranges, for example, control may be real-time control or non-real-time control.

[0048] Control of the manufacturing process can be advantageously performed by a distributed manufacturing automation system. A distributed manufacturing automation system can include decentralized manufacturing facilities and various devices, which can be distributed in multiple systems located in different locations. A distributed manufacturing automation system can include multiple groups of equipment, wherein each group of equipment in each group of equipment is configured to perform a different type of control of the manufacturing process.

[0049] For example, each type of control of a manufacturing process may have a corresponding time range within which the control of the manufacturing process may have to be performed. In other words, each type of control of a manufacturing process has a corresponding control time range. A distributed manufacturing automation system may be implemented according to a functional model so that different types of control of a manufacturing process can be performed. The functional model may define the functions of each device, how data is exchanged and formatted within a distributed manufacturing automation system, and how devices are interconnected within a distributed manufacturing automation system. In one example, the functional model may be an ISA-95 functional model. The ISA-95 functional model may be, for example, a hierarchical pyramid model or a network-based architecture model.

[0050] The distributed manufacturing automation system is configured as an automation pyramid, which means that the distributed manufacturing automation system is implemented according to a functional model that is a hierarchical pyramid model. Each of the multiple groups belongs to a different level of the hierarchical pyramid model. For example, the first level may require a control time range of milliseconds, the second level may require a control time range of seconds, and so on. In other words, each device in a device group at a certain level can have a specific traffic profile.

[0051] For example, the functional model may describe the hierarchical arrangement of devices of a distributed manufacturing automation system according to a field level, a control level, a supervisory level, and an information level.

[0052] The field level and / or field device level may be the lowest level, which may include field devices such as sensors and actuators. The field devices may be configured to transmit process data of the manufacturing process to the next higher level for monitoring and analysis. For example, sensors may convert real-time manufacturing properties such as temperature and pressure into sensor data. The sensor data may further be transmitted to a controller for analysis of the real-time properties. An actuator may convert electrical signals from a controller into mechanical means to control the manufacturing process.

[0053] The control level can consist of various controllers, such as programmable logic controllers (PLCs), which can acquire manufacturing attributes from various sensors. The controllers can drive actuators based on the processed sensor data and control techniques.

[0054] The supervisory level can consist of monitoring devices that enable intervention functions, monitoring various manufacturing attributes, setting production targets, historical archiving, setting machine startup and shutdown, etc.

[0055] The information level manages the entire distributed manufacturing automation system. Tasks at this level can include production planning, customer and market analysis, orders and sales, etc.

[0056] One or more communication networks may exist at all levels to provide a continuous data flow. The present subject matter may further improve data communication in a distributed manufacturing automation system by using wireless connections. This may provide a flexible and efficient implementation of a distributed manufacturing automation system. Wireless connections may enable data communication between devices of a distributed manufacturing automation system. In the case of a hierarchical functional model, wireless connections may enable data communication between hierarchical levels. Additionally or alternatively, wireless connections may enable data communication between a distributed manufacturing automation system and other external systems.

[0057] Communication networks (eg, data communication networks, wide area networks, and / or wireless communication networks) may be used to link different parts of a distributed manufacturing automation system over long distances. The communication network may be adapted to different requirements for maintaining and ensuring a functional model of a manufacturing automation system in long-distance data communications.

[0058] Automation equipment, dispatching devices and / or cellular networks can be link components and / or interfaces between the automation domain and the manufacturing domain of an industrial park in the long-distance data communication provided by the communication network. Thus, the automation equipment can be adapted to map the requirements of the functional model of the manufacturing automation system to the communication network linking different locations of the industrial production network. In this way, supply chains can be linked and the digitalization of production in, for example, the chemical industry can be supported.

[0059] For example, a cellular network can be provided. The cellular network may include a base station and a core network device. The cellular network may enable high-speed wireless connections, wherein the speed of the wireless connection is higher than the minimum speed required to meet the requirements of ultra-reliable low-latency communication (URLLC). For example, the minimum speed may be 10GB per second. For example, the cellular network may be a fifth generation (5G) cellular network. The base station may include a wireless communication station. For example, the base station may be a gNodeB (gNB). The base station may be installed in a fixed ground location and used to facilitate communications in a cellular network. The base station may provide services for devices of a distributed manufacturing automation system in a given geographic area. The core network device may be a collection of network hardware, devices, and software that provide basic functions (such as data planes and control planes). The core network device may implement one or more functions of the data plane and the control plane. For example, these functions may include at least one of the following: user plane function (UPF), network open function (NEF), core access and mobility management function (AMF), session management function (SMF), policy control function (PCF), and unified data management (UDM). The base station may include resources such as processing resources and radio resources. These resources may be referred to as access resources. Core network devices may include resources such as processing resources and radio resources, which may be referred to as core resources.

[0060] Data communications over wireless connections in distributed manufacturing automation systems may need to be secure to prevent attacks, adversary tampering, and loss of confidentiality of manufacturing processes. To this end, communications between automation devices and data networks may be performed via end-to-end connections over wireless networks. Automation devices may send data to receivers connected to the data network via end-to-end connections. The end-to-end connection may be a connection between an automation device and a data network. For example, the end-to-end connection may be an active connection between an automation device and a data network via a cellular network. The data network may be any of the networks present in the hierarchy of the distributed manufacturing automation system or an external network such as the Internet.

[0061] End-to-end connectivity can be implemented as a network slice specifically assigned to the device group to which the automation device belongs. In the case of a hierarchical pyramid model, end-to-end connectivity can be implemented as a network slice specifically assigned to the automation pyramid level to which the automation device belongs. A network slice can be a logical network that provides specific network capabilities and network characteristics based on access resources and core resources. A network slice can be an independent physical end-to-end network or a logical end-to-end network running on a shared physical infrastructure. A network slice can be a collection of network functions and specific radio access technology (RAT) settings that are combined for a specific use case associated with an automation device. For example, a network slice can be a 5G slice.

