CN113282399A - Industrial Internet system architecture - Google Patents
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- CN113282399A CN113282399A CN202110726359.7A CN202110726359A CN113282399A CN 113282399 A CN113282399 A CN 113282399A CN 202110726359 A CN202110726359 A CN 202110726359A CN 113282399 A CN113282399 A CN 113282399A
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
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- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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Abstract
The invention provides an industrial Internet system architecture, which comprises a perception network layer, a calculation communication layer, a production ecological layer and a scheduling decision layer; the perception network layer comprises a physical network formed by all production nodes, and the production nodes are used for producing based on production control instructions; the computing communication layer is used for acquiring and storing production elements and production results of each production node and providing cloud computing capability for other layers; the production ecological layer is used for receiving a scheduling decision instruction of the scheduling decision layer and generating the production control instruction of each production node so as to perform production control on each production node; and the scheduling decision layer is used for generating a scheduling decision instruction and sending the scheduling decision instruction to the production ecological layer. The framework of the invention realizes the cooperative control of each production node, adjusts the change of external production elements in a closed loop manner, quickly responds to market demands, fully utilizes the existing production elements and improves the production efficiency.
Description
Technical Field
The invention relates to the field of industrial internet, in particular to an industrial internet system architecture.
Background
Industrial internetworking is the result of the convergence of global industrial systems with advanced computing, analytics, sensing technologies and internet connectivity. The intelligent factory integrates the related technologies, sales and product experiences of the existing industry, creates an intelligent factory with adaptability and resource efficiency, integrates information of customers and business partners in business processes and value processes, and provides perfect after-sales service.
Fig. 1A shows the current industrial internet system architecture, which is an isolated internet structure, wherein the entire industrial chain is formed by a circle, and supply chain, personnel and production data are added to the circle to supply production, so as to finally generate a product supply market. The matters of department to department, person to person, person to door are interwoven in a circular plane.
Although the current industrial internet system architecture operation can generate a large amount of data coupling of personnel and materials, all departments still make serial decisions, the decision making time for completing all departments is long, and the efficiency of the industrial process cannot be improved; the production element data cannot be automatically updated in time, but the formation and operation of the production elements are determined by human factors, so that the efficiency is low and the operation is slow; production element data information cannot be shared with a centralized mode, the improvement of the whole production efficiency can be influenced by the change of any node, and the efficient operation of a production enterprise cannot be promoted by using information symmetry; the network structure can not ensure clear network input and output, the formation of blocked nodes is frequent, the fast changing growth requirement of the market and the increasing material upgrading requirement can not be adapted, and the production continuity and the health of the ecological chain are influenced.
Fig. 1B shows a network structure of cloud computing, which is a computing manner based on the internet, and realizes that common software and hardware resources (such as hardware resources in the middle of the cloud diagram of fig. 1B) are shared to various terminals and other devices of a computer as required through Hypervisor layer virtualization in fig. 1B. Due to the continuous development of virtualization technology, a plurality of virtual machines (VM in FIG. 1B) are virtualized in one cloud platform.
At present, a cloud management interface of cloud computing can only manage non-real-time virtual machines, cannot manage all real-time virtual machines in an industrial internet, cannot support computing capacity and network resource capacity of edge clouds, and a pure cloud management interface cannot manage the whole industrial internet.
The edge computing uses the edge gateway to control and adjust the state of the edge device, and an open platform integrating network, computing, storage and application core capabilities is adopted at one side close to an object or a data source to provide nearest-end service nearby. Fig. 1C is an example of an edge computing architecture and application, and the lower part is the resources of edge computing including CPU computing devices, memory devices, and some further including graphics card devices, which are typical edge applications above, for sensing, monitoring, drone control, robot control, and also including serial devices for debugging.
The current definition of edge computing only relates to the collection and filing of information flow of equipment related to the Internet of things, and cannot realize the cooperative operation of a real-time virtual machine and a non-real-time virtual machine. The computing and network capability and the service supporting capability are limited by computing power, the capability is limited, and large-scale service operation cannot be carried out.
Disclosure of Invention
In view of this, an embodiment of the present invention provides an industrial internet system architecture, where a computing communication layer shares external production elements and production results of each production node in real time, and provides a computing capability of edge cloud and center cloud cooperation for other layers, so as to implement cooperative control of each production node, adjust changes of the external production elements in a closed-loop manner, quickly respond to market demands, fully utilize existing production elements, and improve production efficiency.
The embodiment of the application provides an industrial Internet system architecture, which comprises a perception network layer, a calculation communication layer, a production ecological layer and a scheduling decision layer; the perception network layer comprises a physical network formed by all production nodes; each production node is used for acquiring external production elements from the outside of the architecture and reporting the external production elements to the computing communication layer; the system is also used for acquiring internal production elements from the computation communication layer, receiving production control instructions issued by the production ecological layer, performing relevant production activities by using the production elements and reporting production results to the computation communication layer; the production elements of each production node comprise external production elements and internal production elements thereof, and the internal production elements of each production node are external production elements and/or production results of other production nodes for production input; the computing communication layer is used for acquiring and storing external production elements and production results of each production node and sharing the external production elements and the production results in the whole architecture; the cloud computing power is provided for each production node of the production ecological layer, the scheduling decision layer and the perception network layer; the production elements of each production node comprise an external production element and an internal production element; the production ecological layer is used for receiving a scheduling decision instruction of the scheduling decision layer, and synchronously generating the production control instruction of each production node by utilizing the cloud computing capability of the computing communication layer based on the expected production elements of each production node so as to perform production control on each production node; and the scheduling decision layer is used for generating a scheduling decision instruction and sending the scheduling decision instruction to the production ecological layer.
Therefore, external production elements are obtained through the perception network layer, scheduling decision and production control of industrial production are achieved through data sharing and cloud computing of the computing communication layer, external changes are responded quickly, and production efficiency is improved.
In one possible implementation of an industrial internet system architecture, the computing communication layer comprises: each edge cloud is connected with each other, and the center cloud is connected with each edge cloud; the edge cloud is used for acquiring the existing production elements and production results of the related production nodes; the system is also used for providing edge cloud computing capacity for a production ecological layer and the related production nodes so as to generate the production control instructions of the related production nodes and control the production activities of the related production nodes; the central cloud is used for providing central cloud computing capacity for the scheduling decision layer and the production ecological layer; and the method is also used for storing the existing production elements and production results of the relevant production nodes of each edge cloud storage.
In the above way, the edge clouds connected with each other and the center cloud connected with the edge clouds are arranged on the computing communication layer of the framework, so that the data sharing and intelligent computing of cloud-edge cooperation are realized, and the real-time control production of the production ecological layer and the scheduling decision layer is realized.
In one possible implementation manner of the industrial internet system architecture, when the production node is a real-time operating system node, the edge cloud managing the production node has CPUs in one-to-one correspondence with the production node to exclusively manage the production node.
Therefore, compared with the conventional edge cloud incapable of managing the real-time system, the method and the device have the advantage that the production nodes of the real-time operating system are controlled by arranging the special CPU in the related edge cloud.
In one possible embodiment of an industrial internet system architecture, the production ecosystem includes a plurality of production control units, each production control unit generating production control instructions for at least one production node using expected production elements of the associated production node based on the associated scheduling decision instructions.
Therefore, the production activities of the production nodes are specifically controlled based on the production control units, so that the control of the whole production is realized.
In a possible implementation manner of an industrial internet system architecture, the scheduling decision layer is further specifically configured to generate a comprehensive production result by using the cloud computing capability based on the production elements and the production results of each node; and the cloud computing capacity adjustment scheduling decision instruction is further specifically used for adjusting the scheduling decision instruction by using the cloud computing capacity based on the production elements and/or the production results and/or the comprehensive production results of the production nodes, and sending the scheduling decision instruction to the production ecological layer.
In the above, the scheduling decision layer adjusts the scheduling decision instruction based on the production elements and/or the production results and/or the comprehensive production results, and quickly responds to market needs or supply chain changes.
In a possible implementation manner of an industrial internet system architecture, the scheduling decision layer is further configured to generate a production prediction instruction and send the production prediction instruction to the production ecological layer; the scheduling decision instruction is generated by utilizing the cloud computing capability of the computing communication layer based on the prediction result of the production ecological layer and is sent to the production ecological layer to control production; the production ecological layer is also used for carrying out production prediction on the activity of each production node by utilizing the cloud computing capability of the computing communication layer based on the production prediction instruction and sending the prediction result to the scheduling decision layer.
From the above, the production ecological layer realizes the production prediction of specific production nodes, and the scheduling decision layer is converted into a scheduling decision instruction, so that the closed loop from the production prediction to the production control is realized.
In a possible implementation manner of an industrial internet system architecture, the production ecological layer is further configured to generate a prediction control instruction based on a production prediction instruction by using cloud computing capability of the computing communication layer, and issue the prediction control instruction to each production node; and each production node performs production prediction by utilizing the cloud computing capability of the computing communication layer based on the prediction control instruction, and sends the node prediction result to the production ecological layer for generating the prediction result of the production ecological layer.
Therefore, each intelligent production node participates in production prediction, so that the prediction is more accurate.
In one possible implementation of an industrial internet system architecture, the scheduling decision layer is specifically configured to generate production forecast instructions based on changes in external production elements obtained by company targets or production nodes.
Therefore, production prediction based on the company target enables each production node to be configured properly to achieve the company target, and production prediction based on major changes of external production elements enables each production node to quickly synchronize corresponding external requirements, so that production efficiency is improved.
In one possible implementation of an industrial internet system architecture, the production nodes include at least a manufacturing node, a research and development node, a purchasing node, a logistics node, a human management node, a financial node, and a marketing node.
From above, each node of industrial chain has been covered to the production node, realizes the whole synchronous control from supply chain and logistics storage, to financial affairs, manpower resources and manufacturing, and then to selling.
In one possible implementation of an industrial internet system architecture, the central cloud is further configured to share the computing tasks of an edge cloud when the computing power of the edge cloud is insufficient.
Therefore, the central cloud is used as the capability supplement of each edge cloud, the computing capability and the safety of the edge elements are improved, and the industrial control capability of each framework is improved.