[0062] A network slice may be defined using at least two segments (a first segment and a second segment). The first segment may be an access slice that is assigned specific access resources at a base station and may support different or fixed radio access technologies at the base station. The second segment may be a core network slice that provides one or more virtualized network functions. For example, an additional segment may be a slice pairing function that connects the first segment and the second segment to form an end-to-end network slice. The pairing between the first segment and the second segment may be 1:1 or 1:many, for example, an access segment may have multiple core network segments built on it.

[0063] The present subject matter can advantageously use network slicing for different groups of devices, for example, for different levels of the automation pyramid. For example, N automation devices can be provided, where N is an integer greater than or equal to 1, N ≥ 1. The automation devices can be referred to as Where index i can be any value between 1 and the number of devices N, and l refers to the i-th automation device In the following, a hierarchical pyramid model may be used as an example implementation, where l refers to the index of the device group to which the i-th automation device belongs. The index of the automation pyramid level to which it belongs, and l is any value between 1 and the total number of automation levels, K. The devices in the N automation devices can belong to the same level or different levels of the automation pyramid. Automation Device It can be any device that helps control the manufacturing process in a distributed manufacturing automation system. For example, automation equipment It can be a sensor, actuator, PLC, computer, etc. Automation equipment May include identification data that enables the automation device Ability to authenticate to and therefore communicate over a cellular network. For example, automation equipment A Subscriber Identity Module (SIM) card may be included that uniquely identifies the automation device And establish the radio parameters required to communicate with the base station.

[0064] Automation Equipment The base station can use time division duplex (TDD) technology for data transmission. Automation equipment Can be configured to use network slicing NS l Data Network DN i Make end-to-end connections. Network Slicing NS l is specifically assigned to level l of the automation pyramid so that all devices belonging to level l can be connected through the network slice NS l The data networks that two different automation devices communicate with can be the same or different, for example, two automation devices can communicate with the same data network or different data networks.

[0065] Network slicing can provide protection against external attacks; however, in network slicing NS l Internally managed data may be exposed to applications running in other network slice services through side channel attacks. To solve this problem, the present invention can isolate the network slice NS l Network Slicing NS l Isolation can be achieved by isolating network slices NS l Network Slice NS l The isolation of the first segment may include providing a network slice NS at the base station l Dedicated assignment of specific radio resources or processing resources. Network Slicing NS l The isolation of the second segment may include isolation of network functions (NFs) such that some NFs may be common to multiple network slices, while some NFs are customized for specific network slices. For example, the isolation slice pairing function may require a 1:1 pairing between the first segment and the second segment.

[0066] The subject invention can further protect data communications through network slices by controlling the isolation level of each network slice. l The isolation level can indicate the network slice NS l For example, the isolation level of a network slice may indicate whether the network slice is completely (100%) or partially (<100%) logically and / or physically isolated from another network slice. This may enable strong network slice isolation and connectivity, thereby preventing system security from being compromised. For example, the isolation level may be controlled so that each pair of network slices NS l1 and NS l2 (where l1≠l2) can be completely physically separated, so that each network slice has physical network isolation, physical computing resource isolation, etc. Alternatively or additionally, each pair of network slices NS l1 and NS l2 (where l1≠l2) Complete logical separation can be achieved using, for example, network function isolation and virtual resource isolation (such as virtual machine (VM) isolation).

[0067] The present subject matter can further protect communications through the network slice by using at least one of the following: encryption or authentication. The data to be transmitted can be encrypted. Automation equipment Through network slicing NS l The encrypted data is sent to a receiver connected to the data network. The receiver may be configured to decrypt the encrypted data. Additionally or alternatively, before data communication can occur, the automation device may The authentication data allows the receiver to first authenticate the automation device. Authentication is performed before automation equipment Able to send data. Using different combinations of authentication techniques and encryption techniques can make it possible to control the security level of communication. For example, a high security level can be achieved by using asymmetric encryption techniques and multi-dimensional authentication techniques (for example, using multi-dimensional passwords). A lower security level can be achieved by using only authentication. Therefore, according to one embodiment, each slice in the network slice is based on a specific security level S defined by at least one of the following: l Configure: Authentication or Encryption.

[0068] According to one embodiment, each network slice NS in the network slice l According to the corresponding predefined delay L l and throughput T l For example, network slice NS lThe delay in may need to be less than the delay L l , and the network slice NS l The maximum throughput allowed in can be the throughput T l This enables flexible and centralized control of data communications at the slice level.

[0069] According to one embodiment, each network slice in the network slice is configured according to different values ​​of performance parameters. The performance parameters include at least one of the following: availability, service area, maximum packet size, maximum number of devices that can simultaneously use the network slice, or radio spectrum supporting the network slice.

[0070] For example, availability may be a percentage value. For example, availability may be a ratio of the amount of time that the system expects or hopes to provide end-to-end communication services to the amount of time that the end-to-end communication services are provided. Availability may be an important indicator of overall system reliability. This embodiment may control the availability of a network slice according to the level of the automation pyramid to which the network slice is assigned. For example, the smaller the level l, the lower the network slice NS l The higher the availability, the higher the availability. For example, an automation pyramid level that requires a very small time frame to control a manufacturing process can have a higher availability value compared to other levels. 1 ,…,NS K Providing different availability may be advantageous.

[0071] A service area may specify an area where devices may access a particular network slice. For example, a service area for a network slice may be an industrial floor where a particular automation device is located. Providing different service areas for network slices in accordance with the present subject matter may further protect data communications because the number and type of devices using the network slice may be controlled, such as limited to a maximum number.

[0072] Controlling the maximum packet size for each network slice can enable the desired latency to be achieved. For example, radio performance can be improved by reducing the packet size so that a large number of small packets are transmitted by a large number of devices.

[0073] Controlling the radio spectrum to support network slicing could be advantageous because some automated devices might only use certain frequency bands.

[0074] According to one embodiment, the automation device Through network slicing NS l The data network DN with which to communicate i A network at a specific level l, or a network at another level in the automation pyramid that is different from the specific level l. For example, a second level automation device Through the slice network NS2 Communicate with the level 2 or another level (eg, level 3) data network.

[0075] According to one embodiment, the automation device Through network slicing NS l The data network with which it communicates can be an information technology (IT) network or an operational technology (OT) network of a distributed manufacturing automation system. For example, an IT network can be a network at the fourth level of the automation pyramid. For example, an OT network can be a network at the third level of the automation pyramid.

[0076] According to one embodiment, the distributed manufacturing automation system further comprises a cellular network, wherein the network slice NS l Including user plane function (UPF l ) network element. The total number K of UPFs can be different instances of UPF elements of core network devices. Automation equipment Can be connected via gNB and UPF l Establish a PDU session to share data based on network slice NS l Establish end-to-end connection. UPF l Can act as PDU session and data network DN i External interconnection point of the UPF. l May be responsible for UP functions, which may include packet routing and forwarding, UP part of policy rule enforcement, and general quality of service (QoS) enforcement for the user plane.

[0077] According to one embodiment, a network slice (e.g., a first network slice) is placed in a demilitarized zone (DMZ). For example, placing the network slice in a DMZ may include providing a DMZ network for the network slice. The DMZ network may include a system that enables a network administrator to manage external traffic (e.g., Internet traffic). The DMZ network may detect and mitigate security vulnerabilities before they reach the network slice, thereby providing additional protection.

[0078] In other words, each level of the automation pyramid may have its own firewall between them, thereby essentially allowing communication between only two levels, for example, allowing communication between the field device level and the automation level, but not between the field device level and the monitoring level. However, if the DMZ (especially the firewall) is placed in the first cellular network, the first cellular network may be able to communicate with each level of the automation pyramid, such as the field level, the automation level, the monitoring level, and the planning and analysis level.

[0079] Figure 1 A distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0080] The distributed manufacturing automation system 100 includes a manufacturing facility 101 having a plurality of field devices 103.1 to 103.N. The field devices 103.1 to 103.N may be provided with direct networking and computing capabilities. The field devices 103.1 to 103.N may include sensors, instruments, motor drives, industrial robots, vision cameras, actuators, or other such field devices. The field devices 103.1 to 103.N may be used to control one or more manufacturing processes 105. To this end, the field devices 103.1 to 103.N may be configured to generate and / or collect process data related to the control of the manufacturing process 105. The field devices 103.1 to 103.N may be configured to transmit process data 107 of the manufacturing process 105 to a data processing system 110 for analysis. For example, a manufacturing parameter of the manufacturing process 105 may be controlled by an actuator based on the analysis.

[0081] Manufacturing process 105 can refer to the steps of the method for preparing the composition in batches. Manufacturing process can, for example, include bonding process and / or shear forming process and / or molding process and / or machining process. Manufacturing process 105 can have one or more configurable manufacturing parameters, such as mixing rate, temperature, etc. Different types of control to manufacturing process 105 can be used. Each type of control to manufacturing process 105 can include an analysis step for analyzing one or more manufacturing attributes of manufacturing process 105, and a control step for adjusting one or more manufacturing parameters of manufacturing process 105 based on analysis. The manufacturing attributes of manufacturing process 105 can, for example, include duration, temperature, pressure, speed, quantity, etc. The analysis step can include monitoring and / or processing process data of manufacturing process 105. Different types of control can, for example, differ in the type of analysis performed and / or the time range required for control, for example, one or more manufacturing parameters of manufacturing process 105 may need to be controlled in real time to meet the required performance.

[0082] Each type of control of the manufacturing process 105 may require specific input data. The input data may include values ​​of one or more manufacturing attributes, which may be obtained directly from the acquired process data 107 or after preprocessing the process data 107. In addition, each type of control of the manufacturing process 105 may have different processing resource requirements. Therefore, in order to implement these different types of control of the manufacturing process 105, the data processing system 110 may be provided with different groups of devices 113, 115 and 117, each group being associated with a corresponding control type. Only three groups of devices are described, but are not limited to this.

[0083] The first group of devices 113 includes automation devices 113.1 to 113.N. The automation devices 113.1 to 113.N may have real-time capabilities. The automation devices 113.1 to 113.N may include computer numerical control (CNC) machine tools, PLCs, etc. The automation devices 113.1 to 113.N may receive process data 107 including manufacturing attributes from various sensors, and may drive actuators based on processed sensor signals and control techniques. The field devices 103.1 to 103.N together with the automation devices 113.1 to 113.N may form an automation system. Examples of automation systems may include batch control systems, continuous control systems, or discrete control systems.

[0084] The second group of devices 115 includes monitoring devices 115.1 to 115.N. For example, the monitoring devices 115.1 to 115.N may include distributed control system (DCS) devices or measurement control and data acquisition (SCADA) devices. The monitoring devices 115.1 to 115.N facilitate intervention functions, overseeing various manufacturing attributes, setting production targets, historical archiving, setting machine startup and shutdown, etc. The monitoring devices 115.1 to 115.N can save, enrich / contextualize process data 107, and make the process data available to other devices (such as analysis devices 117). For example, the monitoring devices 115.1 to 115.N can deploy a visualization application to enable factory operators to gain insights into persistent data; and deploy another application that implements a feedback mechanism in the first group of devices 113 to autonomously react to certain events and adjust the manufacturing process based on the insights generated.