Drawings
FIG. 1A is a schematic diagram of a conventional industrial Internet system architecture;
FIG. 1B is a schematic diagram of a cloud computing network;
FIG. 1C is a schematic diagram of an edge computing network;
FIG. 2 is a schematic diagram of a first embodiment of an industrial Internet system architecture according to the present application;
fig. 3 is a schematic structural diagram of connection between an edge cloud and a central cloud according to a first embodiment of the present application;
FIG. 4A is a schematic diagram of a process control flow of a first embodiment of an industrial Internet system architecture of the present application;
FIG. 4B is a schematic diagram of a production adjustment process according to a first embodiment of an industrial Internet system architecture of the present application;
fig. 4C is a schematic diagram of a scheduling adjustment flow according to a first embodiment of an industrial internet system architecture of the present application;
FIG. 5A is a schematic view of a target prediction flow of a second embodiment of an industrial Internet system architecture of the present application;
FIG. 5B is a schematic diagram illustrating an element prediction process according to a second embodiment of the present disclosure;
fig. 6 is a schematic flow chart of an embodiment of industrial internet construction according to the present application.
Detailed Description
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
In the following description, references to the terms "first \ second \ third, etc." or module a, module B, module C, etc. are used solely to distinguish between similar objects or different embodiments and are not intended to imply a particular ordering with respect to the objects, it being understood that where permissible any particular ordering or sequence may be interchanged to enable embodiments of the invention described herein to be practiced otherwise than as shown or described herein.
In the following description, reference to reference numerals indicating steps, such as S110, S120 … …, etc., does not necessarily indicate that the steps are performed in this order, and the order of the preceding and following steps may be interchanged or performed simultaneously, where permissible.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.
According to the embodiment of the application, the edge clouds are used for connecting the production nodes, the central clouds cooperate with the edge clouds to control the production nodes, the set target scheduling based on company planning and the production activity of the production nodes can be achieved, the change of external production elements can be responded in a closed loop mode, the work production efficiency is improved, and the customer requirements are responded quickly.
An embodiment of an industrial internet system architecture according to the present invention is described below with reference to fig. 2 to 6.
[ embodiment of Industrial Internet System architecture ] for implementing the method
Fig. 2 shows a structure of an industrial internet system architecture embodiment one of the embodiments of the present invention, which includes a sensing network layer, a computing communication layer, a production ecological layer and a scheduling decision layer.
The perception network layer comprises a physical network formed by all production nodes; the system comprises a framework, a computing communication layer and a plurality of production nodes, wherein the framework is used for acquiring external production elements from the outside of the framework by each production node and reporting the external production elements to the computing communication layer; the system is also used for receiving a production control instruction issued by the production ecological layer through the external communication layer and carrying out related production based on the existing production elements.
Illustratively, the production node comprises: the system comprises a manufacturing node, a research and development node, a purchasing node, a logistics node, a manpower management node, a financial node and a marketing node, wherein each production node comprises a plurality of sub-nodes. Node types can be increased or decreased according to actual requirements.
The production elements are necessary resources for each production node to perform the activity of the node, and the resources comprise material resources, technical resources and information resources. The method is divided into an external production element and an internal production element from an acquisition path, wherein the external production element is acquired from the outside of the framework, and the internal production element is an external production element and a production result acquired by other production nodes required by the production node for carrying out production activities. While the production elements of each production node are represented in different forms.
Illustratively, the production elements of the manufacturing node are manufacturing elements, including at least manufacturing raw materials, manufacturing equipment, manufacturing processes, energy sources, and manufacturing labor; the production elements of the marketing node are marketing elements and at least comprise: customer needs, competitive information, point of sale, sales personnel, marketers.
The production results for each production node appear in different forms. Illustratively, the production result of the manufacturing node is the yield of the product, and the production result of the marketing node is the sales volume of the product.
The production activities of each production node also appear in different forms. Illustratively, the production activity of the manufacturing node is manufacturing activity, manufacturing is carried out by utilizing the real-time sensed production elements based on the production control instruction of the manufacturing node, products meeting different specifications of the production control instruction are manufactured, and at least production cost control, energy consumption control and production safety guarantee are realized in the generation process; the production activities of the marketing nodes are marketing activities, the production control instructions based on the marketing nodes utilize the production elements which are perceived in real time to carry out activities such as customer market expansion and product marketing, the product sales volume is realized, and at least sales profit achievement, customer demand management, sales channel management and sales cost control are realized in the marketing process.
Therefore, each production node acquires the external production elements from the outside of the framework and shares the external production elements with the whole network, and produces the production nodes in real time based on the acquired external production elements and internal production elements in a coordinated manner with other production nodes.
The computing communication layer is used for collecting and storing the acquired production elements and the production results of the production nodes of the perception network layer, and the production elements and the production results are shared in the whole framework. The computing communication layer is also used for providing cloud computing capability for production nodes of the production status layer, the scheduling decision layer and the perception network layer.
The computing communication layer comprises: each edge cloud connected to each other and a center cloud connected to each edge cloud.
The edge cloud is used for managing and controlling each production node, acquiring and storing external production elements and generated production results obtained by the production nodes connected with the edge cloud, and sharing the external production elements and the generated production results in the whole framework through the center cloud; the edge cloud is also used for providing edge cloud computing capacity for the production ecological layer so as to generate production control instructions of all production nodes connected with the edge cloud computing capacity; the edge cloud is also used for providing edge cloud computing capacity for the production nodes connected with the edge cloud, and each production node is enabled to carry out internal control on production activities.