[0085] The third group of devices 117 includes planning and analysis devices 117.1 to 117.N. The planning and analysis devices 117.1 to 117.N can be configured to perform production planning, customer and market analysis, orders and sales, etc. For example, the planning and analysis devices 117.1 to 117.N can be configured to perform computationally expensive tasks such as model training and validation. In another example, the planning and analysis devices 117.1 to 117.N can deploy applications that require high-availability storage, such as long-term process data archiving.

[0086] Each device of system 100 can be configured to exchange data with one or more devices in the same group to which the device belongs and / or exchange data with one or more devices in other groups of devices in order to perform tasks. For example, in order to perform a given type of control of manufacturing process 105, a group of one or more devices of system 100 may be required. The group of devices can collaborate so as to perform the analysis step of the control using input data. The input data can be (raw) process data 107 collected for manufacturing process 105, or data obtained based on process data 107 (e.g., after preprocessing). The input data can be received at the group of devices in one or more devices of system 100. Based on the results of the analysis, the group of devices can provide a suggested adjustment of one or more manufacturing parameters of the manufacturing process. These adjustments can be applied by field devices (such as actuators).

[0087] Different groups of devices may be integrated within the distributed manufacturing automation system 100 to provide a continuous flow of information for different types of control of the manufacturing process 105. The integration of the devices may be performed using different deployment and connection configurations. Figure 2 and Figure 3 Two example implementations are provided, but are not limited thereto.

[0088] Figure 2 A distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0089] like Figure 2 As shown, the distributed manufacturing automation system 200 is configured according to a hierarchical pyramid model. The hierarchical pyramid model can be an ISA-95 pyramid model. Through this configuration, Figure 1 The different device groups shown in FIG. 1 are connected via corresponding networks, and data communication is performed between the manufacturing facility and the device groups using specific connections according to predefined data flows.

[0090] The distributed manufacturing automation system 200 is organized according to different levels 201, 213, 215 and 217 of the hierarchical model. The first level 201 includes field devices 203.1 to 203.N. The field devices 203.1 to 203.N may include sensors, instruments, motor drives, industrial robots, visual cameras, actuators or other such field devices. The field devices 203.1 to 203.N may be used to monitor and / or control one or more manufacturing processes. The field devices 203.1 to 203.N may be configured to generate and / or collect process data related to the control of the manufacturing process. The field devices 203.1 to 203.N may be configured to transmit the data of the manufacturing process to the second level 213. The second level 213 includes automation devices 213.1 to 213.N. The automation devices 213.1 to 213.N may include CNC machine tools, PLCs, etc. The automation devices 213.1 to 213.N can receive data including manufacturing attributes from various sensors and can drive actuators based on processed sensor signals and programs or control techniques. The third level 215 includes monitoring devices 215.1 to 215.N. The monitoring devices 215.1 to 215.N facilitate intervention functions, overseeing various manufacturing attributes, setting production targets, historical archiving, setting machine startup and shutdown, etc. For example, the monitoring devices 215.1 to 215.N may include DCS devices or SCADA devices. The fourth level 217 includes planning and analysis devices 217.1 to 217.N. The planning and analysis devices 217.1 to 217.N can be configured to perform production planning, customer and market analysis, orders and sales, machine learning, etc.

[0091] The devices in each level of the distributed manufacturing automation system 200 can be connected to each other through a corresponding network, which is suitable for transmitting data by means of a standard protocol. For example, field devices 203.1 to 203.N can be connected to each other through network 230. Automation devices 213.1 to 213.N can be connected to each other through network 233. Monitoring devices 215.1 to 215.N can be connected to each other through network 235. Planning and analysis devices 217.1 to 217.N can be connected to each other through network 237.

[0092] The field devices 203.1 to 203.N can communicate with the automation devices 213.1 to 213.N via a connection 241. The connection 241 can be an analog connection, a fieldbus-based connection or an Ethernet-based connection. The automation devices 213.1 to 213.N can communicate with the monitoring devices 215.1 to 215.N via a connection 243. The connection 243 can be an Ethernet-based connection. The monitoring devices 215.1 to 215.N can communicate with the planning and analysis devices 217.1 to 217.N via a connection 245. The connection 245 can be an Ethernet-based connection. Each of the connections 241, 243 and 245 can be provided with a firewall that controls the data communication via the corresponding connection.

[0093] The devices of the distributed manufacturing automation system 200 can collaborate according to the hierarchical model to perform different types of control of the manufacturing process. For example, using the system 200, the operations department of a chemical company can monitor its production quality and proactively respond to product quality issues by automatically generating feedback to the automation system.

[0094] Figure 3 A distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0095] Distributed Manufacturing Automation System 300 provides Figure 1 The present invention is an example implementation of a data processing system 110 of a system. At least a portion of the second group of devices and the third group of devices can be implemented in a cloud platform 333 to utilize cloud-based applications and services. The cloud platform 333 can be provided, for example, by a cloud provider as a platform as a service (PaaS). For example, a subgroup 115.1 to 115.M of the second group of devices 115 can be implemented as a local data center, while the remaining subgroups 115.M+1 to 115.N can be implemented in the cloud platform 333. Alternatively or additionally, a subgroup 117.1 to 117.M of the third group of devices 115 can be implemented as a local data center, while the remaining subgroups 117.M+1 to 117.N can be implemented in the cloud platform 333. The devices in the cloud platform 333 can be configured to communicate via the Internet to exchange data with other devices of the data processing system 110. The devices of the local data center and the devices of the cloud platform can cooperate to perform different types of control of the manufacturing process.