The edge cloud is typically deployed near each production node to enable fast and secure control of the production nodes to which it is connected. When the production node is a real-time operating system node, the edge cloud managing the production node has a CPU in one-to-one correspondence with the production node to exclusively manage the production node, illustratively, the edge cloud is provided with a fixed computer (having an independent CPU) in one-to-one correspondence, and the production node of the real-time operating system is exclusively managed with the computer provided through a special routing relationship; or the edge cloud adopts a heterogeneous system architecture, and the CPUs which are in one-to-one correspondence with the production nodes of the real-time operating system are reserved while the production nodes of the non-real-time system are managed, so that the edge cloud is specially used for managing the production nodes of the real-time operating system.
The central cloud is used for providing central cloud computing capacity for the production ecological layer and the scheduling decision layer; and the method is also used for sharing the computing task of an edge cloud when the computing capacity of the edge cloud is insufficient.
Fig. 3 shows a connection relationship between an edge cloud and a center cloud of a computing communication layer, where the edge cloud is generally deployed near each production node to achieve fast and secure control over the production nodes connected thereto. Each production control unit described later of the production ecolayer is connected with the relevant edge cloud to realize the control of the relevant production node. The central cloud is connected with each edge cloud, the data of each edge cloud is synchronously stored, and the computing power of each edge cloud is cooperatively supplemented. In addition, the scheduling decision layer is mainly connected with the central cloud, and is not expressed in the figure.
Therefore, the computing communication layer realizes real-time sharing of the data of the whole architecture, and each production node comprising a manufacturing node, a research and development node, a purchasing node, a logistics node, a manpower management node, a financial node and a marketing node can quickly respond to the change of the external customer requirement or the change of a supply chain. The computing communication layer provides cooperative edge cloud computing capability and center cloud computing capability for the perception network layer, the production ecological layer and the scheduling decision layer, so that producers of all nodes corresponding to the perception network layer, department managers corresponding to the production ecological layer and high-level managers corresponding to the scheduling decision layer are integrated, and the external market change is responded based on the prediction closed loop. Preferably, compared with the conventional edge cloud incapable of managing the real-time system, the method and the device have the advantage that the production nodes of the real-time operating system are controlled by arranging the special CPU in the related edge cloud.
The production ecological layer is used for receiving the scheduling decision instructions of the scheduling decision layer, and synchronously generating the production control instructions of the production nodes by using the cloud computing capability of the computing communication layer based on the expected production elements of the relevant production nodes so as to perform production control on the production nodes. The expected production elements include requirements for associated production elements in scheduling decisions and the production control instructions for associated production nodes.
Specifically, the production ecological layer includes a plurality of production control units, and the user who the production control unit of every production node corresponds is the management layer of corresponding department, and each department management layer sets up the production control model of the production control unit that corresponds based on the scheduling decision instruction, generates at least one production node through cloud computing generate control instruction, production control instruction still is used for controlling the production progress, the production mode of relevant production node, the production factor and the production process control of use.
Illustratively, the production ecosystem comprises at least the following production control units:
the digital process and manufacturing auxiliary unit controls the production of the manufacturing nodes;
the quality management unit controls the product quality detection automation of the manufacturing node;
the equipment health management unit is used for controlling equipment condition monitoring and troubleshooting of the manufacturing nodes;
the production monitoring and analyzing unit is used for controlling the production monitoring and production analysis of the manufacturing nodes;
the energy consumption and emission management unit controls the energy consumption and emission of the manufacturing nodes;
the production management optimization unit controls the automatic coordination of the purchasing node, the logistics node, the manufacturing node and the marketing node;
the digital design and simulation verification unit controls the automatic matching of the research and development node and the manufacturing node;
the supply chain management unit controls the activities of the purchasing node and the logistics node;
the personalized user-defined service management unit controls the automatic coordination of the marketing node, the research and development node, the manufacturing node, the purchasing node and the supply node;
the customer management unit is used for controlling customer demand management, customer purchase amount and sales margin achievement control, customer delivery management and customer feedback management of a sales department;
the financial service unit controls financial control of the financial node, the marketing node and the purchasing node, and at least comprises financial cost control, financing cost control and cash flow control;
the manpower management unit controls a manpower management node recruitment plan, a cultivation plan, personnel efficiency improvement and a personnel compensation plan;
and the safety management service unit controls the cultivation, propaganda and monitoring of the safety production capacity of each production node.
When the production control unit of the production ecological layer performs relevant production control, the production control model of the unit is set, and production control instructions are automatically generated by using relevant predicted production elements and are issued to each production node. And in the production activity, modifying the relevant production control model and modifying the production control instruction based on the production result of each node so as to optimize the relevant production activity.
It is emphasized that since some production control units need to use the production control instruction content of other nodes as part of the intended production element, the production control units produce the production control instructions sequentially in sequence. But the production control instruction is synchronously issued to the corresponding production nodes to implement synchronous control.
It is further emphasized that when a plurality of production control units generate production control commands to the same node, each production control unit cooperatively predicts that one of the production control units will issue a production control command.