[0096] Figure 4 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0097] The wireless communication system 400 includes a cellular network 405. The cellular network 405 includes a base station 402, which communicates with the automation equipment via a transmission medium. and Communicate. Automation equipment and Can be part of a distributed manufacturing automation system. Automation equipment can belong to level l1 of the automation pyramid, and the automation equipment Can belong to level l2 of the automation pyramid. l1 can be any number between 1 and the total number of levels of the automation pyramid, K. l2 can be any number between 1 and the total number of levels of the automation pyramid, K, where l2 is different from l1. Automation equipment and Each of these can be a reference Figure 1 , Figure 2 and Figure 3 Any of the described field devices, automation devices, monitoring devices, and planning and analysis devices.

[0098] Base station 402 may be a base transceiver station (BTS) and may include a communication interface that enables communication with automation equipment. and Base station 402 can be coupled to core network 404. Core network 404 can also be coupled to one or more data networks, such as data network DN i and DN j . Data Network DN i and DN j Each of the base stations 402 may be a network of a distributed manufacturing automation system or an external network. The external network may include the Internet, a public switched telephone network (PSTN), and / or any other network. Thus, the base station 402 may facilitate the automation equipment and With network 404, DN i and DN j Communication between.

[0099] Base station 402 and automation equipment and It can be configured to communicate over a transmission medium using various radio access technologies (RATs), such as Long Term Evolution (LTE) and 5G New Radio (5G NR), among others.

[0100] Automation Equipment and Can be configured to use slice network NS separately l1 and NS l2 Data Network DN i and DN j Communicate. Network Slice NS l1 and NS l2They are specifically assigned to levels l1 and l2 respectively, which means that only level l1 devices can use network slices NS l1 , and only level l2 devices can use network slicing NS l2 .

[0101] Network Slicing NS l1 At least two segments may be used to define. The first segment 407.1 at the base station level may be an access slice supporting different radio or fixed access at the base station. The second segment 409.1 at the core network level may be a core network slice providing one or more virtualized network functions. For example, an additional segment may be a first segment 407.1 and a second segment 409.1 connected to form an end-to-end network slice NS l1 Similarly, network slice NS l2 A network slice NS can be defined using at least two segments. l2 A first segment 407 . 2 at the base station 402 and a second segment 409 . 2 at the core network 404 may be included.

[0102] Figure 5 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0103] The wireless communication system 500 includes a cellular network 505. The cellular network 505 includes a base station 502, which communicates with the automation equipment via a transmission medium. and Communicate. Automation equipment and Can be part of a distributed manufacturing automation system. Automation equipment can belong to level l1 of the automation pyramid, and the automation equipment Can belong to level l2 of the automation pyramid. l1 can be any number between 1 and the total number of levels of the automation pyramid, K. l2 can be any number between 1 and the total number of levels of the automation pyramid, K, where l2 is different from l1. Automation equipment and Each of these can be a reference Figure 1 , Figure 2 and Figure 3 Any of the described field devices, automation devices, monitoring devices, and planning and analysis devices.

[0104] Base station 502 may be a base transceiver station (BTS) and may include a communication interface that enables communication with automation equipment. and Base station 502 can be coupled to core network 504. Core network 504 can also be coupled to a data network, such as data network DN k . Data Network DN k The base station 502 may be a network of distributed manufacturing automation systems or an external network. The external network may include the Internet, the public switched telephone network (PSTN), and / or any other network. Thus, the base station 502 may facilitate the automation equipment and With network 504DN k Communication between.

[0105] Base station 502 and automation equipment and It can be configured to communicate over a transmission medium using various radio access technologies (RATs), such as Long Term Evolution (LTE) and 5G New Radio (5G NR), among others.

[0106] Automation Equipment and Can be configured to use different slice networks NS l1 and NS l2 Same data network DN k To communicate, these automation devices belong to two different levels, l1 and l2. Slice Network NS l1 and NS l2 They are specifically assigned to levels l1 and l2 respectively, which means that only level l1 devices can use network slices NS l1 , and only level l2 devices can use network slicing NS l2 .

[0107] Figure 6 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0108] The wireless communication system 600 includes a cellular network 605. The cellular network 605 includes a base station 602, which communicates with the automation equipment via a transmission medium. and Communicate. Automation equipment and Can be part of a distributed manufacturing automation system. Automation equipment and Can belong to the same level l1 of the automation pyramid. l1 can be any number between 1 and the total number of levels K of the automation pyramid. Automation equipment and Each of these can be a reference Figure 1 , Figure 2 and Figure 3 Any of the described field devices, automation devices, monitoring devices, and planning and analysis devices.

[0109] Base station 602 may be a base transceiver station (BTS) and may include a communication interface that enables communication with automation equipment. and Base station 602 can be coupled to core network 604. Core network 604 can also be coupled to one or more data networks, such as data network DN i and DN j . Data Network DN i and DN j Each of the base stations 602 may be a network of a distributed manufacturing automation system or an external network. The external network may include the Internet, a public switched telephone network (PSTN), and / or any other network. Thus, the base station 602 may facilitate the automation equipment and With network 604, DN i and DN j Communication between.

[0110] Base station 602 and automation equipment and It can be configured to communicate over a transmission medium using various radio access technologies (RATs), such as Long Term Evolution (LTE) and 5G New Radio (5G NR), among others.

[0111] Automation Equipment and Can be configured to use the same slice network NS dedicated to level l1 l1 Data Network DN i and DN j This means that only level l1 devices can use network slices NS l1 .

[0112] Figure 6a A scheduling apparatus 610 of a system for implementing data communications at a distributed manufacturing automation system according to an example of the present subject matter is depicted.