From the above, each production control unit of the production ecological layer cooperatively controls each production node based on the shared expected production elements, so that each production node synchronously performs production activities, and the corresponding external market demand and supply chain change are closed-loop.
The scheduling decision layer is used for generating a scheduling decision instruction and sending the scheduling decision instruction to the production ecological layer; the central cloud computing system is also used for generating a comprehensive operation result by utilizing the central cloud computing capacity based on the production result of each node; and the scheduling decision instruction is adjusted based on the production elements and/or the production results and/or the comprehensive production results of the nodes and is sent to the production ecological layer.
And the operator of the scheduling decision layer is a high-level management layer of the company, makes a scheduling decision instruction based on a set target of the company, performs scheduling decision based on large change of customer demands, and generates or modifies and schedules the scheduling decision instruction.
Illustratively, the scheduling decision instructions include, but are not limited to, one or more of the following: a product production plan, a cost plan, a procurement plan, a logistics plan, a manpower plan, and a financial plan; scheduling decision instructions in terms of social goals also include, but are not limited to, one or more of the following: energy consumption control plans, pollution control plans, and safety production plans.
It is noted that the scheduling decision instruction has some adjustable elastic space.
The scheduling decision layer is also used for generating a comprehensive production result by utilizing the central cloud computing capacity based on the production result of each node; and the scheduling decision layer is also used for adjusting scheduling decision instructions based on the production elements and/or the production results and/or the comprehensive production results of the production nodes, and sending the scheduling decision instructions to the production ecological layer, wherein the adjustment is in the elastic space of the scheduling decision instructions. The comprehensive operation result reflects the overall operation condition of the company and at least comprises one of the following conditions: the system comprises a production progress report, a product quality report, a raw material inventory report, a product inventory report, a labor efficiency report, an equipment operation report, a unit energy consumption report, a pollution emission report and a safety generation report.
In the above, the scheduling decision layer performs scheduling decisions based on the company target to achieve the company set target, adjusts the scheduling decisions based on the production result or the comprehensive production result to make the scheduling decisions automatically adapt to the actual production flow, and adjusts the scheduling decisions based on the change of the production elements to make the scheduling decisions quickly respond to the change of the external market demand or the supply chain, and the like.
The following describes a production process of an embodiment of an industrial internet system architecture, which includes a production control process, a production adjustment process, and a scheduling adjustment process. The production control flow is a flow for controlling the whole production based on a scheduling decision, the production adjustment flow is a production control instruction for adjusting a specific production node based on a production result in a production ecological layer, and the scheduling adjustment flow is a scheduling decision instruction for adjusting a scheduling decision in an elastic space of a scheduling decision by a scheduling decision layer.
[ PRODUCTION CONTROL FLOW ]
Fig. 4A shows a production control flow of an embodiment of an industrial internet system architecture, which includes the following steps:
and S1010, generating or adjusting a scheduling decision instruction by the scheduling decision layer, and issuing the scheduling decision instruction to the production ecological layer.
The operator of the scheduling decision layer is a high-level management layer of the company, the scheduling decision instruction is made based on the set target of the company, and/or the scheduling decision instruction is modified based on the important change of the customer demand or the production result of the company.
And S1020, the production ecological layer calls the cloud computing capacity of the computing communication layer to compute and generate a production control instruction by utilizing the expected production elements based on the scheduling decision instruction.
The production ecological layer comprises a plurality of production control units, each production control unit is provided with a production control model, cloud computing capacity of the edge cloud connected with relevant production nodes is called, and production control instructions of one or more production nodes are generated. When the capacity of the edge cloud is insufficient, the operation is automatically switched to the central cloud.
And S1030, the production ecological layer sends the production control instruction to the production node of the perception network layer through the calculation communication layer.
And each production control unit of the production ecological layer sends a production control instruction to the corresponding production node through the related edge cloud, or sends the production control instruction to the corresponding production node through the child node of the center cloud.
S1040, the perception network layer carries out production related activities based on the production control instructions and reports production results and the use conditions of production elements to the calculation communication layer.
And each production node of the perception network layer utilizes the production element to carry out production activity based on the production control instruction, generates a production result, and reports the production result and the condition of the production element to the computing communication layer so as to be shared by the whole architecture. The status of the production element includes usage and availability of the production element.
And S1050, the production ecological layer acquires the production results of the production nodes stored in the calculation communication layer.
The production ecological layer respectively obtains corresponding production results to evaluate whether the control of each production control unit meets the requirements or not, and production control instructions are adjusted. Please refer to the production adjustment process below for a method for adjusting production control commands based on production results.
S1060, the scheduling decision layer obtains the production result and the existing production elements, and generates a comprehensive operation result by using the central cloud computing capability of the computing communication layer.
The scheduling decision layer is provided with a comprehensive operation model, and a comprehensive operation result is generated by utilizing the central cloud computing capability of the computing communication layer based on the production result of each production node. The comprehensive operation result is used for comprehensively evaluating the production condition. The method for adjusting the scheduling decision instruction based on the comprehensive operation result refers to the following scheduling adjustment flow.