[0113] The dispatching device 610 and / or the balancing device 610 are shown as different automation devices. A separate device between the cellular network 605. However, it may also include an automated device and / or cellular network 605. The dispatch device 610 may be implemented as an edge device and / or a concentrator to collect traffic at a certain location on the site, such as traffic from a factory.

[0114] In one example, if Figure 2 The lower the level in the hierarchical pyramid model shown, the closer the level is to the original data. The original data can be provided basically as analog data and / or bus data. The original data can also be provided as digital data in a bus protocol format after processing the analog data. In the example, the higher the level of the hierarchy, the more encapsulated data can be included in the exchanged data. For example, each hierarchical layer adds a header of a specific layer to the data. If the hierarchy is arranged according to the OSI network model, each layer adds its own PDU (protocol data unit). One and / or more interfaces of the automation device can be adapted to unpack and / or pack data according to the connected network hierarchy. The PDU can embed payload data, which is essentially data at the lowest hierarchical level, such as field device data.

[0115] In another example, the level of the hierarchical pyramid model can be indicated by a level indicator, a level identifier, and / or a level ID. The level indicator can be added to the data packets distributed in the network to show the association with the predefined level. Devices belonging to a specific level can be grouped together by using the same level indicator. The differentiation of participants in the functional level can be achieved by adopting a subnet mask, which is used to filter the predefined device function group and its members. The subnet mask can be a bit pattern that allows filtering of data packets and / or data streams by XOR operations. The level identifier can be a bit pattern in which the set bits represent the levels in the pyramid. For example, in a 5-bit header, the bit pattern 00001 represents level 1, 00010 represents level 2, and so on. In other words, the length of the level identifier corresponds to the number of available levels, and the position of the set bit in the header corresponds to the level associated with the data packet.

[0116] With automation equipment The dispatching device 610 may have a level identifier assigning device that receives input from a specific network 230, 233, 235, 237 of a certain level and adds a corresponding bit pattern to the traffic from the corresponding network. The bit pattern can be used for internal routing processes within the automation device. In the example, the dispatching device 610 can have different ports for connecting different networks corresponding to specific levels. For example, port 1 is assigned to the field device network, i.e. level 1, port 2 is assigned to the automation device network, i.e. level 2, and so on. Automation device May be part of such a port to connect to the relevant levels of the network 230, 233, 235, 237.

[0117] In another example, each level may form a separate network, such as a VLAN (virtual local area network). In such an example, devices belonging to the same level may be indicated as belonging to the same network. In an example, different devices may be distinguished by registering addresses (e.g., IP addresses, MAC addresses) in a network dedicated to a particular level.

[0118] Combinations of different level indicators and level assignments are possible.

[0119] The levels of the functional model can be mapped to quality parameters of the network and specific network parameters of the backbone network. One quality parameter can be latency and another parameter can be reliability.

[0120] In an example, a manufacturing device (e.g., a sensor) may request a predefined data transmission delay. Such a request is issued by sending a request packet. The scheduling means 610 may be adapted to verify whether the backbone network can meet the requested predefined quality in order to guarantee the same high latency required by devices at a certain level of the functional level of the functional model.

[0121] Therefore, the scheduling device 610 also has different slices NS l It maps a traffic profile to the corresponding slice.

[0122] The sensor data and / or field device data may be analog data. After preprocessing (eg, by an A / D converter), the sensor may also provide digital data. The scheduling device 610 may include such an A / D converter for direct sensor connection.

[0123] The scheduling means 610 may be adapted to schedule the data according to predefined criteria. For example, different levels may have different levels of latency. However, it may happen that a large amount of data arrives with a low latency requirement. However, the amount of data arriving is so large that it may not be processed by the connection and / or slice at a suitable latency level. Then, if there is a slice NS with a higher latency level when the data arrives, lThis connection can be used if the connection is available and / or unused. For example, field device data can be allocated to high latency requirements. Planning data can be allocated to low latency requirements. However, a large amount of data traffic suddenly appears, for example when backup is performed. If the activity of high latency levels (such as field devices) is low at the same time, the idle capacity can be used for lower priority traffic. In this case, the scheduling device 610 can allocate traffic (such as data items) to different channels, in particular to related cellular networks. Scheduling can allow the available frequency bands to be used efficiently. Operators in the industrial field do not have to pay additional fees for additional bandwidth within the predefined frequency bands. Therefore, the leased frequency bands can be optimally utilized.

[0124] The scheduling means 610 may be adapted to detect the configuration files of different devices in each group of devices and understand the characteristics of different network slices. Therefore, the scheduling means 610 may be adapted to assign the configuration files to the appropriate slices.

[0125] However, one of the devices may generate traffic of two or more types and / or profiles. When the scheduling device 610 identifies that different traffic profiles may need to be assigned to different slices, the scheduling device 610 may be adapted to extract sub-data items and / or different profile traffic and use a second network slice and / or a third network slice different from the first network slice for the different profiles and / or sub-data items.

[0126] In the campus network, there may also be dynamically controlled delays or any other characteristics that depend on specific locations. At a company site, it may be necessary to temporarily provide communication capabilities for some additional locations. For example, it may be temporarily necessary to perform some measurements in a specific factory by using special measuring equipment. In this case, this special measuring equipment may have high requirements for the delay of transmitting data. Having a scheduling device 610 that can be adapted to temporarily and / or dynamically set the delay level can increase the flexibility of the mobile network. This feature can be referred to as location-based delay and / or more generally as location-based slicing, because any characteristics and / or combination of characteristics of the slice can dynamically extract some traffic and put the traffic into the appropriate slice.

[0127] In an example, the scheduling device 610 may include a location detection device, such as a GPS receiver. Once the automation device detects a location on the campus, such as a location close to a factory using sensors with high latency requirements, the latency level can be automatically adjusted and the data item can be sent to each different slice of the cellular network according to the latency level.

[0128] In one example, the delay may correspond to the number of levels of the hierarchical pyramid model. For example, the hierarchical pyramid model may have 4 levels, wherein data from the field device level may use a quarter of the delay of level 4, and data from the third level may have a third of the delay of level 4, etc. The scheduling device 610 may have a delay exploration device that may request the field device, automation device, monitoring device, and / or planning and analysis device for its desired delay level.

[0129] The destination of the transmitted processing data and / or data items may be a receiver at a remote location. The receiver may be a server, a data network and / or another part of a VPN (Virtual Private Network).

[0130] Figure 2 The different networks 230, 233, 235, 237 can extend to different locations. In this case, the following can be done between the different networks: Figure 6a The slices shown. In other words, each network 230, 233, 235, 237 can be connected to a different slice. However, if, for example, field devices can generate different traffic profiles, some traffic may be assigned to an inappropriate network slice. For example, if field devices typically generate latency-sensitive traffic, this traffic can be routed to a slice with low latency. If traffic with low latency requirements occurs, this traffic can also be transmitted through slices with low latency, which may be costly. Therefore, extracting such traffic and moving it to a slice with high latency can reduce technical workload and free up bandwidth for other latency-sensitive traffic.

[0131] It is also possible that a device assigned to a device group with high latency requirements may be detected as not having high latency requirements through monitoring. The traffic of such a device may be diverted to a slice different from the slice according to the level of the functional model.

[0132] For example, a camera that generates constant pictures may not have high latency requirements. It may then be moved to a different layer of the functional model, which is different from the level classified according to device type. Therefore, the device may be scheduled at least temporarily according to the current traffic profile rather than the device type, and therefore, the scheduling device 610 may schedule the slice to the current traffic profile, the temporary profile and / or the location-based traffic profile.

[0133] Figure 7 is a flow chart of a method for a distributed manufacturing automation system configured, for example, as an automation pyramid.

[0134] In step 701, a network slice NS may be created. l(where l varies between 1 and K (i.e., the number of levels of the automation pyramid)) and assigns it to each level of the automation pyramid.

[0135] In step 703, the automation equipment at a specific level 1 of the automation pyramid You can use the network slice NS assigned to this level l End-to-end connection with data network.

[0136] Figure 8 is a flow chart of a method for a distributed manufacturing automation system, the system including multiple groups of devices, such as reference Figure 1 Shown are groups 113, 115, and 117. Each of the groups of equipment is configured to perform a corresponding type of control of the manufacturing process.

[0137] In step 711, network slices may be created and assigned to various groups of the distributed manufacturing automation system. Different network slices may be assigned to each of these groups.

[0138] In step 713, the automation devices of one of the groups may be connected end-to-end to the data network using the network slice assigned to the group.

[0139] Fig. 9 A system for implementing data communications at a distributed manufacturing automation system according to examples of the present subject matter is depicted.

[0140] The wireless communication system 800 includes a 5G cellular network 805. The cellular network 805 includes an access node (AN) 802, which communicates with an automation device 801 via a transmission medium. The automation device 801 may be part of a distributed manufacturing automation system. The automation device 801 may be a reference Figure 1 , Figure 2 and Figure 3 Any of the field devices, automation devices, monitoring devices, and planning and analysis devices described. The access node 802 can be coupled to the 5G core network 804. The core network 804 can also be coupled to the IT network and OT network of the distributed manufacturing automation system. The core network 804 can enable the AMF function 809 and the SMF function 810. The core network 804 can enable the UPF 811 for uplink classification and enable two UPFs (UPF1 and UPF2) as PDU session anchors.

[0141] The automation device 801 may establish a first PDU session with UPF1 via AN 802 to establish an end-to-end connection with the IT network. Alternatively, the automation device 801 may establish a second PDU session with UPF2 via AN 802 to establish an end-to-end connection with the OT network.

[0142] Fig.10 Depicted is an example simplified block diagram of an automation device according to examples of the present subject matter.

[0143] The automation device 900 may include a system on a chip (SOC) 901, which includes (multiple) processors 902, which may execute program instructions of the automation device 900. The (multiple) processors 902 may be coupled to a memory management unit (MMU) 903 of the SOC 901, which may be configured to receive addresses from the (multiple) processors 902 and convert these addresses into locations in a memory 904 of the SOC 901 and / or into other circuits or devices (such as cellular communication circuit systems). The automation device 900 may further include a cellular communication circuit system 906, such as for 5G, LTE, etc. The automation device 901 may further include two or more smart cards 908, such as two or more universal integrated circuit cards (UICCs) 908, each including SIM functionality. The cellular communication circuit system 906 may be coupled to one or more antennas, preferably to two antennas 910 and 912. It should be noted that Fig. 9 The automation device 900 shown may include several further elements or functions in addition to the elements or functions described below, which are omitted herein for the sake of simplicity, as they are not necessary for understanding.

[0144] The inclusion of two or more SIM cards 908 may allow the automation device to support two different identifiers and may allow the automation device 900 to communicate on corresponding two or more respective networks. The cellular communication circuit system 906 may include two different radios, each having a receive chain and a transmit chain. The two radios may support different RAT stacks.

[0145] The processor 902 is configured to perform processing related to the above-mentioned subject matter. For example, the processor 902 may be configured to perform Figure 7 or Figure 8 method.