[ PRODUCT ADJUSTING FLOW ]
Fig. 4B shows a production adjustment flow of an embodiment one of the industrial internet system architectures, which includes the following steps:
s1110, determining whether the production result meets the expectation by the production ecological layer?
And each production control unit of the production ecological layer analyzes whether the production result of the related production node meets the expectation or not based on the received scheduling decision instruction. Illustratively, each production control unit generates a production control instruction based on a production control model, and if the set production control model deviates from the production process, the production result does not meet the expectation; illustratively, customer requirements change the color requirements of a product, and a production control model that controls the manufacturing process needs to be adjusted.
If the production result is not expected, the process proceeds to step S1140, and if the production result is not expected, the process proceeds to step S1120.
S1120, the production ecological layer determines whether the production control command is adjustable?
Wherein, each production control unit of the production ecological layer judges whether the expected production result is achieved by changing the production control model, namely, whether the production control command is adjustable is judged. If the production control command can be adjusted, go to step S1130; otherwise, go to step S1150 to adjust the scheduling decision instruction.
S1130, adjusting the production control command by the production ecological layer.
And each production control unit of the production ecological layer calls related cloud computing capacity and adjusts a production control instruction by changing a production control model.
S1140, step S1040 of the production control flow is executed to perform production control of each production node and the subsequent flow thereof.
S1150, executing the step S1010 of the production control flow to adjust the scheduling decision instruction and the subsequent flow thereof.
[ Schedule adjustment procedure ]
Fig. 4C shows a scheduling adjustment process according to a first embodiment of the industrial internet system architecture, which includes the following steps:
s1210, the scheduling decision layer determines whether the production result or the integrated operation result meets expectations?
Wherein, when the production result or the comprehensive operation result is in accordance with the expectation, the step S1220 is carried out; otherwise, the process proceeds to step S1230.
And S1220, keeping a scheduling decision instruction, and executing the step S1040 of the production control flow to control the production of each production node and carry out the subsequent flow.
S1230, executing the step S1010 of the production control flow to adjust the scheduling decision instruction and the subsequent flow thereof.
In summary, in the first embodiment of the architecture of the industrial internet system, each production node in the sensing network layer senses the change of the external production element in real time, and synchronously and cooperatively produces under the control of the production ecological layer; the computing communication layer shares all production elements and production results and provides corresponding central cloud computing or edge cloud computing for other layers of the architecture; synchronously generating production control instructions by all production control units of the production ecological layer to control the production activities of all production nodes; the scheduling decision layer carries out scheduling decision based on the company target to achieve the set target of the company, carries out adjustment scheduling decision based on the production result or the comprehensive production result to enable the scheduling decision to automatically adapt to the actual production flow, adjusts the scheduling decision based on the change of the production element to enable the scheduling decision to quickly respond to the change of the external market demand or the supply chain, and the like, and adjusts the scheduling decision based on the change of the production element to enable the scheduling decision to quickly respond to the change of the external market demand or the supply chain, and the like. Therefore, compared with the existing industrial internet system architecture, the embodiment of the industrial internet system architecture not only improves the efficiency of industrial production, but also improves the correspondence to external changes.
(II) Industrial Internet System architecture embodiment
Continuing with fig. 2 as the structure of the second embodiment of the industrial internet system architecture, the second embodiment of the industrial internet system architecture inherits the structure and the functions of each layer in the first embodiment of the industrial internet system architecture, and has all the advantages of the first embodiment of the industrial internet system architecture. Meanwhile, in order to realize industrial prediction, the related layers of the architecture are added with the following functions:
the scheduling decision layer is also used for generating a production prediction instruction and sending the production prediction instruction to the production ecological layer; and the scheduling decision instruction is generated based on the prediction result of the production ecological layer and is sent to the production ecological layer for production control.
When planning a company, the company management department calls the computing capacity of the center cloud based on the set target of the company to generate a production prediction instruction. And when the overall production is influenced by the major change of the external production elements of each production node in the production process, the production prediction is also carried out to generate a production prediction instruction. The production forecast instructions include multiple forecasts of manufacturing, manufacturing processes, sales, finance, purchasing, logistics, and human resources. The set goals include business goals and/or social goals, which may be determined on a periodic schedule, such as year or quarter, for a given company.
And when the scheduling decision instruction is generated on the basis of the prediction result of the production ecological layer, the scheduling decision instruction is generated on the basis of the prediction result of the production ecological layer by utilizing the cloud computing capability of the computing communication layer, and is issued to the production ecological layer.
The production ecological layer is also used for carrying out production prediction on the activity of each production node by utilizing the cloud computing capability of the computing communication layer based on the production prediction instruction and sending the prediction result to the scheduling decision layer.
The production control unit of the production ecological layer not only has a production control function, but also has a production prediction function, and the best set target, the target of each production node and important production element requirements are predicted to be achieved. Illustratively, the predicted outcome includes at least the following: product yield, gross profit, net profit, energy consumption and pollution discharge of unit yield, important raw material supply demand, manpower demand, production process improvement demand, cash demand. The prediction result also includes the influence on the set target when the production element is changed.