[0146] As will be understood by those skilled in the art, aspects of the present invention may be embodied as devices, methods, computer programs, or computer program products. Thus, aspects of the present invention may take the form of fully hardware embodiments, fully software embodiments (including firmware, resident software, microcode, etc.), or embodiments of combined software and hardware aspects generally referred to herein as "circuits," "modules," or "systems." Additionally, aspects of the present invention may also take the form of a computer program product embodied in one or more computer-readable media having computer executable code embodied thereon. A computer program includes computer executable code or "program instructions."

[0147] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable storage medium. As used herein, "computer-readable storage medium" encompasses any tangible storage medium that can store instructions that can be executed by a processor of a computing device. The computer-readable storage medium may be referred to as a computer-readable non-transitory storage medium. The computer-readable storage medium may also be referred to as a tangible computer-readable medium. In some embodiments, a computer-readable storage medium may also be capable of storing data that can be accessed by a processor of a computing device.

[0148] "Computer memory" or "memory" is an example of a computer-readable storage medium. Computer memory is any memory directly accessible by a processor. "Computer storage" or "storage" is a further example of a computer-readable storage medium. Computer storage is any non-volatile computer-readable storage medium. In some embodiments, computer storage may also be computer memory and vice versa.

[0149] As used herein, "processor" encompasses an electronic component capable of executing a program or machine executable instructions or computer executable code. References to a computing device that includes a "processor" should be interpreted as possibly including more than one processor or processing core. The processor may, for example, be a multi-core processor. A processor may also refer to a collection of processors within a single computer system or distributed among multiple computer systems. The term computing device should also be interpreted as possibly referring to a collection or network of computing devices, each of which includes one or more processors. Computer executable code may be executed by multiple processors that may be located within the same computing device or may even be distributed across multiple computing devices.

[0150] Computer executable code may include machine executable instructions or programs that cause a processor to perform an aspect of the present invention. Computer executable code for performing the operations of various aspects of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​(such as Java, Smalltalk, C++, etc.) and conventional procedural programming languages ​​(such as "C" programming language or similar programming languages) and compiled into machine executable instructions. In some cases, the computer executable code may be in the form of a high-level language or in a precompiled form, and may be used in conjunction with an interpreter that generates machine executable instructions on the fly.

[0151] Typically, program instructions can be executed on one processor or on several processors. In the case of multiple processors, they can be distributed on several different entities. Each processor can execute the portion of instructions for that entity. Therefore, when referring to a system or process involving multiple entities, a computer program or program instructions is understood to be suitable for execution by a processor associated or related to the corresponding entity.

Claims

1. A distributed manufacturing automation system, the distributed manufacturing automation system comprising a plurality of groups of equipment, in, Each group of devices in each group of devices is configured to perform a corresponding type of control of a manufacturing process, the distributed manufacturing automation system includes a first device in a specific group of devices in the plurality of groups of devices, the first device including a device configured to perform an end-to-end connection with a data network using a first network slice, the first network slice being assigned to the specific group of devices; In which, the device of the first device in the group of devices is further configured to extract sub-data items and use a second network slice and / or a third network slice different from the first network slice.

2. The distributed manufacturing automation system according to claim 1, in, The device of the first device in the group of devices is further configured to determine which of the second network slice and / or the third network slice is suitable for use.

3. The distributed manufacturing automation system according to claim 2, in, Based on the monitoring operation, determine which of the second network slice and / or the third network slice is suitable for use.

4. The distributed manufacturing automation system according to claim 3, in, This monitoring operation includes machine learning.

5. A distributed manufacturing automation system as claimed in any one of the preceding claims, configured as an automation pyramid, in, Each of the plurality of groups belongs to a different level of the automation pyramid.

6. A distributed manufacturing automation system as claimed in any of the preceding claims, comprising a second device in another of the groups, the second device comprising a device configured to establish an end-to-end connection with the data network using a second network slice, the second network slice being specifically assigned to the other group.

7. In a distributed manufacturing automation system as described in any one of claims 5 to 6, the data network of the first network slice is a network at the first device level or another level of the automation pyramid, and the data network of the second network slice is a network at the second device level or another level of the automation pyramid.

8. A distributed manufacturing automation system as claimed in any one of the preceding claims, further comprising a cellular network comprising a base station and a core network device, in, The first network slice, the second network slice and / or another network slice respectively include a first user plane function network element, a second user plane function network element and another user plane function of the core network device.

9. The distributed manufacturing automation system according to any one of the preceding claims, wherein the data network is an information technology network and / or an operation technology network of the distributed manufacturing automation system.

10. A distributed manufacturing automation system as claimed in any of the preceding claims, wherein each of these network slices is configured according to a predefined latency value, throughput value and / or special security level.

11. The distributed manufacturing automation system according to claim 10, in, Data communications through the slice are protected according to the particular security level using at least one of: authentication, encryption, and slice isolation with exclusive network resources.

12. In a distributed manufacturing automation system as claimed in any of the preceding claims, each of the network slices is configured according to different values ​​of a performance parameter, the performance parameter comprising at least one of: availability, service area, isolation level, maximum packet size, maximum number of devices that can simultaneously use the network slice, and a radio spectrum to support the network slice.

13. A method for a distributed manufacturing automation system, the distributed manufacturing automation system comprising a plurality of groups of equipment, in, Each group of devices in the groups is configured to perform a corresponding type of control over a manufacturing process, and the method includes a first device in a specific group of these groups making an end-to-end connection to a data network using a first network slice, wherein the first network slice is specifically assigned to the specific group.

14. A computer program product comprising a computer-readable storage medium having a computer-readable program code embodied therein, the computer-readable program code being configured to implement the method of claim 13.

15. A device for a specific device group of a distributed manufacturing automation system, the device comprising a device configured to use a first network slice to establish an end-to-end connection with a data network, the first network slice being specifically assigned to the specific group.

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