When the production ecological layer needs related production node auxiliary prediction for production prediction, the production ecological layer is also used for generating a prediction control command by utilizing the cloud computing capability of the computing communication layer based on the production prediction command and issuing the prediction control command to each production node. And
and each production node performs production prediction by utilizing the cloud computing capability of the computing communication layer based on the prediction control instruction, and sends the node prediction result to the production ecological layer for generating the prediction result of the production ecological layer.
The prediction process of the second embodiment of the industrial internet system architecture is described below, which includes a target prediction process and an element prediction process. The target prediction process is a process for carrying out production prediction based on a set target planned by a company, and the element prediction process is a process for carrying out production prediction based on significant changes of external production elements. How the above-described flows are implemented in the architecture is described below, respectively.
[ Objective prediction procedure ]
FIG. 5A shows a target prediction flow of an embodiment of an industrial Internet system architecture II, which comprises the following steps:
and S2010, the scheduling decision layer generates a production prediction instruction based on the annual set target and issues the production prediction instruction to the production ecological layer.
The scheduling decision layer is provided with a production prediction model, decomposes the annual set target by using the central cloud computing capability of the computing communication layer, generates a production prediction instruction and issues the production prediction instruction to each production control unit of the production ecological layer.
S2020, the production ecological layer carries out production prediction based on the production prediction instruction and sends a prediction result to the scheduling decision layer.
Each production control unit of the production ecological layer configures a production prediction model to call related edge cloud computing capacity to predict based on related production prediction instructions, and the prediction result is sent to a scheduling decision layer through a computing communication layer.
Wherein, some production control units utilize the production node to help them to complete the prediction function, and the concrete steps are as follows:
and S2022, the production control unit generates a prediction control command and sends the prediction control command to the production node.
When the production nodes are required to participate in prediction, the related production control units generate prediction control instructions by using related edge cloud computing capacity and send the prediction control instructions to the related production nodes through a computing communication layer.
And S2024, generating a node prediction result by the production node based on the prediction control instruction, and sending the node prediction result to the production control unit.
The production node generates a node prediction result by utilizing the related edge cloud computing capability based on the prediction control instruction, and sends the node prediction result to the production control unit through the computing communication layer.
S2026, the production control unit generates a prediction result by using the node prediction result of the production node.
S2030, the scheduling decision layer generates a scheduling decision instruction based on the prediction result.
The scheduling decision layer is provided with a production scheduling model, calls the cloud computing capacity of the center based on the prediction result of each production unit of the production ecological layer, generates a scheduling decision instruction and issues the scheduling decision instruction to the production ecological layer.
S2040, step S1010 of executing the production control flow of the first embodiment of the architecture, and the subsequent steps, perform production control by issuing a scheduling decision-making adjustment instruction.
[ element prediction procedure ]
Fig. 5B shows an element prediction flow of an embodiment of an industrial internet system architecture two, which includes the following steps:
and S2110, the sensing network layer acquires the significant changes of the external production elements and reports the changes to the calculation scheduling decision layer through the calculation communication layer.
When the external production element is changed significantly, the original scheduling decision instruction cannot be adjusted in the elastic space of the original scheduling decision instruction based on the fact that the original scheduling decision instruction cannot achieve the set target. Illustratively, a customer's demand for a doubled product or some raw material cannot supply the significant changes that are part of the external production factor.
S2120, the scheduling decision layer generates a production prediction instruction based on the significant change of the external production element.
And the scheduling decision layer decomposes the influence of the major change of the production elements to generate a production prediction instruction, and sends the production prediction instruction to each production scheduling unit of the production ecological layer.
S2130, executing the step S2020 of the target prediction process to perform production prediction and subsequent processes.
In summary, the scheduling decision layer, the production ecological layer and the perception network layer of the second embodiment of the industrial internet system architecture add functions in relevant production prediction, so that not only is production prediction based on company targets realized, but also production prediction is performed by perceiving significant changes of the external production elements, and new scheduling decision instructions are generated to respond to external changes in real time.
[ an industrial Internet construction example ]
Fig. 6 shows a flow of an embodiment of industrial internet construction of the present application, which includes the following steps:
s310, decoupling the industrial chain process, and determining cloud requirements of each production node, the production ecological layer and the scheduling decision layer.
The cloud requirements include at least data capacity requirements, computing power requirements, and network requirements.
And S320, determining the configuration of each edge cloud based on the cloud requirements of each production node and the production ecological layer.
Wherein the configuration of the edge cloud comprises an edge cloud physical device and an edge cloud software device; the edge cloud physical device at least comprises: the server, the firewall, the router, the local storage and the edge cloud software equipment at least comprise: operating system, cloud related components.
S330, determining the configuration of the central cloud based on the cloud requirement of the scheduling decision layer and the redundancy requirement of each edge cloud.
The configuration of the central cloud comprises edge cloud physical equipment and central cloud software equipment, and the central cloud physical equipment at least comprises: the system comprises a server, a switch, a firewall, a router, a disk array and a load balancer; the central cloud software device at least comprises: operating system, cloud related components. The load balancer is used for detecting the computing power of the edge cloud, and when the computing power of the edge cloud is insufficient, the central cloud is used for supplementing the computing power of the edge cloud.
And S340, building a physical network of the industrial Internet.
The method comprises the steps of building edge clouds of a center cloud and each production node, connecting the center cloud with each edge cloud, connecting each production node with each edge cloud, forming a physical network of the industrial internet with the cooperation of cloud and edge, configuring a network management system of the working internet, managing the center cloud and each edge cloud device, and supporting software import and configuration of the center cloud and each edge.
And S350, importing software and a model supporting the industrial process, and establishing a control function of the industrial Internet.
And importing control software of each production node into each edge cloud, and realizing the control of the production nodes by using the existing interfaces of the production nodes. Leading software of each production control unit of the production ecological layer into the central cloud, and configuring a related production control model to enable the central cloud and the edge cloud to cooperatively control each production node; and meanwhile, relevant production prediction models are configured, so that the production prediction of relevant nodes and production prediction results are realized. Importing software of a scheduling decision layer into the central cloud, configuring a comprehensive operation model, and calculating and analyzing a produced comprehensive operation result to modify a scheduling decision; and meanwhile, a production scheduling model is configured, and a scheduling decision instruction is generated based on a prediction result.
The industrial internet is built, and the whole production process can be subjected to closed-loop control after the debugging is successful.
In summary, the decoupling industrial chain process is implemented in the embodiment, based on the requirements of each production node, a cloud-edge cooperative industrial internet physical network is built, various control and decision-making software and models are introduced, an industrial control function is enabled, and the industrial internet that the closed loop is sensed externally and the efficiency is improved internally is realized.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in more detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention.
Claims (9)
1. An industrial internet system architecture is characterized by comprising a perception network layer, a calculation communication layer, a production ecological layer and a scheduling decision layer;
the perception network layer comprises a physical network formed by all production nodes; each production node is used for acquiring external production elements and reporting the external production elements to the computing communication layer; the system is also used for acquiring internal production elements from the computation communication layer, receiving production control instructions issued by the production ecological layer, performing relevant production activities by using the production elements and reporting production results to the computation communication layer; wherein, the internal production element is an external production element and/or a production result of other production nodes for production input of the production node; the production elements of each production node include the external production elements thereof and the internal production elements thereof;
the computing communication layer is used for collecting and storing the production elements and the production results of the production nodes and sharing the production elements and the production results in the whole architecture; the cloud computing power is provided for each production node of the production ecological layer, the scheduling decision layer and the perception network layer;
the production ecological layer is used for receiving a scheduling decision instruction of the scheduling decision layer, and synchronously generating the production control instruction of each production node by utilizing the cloud computing capability of the computing communication layer based on the production elements expected by each production node so as to perform production control on each production node;
and the scheduling decision layer is used for generating a scheduling decision instruction and sending the scheduling decision instruction to the production ecological layer.
2. The architecture of claim 1, wherein the computing communication layer comprises: each edge cloud is connected with each other, and the center cloud is connected with each edge cloud;
the edge cloud is used for acquiring the existing production elements and production results of the related production nodes; the system is also used for providing edge cloud computing capacity for a production ecological layer and the related production nodes so as to generate the production control instructions of the related production nodes and control the production activities of the related production nodes;
the central cloud is used for providing central cloud computing capacity for the scheduling decision layer and the production ecological layer; and also for storing the production elements and production achievements for the associated production nodes of each edge cloud.
3. The architecture of claim 2, wherein when the production node is a real-time operating system node, the edge cloud managing the production node has a one-to-one correspondence of CPUs to the production node for managing the production node exclusively.
4. The architecture of claim 2,
the production ecosystem includes a plurality of production control units, each production control unit generating production control instructions for at least one production node using the expected production elements for the associated production node based on the associated scheduling decision instructions.
5. The architecture of claim 2,
the scheduling decision layer is further specifically used for generating a comprehensive production result by utilizing the cloud computing capacity based on the production elements and the production results of the production nodes; and the cloud computing capacity adjustment scheduling decision instruction is further specifically used for adjusting the scheduling decision instruction by using the cloud computing capacity based on the production elements and/or the production results and/or the comprehensive production results of the production nodes, and sending the scheduling decision instruction to the production ecological layer.
6. The architecture of claim 1,
the scheduling decision layer is also used for generating a production prediction instruction and issuing the production prediction instruction to the production ecological layer; the scheduling decision instruction is generated by utilizing the cloud computing capability of the computing communication layer based on the prediction result of the production ecological layer and is sent to the production ecological layer to control production;
the production ecological layer is also used for carrying out production prediction on the activity of each production node by utilizing the cloud computing capability of the computing communication layer based on the production prediction instruction and sending the prediction result to the scheduling decision layer.
7. The architecture of claim 6,
the production ecological layer is also used for generating a prediction control instruction by utilizing the cloud computing capability of the computing communication layer based on the production prediction instruction and issuing the prediction control instruction to each production node;
and each production node performs production prediction by utilizing the cloud computing capability of the computing communication layer based on the prediction control instruction, and sends the node prediction result to the production ecological layer for generating the prediction result of the production ecological layer.
8. The architecture of claim 7, wherein the scheduling decision layer is specifically configured to generate production forecast instructions based on changes in external production factors captured by a set target or each production node.
9. The architecture of any one of claims 2 to 5 or 7 to 8 wherein the central cloud is further configured to share the computing tasks of an edge cloud when the computing power of the edge cloud is insufficient.
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